Joint multiple-input multiple-output (MIMO) communications and MIMO sensing

Disclosed are systems, apparatuses, processes, and computer-readable media for wireless communications. For example, an example of a process may include receiving, at a network device (e.g., a user equipment (UE)) from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform including communications resources and sensing resources. The waveform has a rank Nt and J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications that is less than Nt. The process may further include processing at least the communications resources of the waveform.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to joint communications and sensing. For example, aspects of the present disclosure relate to joint multiple-input multiple-output (MIMO) communications and MIMO sensing.

BACKGROUND OF THE DISCLOSURE

Due to larger bandwidths being allocated for wireless cellular communications systems (e.g., including 5G and 5G beyond) and more use cases being introduced into the cellular communications systems, joint MIMO communications and MIMO sensing can be an essential feature for existing or future wireless communication systems, such as to enhance the overall spectral efficiency of the wireless communication networks.

SUMMARY

Systems and techniques are described for joint MIMO communications and MIMO sensing at a user equipment (UE). According to at least one example, a method is provided for wireless communications. The method includes: receiving, at the UE from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform comprising communications resources and sensing resources, the waveform having a rank Nt, wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and processing at least the communications resources of the waveform.

In another example, an apparatus for wireless communications is provided that includes at least one memory and at least one processor coupled to the at least one memory. The at least one processor is configured to: receive, from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform comprising communications resources and sensing resources, the waveform having a rank Nt, wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and process at least the communications resources of the waveform.

In another example, a non-transitory computer-readable medium is provided that has stored thereon instructions that, when executed by one or more processors, cause the one or more processors to: receive, from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform comprising communications resources and sensing resources, the waveform having a rank Nt, wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and process at least the communications resources of the waveform.

In another example, an apparatus for wireless communications is provided. The apparatus includes: means for receiving, from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform comprising communications resources and sensing resources, the waveform having a rank Nt, wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and means for processing at least the communications resources of the waveform.

According to one or more other examples, a method is provided for wireless communications at a network entity. The method includes: generating, at the network entity, a waveform comprising communications resources and sensing resources based on a maximum of Nt−J sensing streams, the waveform having a rank Nt, wherein the network entity comprises Ntnumber of transmitting antenna elements, and wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and transmitting, via a number of sensing streams based on the maximum of Nt−J sensing streams, the waveform to one or more network devices for MIMO communications and MIMO sensing.

In another example, an apparatus for wireless communications is provided that includes at least one memory and at least one processor coupled to the at least one memory. The at least one processor is configured to: generate a waveform comprising communications resources and sensing resources based on a maximum of Nt−J sensing streams, the waveform having a rank Nt, wherein the apparatus comprises Ntnumber of transmitting antenna elements, and wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and transmit, via a number of sensing streams based on the maximum of Nt−J sensing streams, the waveform to one or more network devices for MIMO communications and MIMO sensing.

In another example, a non-transitory computer-readable medium is provided that has stored thereon instructions that, when executed by one or more processors, cause the one or more processors to: generate a waveform comprising communications resources and sensing resources based on a maximum of Nt−J sensing streams, the waveform having a rank Nt, wherein the apparatus comprises Ntnumber of transmitting antenna elements, and wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and transmit, via a number of sensing streams based on the maximum of Nt−J sensing streams, the waveform to one or more network devices for MIMO communications and MIMO sensing.

In another example, an apparatus for wireless communications is provided. The apparatus includes: means for generating a waveform comprising communications resources and sensing resources based on a maximum of Nt−J sensing streams, the waveform having a rank Nt, wherein the apparatus comprises Ntnumber of transmitting antenna elements, and wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and means for transmitting, via a number of sensing streams based on the maximum of Nt−J sensing streams, the waveform to one or more network devices for MIMO communications and MIMO sensing.

In some aspects, the apparatus is, is part of, and/or includes a UE, such as a mobile device (e.g., a mobile telephone and/or mobile handset and/or so-called “smart phone” or other mobile device), an extended reality (XR) device (e.g., a virtual reality (VR) device, an augmented reality (AR) device, or a mixed reality (MR) device such as a head-mounted display (HMD) device), a wearable device (e.g., a network-connected watch or other wearable device), a wireless communication device, a camera, a personal computer, a laptop computer, a server computer, a vehicle or a computing device or component of a vehicle, another device, or a combination thereof. In some aspects, the apparatus includes a camera or multiple cameras for capturing one or more images. In some aspects, the apparatus further includes a display for displaying one or more images, notifications, and/or other displayable data. In some aspects, the apparatuses described above can include one or more sensors (e.g., one or more inertial measurement units (IMUs), such as one or more gyroscopes, one or more gyrometers, one or more accelerometers, any combination thereof, and/or other sensor).

DETAILED DESCRIPTION

Certain aspects of this disclosure are provided below for illustration purposes. Alternate aspects may be devised without departing from the scope of the disclosure. Additionally, well-known elements of the disclosure will not be described in detail or will be omitted so as not to obscure the relevant details of the disclosure. Some of the aspects described herein may be applied independently and some of them may be applied in combination as would be apparent to those of skill in the art. In the following description, for the purposes of explanation, specific details are set forth in order to provide a thorough understanding of aspects of the application. However, it will be apparent that various aspects may be practiced without these specific details. The figures and description are not intended to be restrictive.

As previously mentioned, due to larger bandwidths being allocated for wireless communications systems (e.g., including cellular communications systems such as 4G/LTE, 5G/NR, and beyond) and more use cases being introduced into the wireless communications systems, joint multiple-input multiple-output (MIMO) communications and MIMO sensing can be an essential feature for wireless communications systems.

Radar sensing systems typically use radio frequency (RF) waveforms to perform RF sensing to determine or estimate one or more characteristics of a target object, such as the distance, angle, and/or velocity of the target object. A target object may include a vehicle, an obstruction, a user, a building, or other object. A typical radar system includes at least one transmitter, at least one receiver, and at least one processor. A radar sensing system may perform monostatic sensing when one receiver is employed that is co-located with a transmitter. A radar system may perform bistatic sensing when one receiver of a first device is employed that is located remote from a transmitter of a second device. Similarly, a radar system may perform multi-static sensing when multiple receivers of multiple devices are employed that are all located remotely from at least one transmitter of at least one device.

During operation of a radar sensing system, a transmitter transmits an electromagnetic (EM) signal in the RF domain towards a target object. The signal reflects off of the target object to produce one or more reflection signals, which provides information or properties regarding the target, such as target object's location and speed. At least one receiver receives the one or more reflection signals and at least one processor, which may be associated with at least one receiver, utilizes the information from the one or more reflection signals to determine information or properties of the target object. A target object can also be referred herein as a target.

It should be noted that these radar sensing signals, which can be referred to as radar reference signals (RSs), are typically designed for and solely used for sensing purposes. Radar RSs do not contain any communications information. Conversely, communication RSs are typically designed for and solely used for communications purposes, including estimating channel parameters for communications.

Cellular communications systems are designed to transmit communications signals on designated communications frequency bands (e.g., 23 gigahertz (GHz), 3.5 GHz, etc. for 5G/NR, 2.2 GHz for LTE, among others). RF sensing systems are designed to transmit RF sensing signals on designated radar RF frequency bands (e.g., 77 GHz for autonomous driving). The spectrum for communication and sensing is very likely to be shared in future cellular communication systems, in which case the communications and sensing should be jointly considered.

MIMO is a multi-antenna spectrum-efficient technique, and has become a leading driver of next-generation antenna technology for cellular networks. A MIMO system may transmit more than one signal over the same channel, providing for an increase in spectral efficiency and overall throughput. By taking advantage of spatial separation, the antennas of a MIMO system are spaced at specific distances and angles to compensate for self-interference. A MIMO system can provide a robust wireless communication mechanism to address fading and shadowing caused by multiple transmission paths and long distances. In a MIMO system, various streams of data can be transmitted at the same time, which can provide for multiplexing gains and an improvement in the overall throughput. For at least these reasons, MIMO has been recently employed in cellular wireless communications technology and is included in various next-generation wireless projects and standards, including 5G NR.

A simple form of MIMO is point-to-point MIMO. In point-to-point MIMO, two systems (e.g., a base station and a UE) each employ multiple antennas to communicate with each other. The use of multiple antennas provides for an increase in the capacity of the air interface. However, point-to-point MIMO employs a multi-antenna configuration that requires additional hardware at both the base station and the end-user device (e.g., in the UE). The requirement of additional hardware at both the base station and the user device is a disadvantage to point-to-point MIMO because it increases the overall system complexity. It should be noted that, in a typical mobile communications system, the end-user equipment (e.g., UE) may not be able to support multiple antennas due to its small physical size and/or the low-cost requirements of the UE devices.

An enhancement of point-to-point MIMO is single-user MIMO (SU-MIMO), which provides for an increase in the data rate by transmitting multiple data streams to a specific user device (e.g., specific UE). Similar to point-to-point MIMO, SU-MIMO has the drawback of requiring the user device (e.g., UE) to support multiple antennas.

Conversely to point-to-point MIMO and SU-MIMO, multiple-user MIMO (MU-MIMO) does not have the disadvantage of requiring the user device to support multiple antennas. In MU-MIMO, multiple users share the same time and frequency resources, while each base station (e.g., a next generation node B (gNB), evolved node B (eNB), or portion thereof such as a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC) is equipped with multiple antennas (e.g., antenna arrays) and serves many users (e.g., UEs) simultaneously. Each end-user device (e.g., UE) need only employ a single antenna and, as such, complex hardware is only needed at the base station side. The cost and complexity of the antenna system are significantly reduced for a MU-MIMO system because low-cost single antennas (e.g., dipole antennas) may be employed for the end-user devices (e.g., UEs), and the more expensive, complex hardware may be utilized only at the base station side.

Due to the variety in the distance, angle, and quality of the signals of the multiple users in MU-MIMO systems, the performance of MU-MIMO systems is generally less affected by the transmission environment as compared to point-to-point MIMO. This advantage is achieved by MU-MIMO systems employing selective beamforming and power control to cancel interference. MU-MIMO systems offer high reliability and throughput and, as such, have become an integral part of wireless communication systems, including Wi-Fi, LTE, and 5G networks.

Massive MIMO (mMIMO) is a form a MU-MIMO that employs a larger number of antennas at the base stations than MU-MIMO and, as such, the number of users (e.g., UEs) served can be increased significantly over MU-MIMO systems (e.g., in mMIMO, a single base station with many antennas can serve a large number of users). With a large number of antennas in each base station, the channel vectors between users (e.g., UEs) and the base station are per pair almost rectangular and, as such, can provide for exceptional linear transmissions. In mMIMO, a large throughput can be achieved due to multiplexing gain, diversity gain, and array gain. The large number of antennas at the base stations, in mMIMO, may serve hundreds of users with the same frequency resource by taking advantage of antenna beamforming techniques.

In mMIMO, the more antennas employed for each base station, the more robust the communications operation. Theoretically, mMIMO may employ an infinite number of antennas at each of the base stations. But, usually (e.g., in 5G networks), 64 to 128 (e.g., 64 receive antennas and 64 transmit antennas) antennas have been utilized practically in mMIMO base stations. A prominent advantage of mMIMO is that sophisticated hardware is only needed at the base stations, not at the user devices (e.g., UEs), which each only require a single antenna and a simple antenna design. Another advantage of mMIMO is that it has an extensible architecture that can be easily scaled up to serve more users by only needing to upgrade the antenna systems on the base stations.

In some aspects of the present disclosure, systems, apparatuses, methods (also referred to as processes), and computer-readable media (collectively referred to herein as “systems and techniques”) are described herein that provide for joint MIMO communications and MIMO sensing. In one or more examples, the systems and techniques of the present disclosure employ a unified waveform for both communications and sensing, which may be referred to as a “joint communications and sensing (JCS) waveform,” with a MU-MIMO and/or mMIMO systems architecture. One advantage of such a JCS waveform is that it provides a high spectral efficiency since the spectrum can be fully reused. Another advantage is that such JCS waveform allows for unified hardware that can be utilized for both communications and sensing. Additional details regarding the disclosed systems and techniques for joint MIMO communications and MIMO sensing, as well as specific implementations, are described below with respect to the figures.

Additional aspects of the present disclosure are described in more detail below.

As used herein, the terms “user equipment” (UE) and “network entity” are not intended to be specific or otherwise limited to any particular radio access technology (RAT), unless otherwise noted. In general, a UE may be any wireless communication device (e.g., a mobile phone, router, tablet computer, laptop computer, and/or tracking device, etc.), wearable (e.g., smartwatch, smart-glasses, wearable ring, and/or an extended reality (XR) device such as a virtual reality (VR) headset, an augmented reality (AR) headset or glasses, or a mixed reality (MR) headset), vehicle (e.g., automobile, motorcycle, bicycle, etc.), and/or Internet of Things (IoT) device, etc., used by a user to communicate over a wireless communications network. A UE may be mobile or may (e.g., at certain times) be stationary, and may communicate with a radio access network (RAN). As used herein, the term “UE” may be referred to interchangeably as an “access terminal” or “AT,” a “client device,” a “wireless device,” a “subscriber device,” a “subscriber terminal,” a “subscriber station,” a “user terminal” or “UT,” a “mobile device,” a “mobile terminal,” a “mobile station,” or variations thereof. Generally, UEs can communicate with a core network via a RAN, and through the core network the UEs can be connected with external networks such as the Internet and with other UEs. Of course, other mechanisms of connecting to the core network and/or the Internet are also possible for the UEs, such as over wired access networks, wireless local area network (WLAN) networks (e.g., based on IEEE 802.11 communication standards, etc.) and so on.

A network entity can be implemented in an aggregated or monolithic base station architecture, or alternatively, in a disaggregated base station architecture, and may include one or more of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC. A base station (e.g., with an aggregated/monolithic base station architecture or disaggregated base station architecture) may operate according to one of several RATs in communication with UEs depending on the network in which it is deployed, and may be alternatively referred to as an access point (AP), a network node, a NodeB (NB), an evolved NodeB (eNB), a next generation eNB (ng-eNB), a New Radio (NR) Node B (also referred to as a gNB or gNodeB), etc. A base station may be used primarily to support wireless access by UEs, including supporting data, voice, and/or signaling connections for the supported UEs. In some systems, a base station may provide edge node signaling functions while in other systems it may provide additional control and/or network management functions. A communication link through which UEs can send signals to a base station is called an uplink (UL) channel (e.g., a reverse traffic channel, a reverse control channel, an access channel, etc.). A communication link through which the base station can send signals to UEs is called a downlink (DL) or forward link channel (e.g., a paging channel, a control channel, a broadcast channel, or a forward traffic channel, etc.). The term traffic channel (TCH), as used herein, can refer to either an uplink, reverse or downlink, and/or a forward traffic channel.

The term “network entity” or “base station” (e.g., with an aggregated/monolithic base station architecture or disaggregated base station architecture) may refer to a single physical Transmission-Reception Point (TRP) or to multiple physical Transmission-Reception Points (TRPs) that may or may not be co-located. For example, where the term “network entity” or “base station” refers to a single physical TRP, the physical TRP may be an antenna of the base station corresponding to a cell (or several cell sectors) of the base station. Where the term “network entity” or “base station” refers to multiple co-located physical TRPs, the physical TRPs may be an array of antennas (e.g., as in a multiple-input multiple-output (MIMO) system or where the base station employs beamforming) of the base station. Where the term “base station” refers to multiple non-co-located physical TRPs, the physical TRPs may be a distributed antenna system (DAS) (a network of spatially separated antennas connected to a common source via a transport medium) or a remote radio head (RRH) (a remote base station connected to a serving base station). Alternatively, the non-co-located physical TRPs may be the serving base station receiving the measurement report from the UE and a neighbor base station whose reference radio frequency (RF) signals (or simply “reference signals”) the UE is measuring. Because a TRP is the point from which a base station transmits and receives wireless signals, as used herein, references to transmission from or reception at a base station are to be understood as referring to a particular TRP of the base station.

According to various aspects,FIG.1Aillustrates an exemplary wireless communications system100, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. The wireless communications system100(which may also be referred to as a wireless wide area network (WWAN)) can include various base stations102and various UEs104. In some aspects, the base stations102may also be referred to as “network entities” or “network nodes.” One or more of the base stations102can be implemented in an aggregated or monolithic base station architecture. Additionally or alternatively, one or more of the base stations102can be implemented in a disaggregated base station architecture, and may include one or more of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC. The base stations102can include macro cell base stations (high power cellular base stations) and/or small cell base stations (low power cellular base stations). In an aspect, the macro cell base station may include eNBs and/or ng-eNBs where the wireless communications system100corresponds to a long term evolution (LTE) network, or gNBs where the wireless communications system100corresponds to a NR network, or a combination of both, and the small cell base stations may include femtocells, picocells, microcells, etc.

The base stations102may collectively form a RAN and interface with a core network170(e.g., an evolved packet core (EPC) or a 5G core (5GC)) through backhaul links122, and through the core network170to one or more location servers172(which may be part of core network170or may be external to core network170). In addition to other functions, the base stations102may perform functions that relate to one or more of transferring user data, radio channel ciphering and deciphering, integrity protection, header compression, mobility control functions (e.g., handover, dual connectivity), inter-cell interference coordination, connection setup and release, load balancing, distribution for non-access stratum (NAS) messages, NAS node selection, synchronization, RAN sharing, multimedia broadcast multicast service (MBMS), subscriber and equipment trace, RAN information management (RIM), paging, positioning, and delivery of warning messages. The base stations102may communicate with each other directly or indirectly (e.g., through the EPC or 5GC) over backhaul links134, which may be wired and/or wireless.

The wireless communications system100may further include a WLAN AP150in communication with WLAN stations (STAs)152via communication links154in an unlicensed frequency spectrum (e.g., 5 Gigahertz (GHz)). When communicating in an unlicensed frequency spectrum, the WLAN STAs152and/or the WLAN AP150may perform a clear channel assessment (CCA) or listen before talk (LBT) procedure prior to communicating in order to determine whether the channel is available. In some examples, the wireless communications system100can include devices (e.g., UEs, etc.) that communicate with one or more UEs104, base stations102, APs150, etc. utilizing the ultra-wideband (UWB) spectrum. The UWB spectrum can range from 3.1 to 10.5 GHz.

Receive beams may be spatially related. A spatial relation means that parameters for a transmit beam for a second reference signal can be derived from information about a receive beam for a first reference signal. For example, a UE may use a particular receive beam to receive one or more reference downlink reference signals (e.g., positioning reference signals (PRS), tracking reference signals (TRS), phase tracking reference signal (PTRS), cell-specific reference signals (CRS), channel state information reference signals (CSI-RS), primary synchronization signals (PSS), secondary synchronization signals (SSS), synchronization signal blocks (SSBs), etc.) from a network node or entity (e.g., a base station). The UE can then form a transmit beam for sending one or more uplink reference signals (e.g., uplink positioning reference signals (UL-PRS), sounding reference signal (SRS), demodulation reference signals (DMRS), PTRS, etc.) to that network node or entity (e.g., a base station) based on the parameters of the receive beam.

For example, still referring toFIG.1A, one of the frequencies utilized by the macro cell base stations102may be an anchor carrier (or “PCell”) and other frequencies utilized by the macro cell base stations102and/or the mmW base station180may be secondary carriers (“SCells”). In carrier aggregation, the base stations102and/or the UEs104may use spectrum up to Y MHz (e.g., 5, 10, 15, 20, 100 MHz) bandwidth per carrier up to a total of Yx MHz (x component carriers) for transmission in each direction. The component carriers may or may not be adjacent to each other on the frequency spectrum. Allocation of carriers may be asymmetric with respect to the downlink and uplink (e.g., more or less carriers may be allocated for downlink than for uplink). The simultaneous transmission and/or reception of multiple carriers enables the UE104/182to significantly increase its data transmission and/or reception rates. For example, two 20 MHz aggregated carriers in a multi-carrier system would theoretically lead to a two-fold increase in data rate (i.e., 40 MHz), compared to that attained by a single 20 MHz carrier.

In order to operate on multiple carrier frequencies, a base station102and/or a UE104is equipped with multiple receivers and/or transmitters. For example, a UE104may have two receivers, “Receiver 1” and “Receiver 2,” where “Receiver 1” is a multi-band receiver that can be tuned to band (i.e., carrier frequency) ‘X’ or band ‘Y,’ and “Receiver 2” is a one-band receiver tuneable to band ‘Z’ only. In this example, if the UE104is being served in band ‘X,’ band ‘X’ would be referred to as the PCell or the active carrier frequency, and “Receiver 1” would need to tune from band ‘X’ to band ‘Y’ (an SCell) in order to measure band ‘Y’ (and vice versa). In contrast, whether the UE104is being served in band ‘X’ or band ‘Y,’ because of the separate “Receiver 2,” the UE104can measure band ‘Z’ without interrupting the service on band ‘X’ or band ‘Y.’

As previously mentioned,FIG.1Bshows a diagram illustrating an example disaggregated base station101architecture. The disaggregated base station101architecture may include one or more central units (CUs)111that can communicate directly with a core network123via a backhaul link, or indirectly with the core network123through one or more disaggregated base station units (such as a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC)127via an E2 link, or a Non-Real Time (Non-RT) RIC117associated with a Service Management and Orchestration (SMO) Framework107, or both). A CU111may communicate with one or more distributed units (DUs)131via respective midhaul links, such as an F1 interface. The DUs131may communicate with one or more radio units (RUs)141via respective fronthaul links. The RUs141may communicate with respective UEs121via one or more RF access links. In some implementations, the UE121may be simultaneously served by multiple RUs141.

Each of the units, i.e., the CUs111, the DUs131, the RUs141, as well as the Near-RT RICs127, the Non-RT RICs117and the SMO Framework107, may include one or more interfaces or be coupled to one or more interfaces configured to receive or transmit signals, data, or information (collectively, signals) via a wired or wireless transmission medium. Each of the units, or an associated processor or controller providing instructions to the communication interfaces of the units, can be configured to communicate with one or more of the other units via the transmission medium. For example, the units can include a wired interface configured to receive or transmit signals over a wired transmission medium to one or more of the other units. Additionally, the units can include a wireless interface, which may include a receiver, a transmitter or transceiver (such as an RF transceiver), configured to receive or transmit signals, or both, over a wireless transmission medium to one or more of the other units.

Lower-layer functionality can be implemented by one or more RUs141. In some deployments, an RU141, controlled by a DU131, may correspond to a logical node that hosts RF processing functions, or low-PHY layer functions (such as performing fast Fourier transform (FFT), inverse FFT (iFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, or the like), or both, based at least in part on the functional split, such as a lower layer functional split. In such an architecture, the RU(s)141can be implemented to handle over the air (OTA) communication with one or more UEs121. In some implementations, real-time and non-real-time aspects of control and user plane communication with the RU(s)141can be controlled by the corresponding DU131. In some scenarios, this configuration can enable the DU(s)131and the CU111to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

The SMO Framework107may be configured to support RAN deployment and provisioning of non-virtualized and virtualized network elements. For non-virtualized network elements, the SMO Framework107may be configured to support the deployment of dedicated physical resources for RAN coverage requirements which may be managed via an operations and maintenance interface (such as an O1 interface). For virtualized network elements, the SMO Framework107may be configured to interact with a cloud computing platform (such as an open cloud (O-Cloud)191) to perform network element life cycle management (such as to instantiate virtualized network elements) via a cloud computing platform interface (such as an O2 interface). Such virtualized network elements can include, but are not limited to, CUs111, DUs131, RUs141and Near-RT RICs127. In some implementations, the SMO Framework107can communicate with a hardware aspect of a 4G RAN, such as an open eNB (O-eNB)113, via an O1 interface. Additionally, in some implementations, the SMO Framework107can communicate directly with one or more RUs141via an O1 interface. The SMO Framework107also may include a Non-RT RIC117configured to support functionality of the SMO Framework107.

The Non-RT RIC117may be configured to include a logical function that enables non-real-time control and optimization of RAN elements and resources, Artificial Intelligence/Machine Learning (AI/ML) workflows including model training and updates, or policy-based guidance of applications/features in the Near-RT RIC127. The Non-RT RIC117may be coupled to or communicate with (such as via an A1 interface) the Near-RT RIC127. The Near-RT RIC127may be configured to include a logical function that enables near-real-time control and optimization of RAN elements and resources via data collection and actions over an interface (such as via an E2 interface) connecting one or more CUs111, one or more DUs131, or both, as well as an O-eNB113, with the Near-RT RIC127.

In some implementations, to generate AI/ML models to be deployed in the Near-RT RIC127, the Non-RT RIC117may receive parameters or external enrichment information from external servers. Such information may be utilized by the Near-RT RIC127and may be received at the SMO Framework107or the Non-RT RIC117from non-network data sources or from network functions. In some examples, the Non-RT RIC117or the Near-RT RIC127may be configured to tune RAN behavior or performance. For example, the Non-RT RIC117may monitor long-term trends and patterns for performance and employ AI/ML models to perform corrective actions through the SMO Framework107(such as reconfiguration via O1) or via creation of RAN management policies (such as A1 policies).

FIG.2shows a block diagram of a design of a base station102and a UE104that enable transmission and processing of signals exchanged between the UE and the base station, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. Design200includes components of a base station102and a UE104, which may be one of the base stations102and one of the UEs104inFIG.1. Base station102may be equipped with T antennas234athrough234t, and UE104may be equipped with R antennas252athrough252r, where in general T≥1 and R≥1.

At base station102, a transmit processor220may receive data from a data source212for one or more UEs, select one or more modulation and coding schemes (MCS) for each UE based at least in part on channel quality indicators (CQIs) received from the UE, process (e.g., encode and modulate) the data for each UE based at least in part on the MCS(s) selected for the UE, and provide data symbols for all UEs. Transmit processor220may also process system information (e.g., for semi-static resource partitioning information (SRPI) and/or the like) and control information (e.g., CQI requests, grants, upper layer signaling, and/or the like) and provide overhead symbols and control symbols. Transmit processor220may also generate reference symbols for reference signals (e.g., the cell-specific reference signal (CRS)) and synchronization signals (e.g., the primary synchronization signal (PSS) and secondary synchronization signal (SSS)). A transmit (TX) multiple-input multiple-output (MIMO) processor230may perform spatial processing (e.g., precoding) on the data symbols, the control symbols, the overhead symbols, and/or the reference symbols, if applicable, and may provide T output symbol streams to T modulators (MODs)232athrough232t. The modulators232athrough232tare shown as a combined modulator-demodulator (MOD-DEMOD). In some cases, the modulators and demodulators can be separate components. Each modulator of the modulators232ato232tmay process a respective output symbol stream, e.g., for an orthogonal frequency-division multiplexing (OFDM) scheme and/or the like, to obtain an output sample stream. Each modulator of the modulators232ato232tmay further process (e.g., convert to analog, amplify, filter, and upconvert) the output sample stream to obtain a downlink signal. T downlink signals may be transmitted from modulators232ato232tvia T antennas234athrough234t, respectively. According to certain aspects described in more detail below, the synchronization signals can be generated with location encoding to convey additional information.

At UE104, antennas252athrough252rmay receive the downlink signals from base station102and/or other base stations and may provide received signals to demodulators (DEMODs)254athrough254r, respectively. The demodulators254athrough254rare shown as a combined modulator-demodulator (MOD-DEMOD). In some cases, the modulators and demodulators can be separate components. Each demodulator of the demodulators254athrough254rmay condition (e.g., filter, amplify, downconvert, and digitize) a received signal to obtain input samples. Each demodulator of the demodulators254athrough254rmay further process the input samples (e.g., for OFDM and/or the like) to obtain received symbols. A MIMO detector256may obtain received symbols from all R demodulators254athrough254r, perform MIMO detection on the received symbols if applicable, and provide detected symbols. A receive processor258may process (e.g., demodulate and decode) the detected symbols, provide decoded data for UE104to a data sink260, and provide decoded control information and system information to a controller/processor280. A channel processor may determine reference signal received power (RSRP), received signal strength indicator (RSSI), reference signal received quality (RSRQ), channel quality indicator (CQI), and/or the like.

On the uplink, at UE104, a transmit processor264may receive and process data from a data source262and control information (e.g., for reports comprising RSRP, RSSI, RSRQ, CQI, and/or the like) from controller/processor280. Transmit processor264may also generate reference symbols for one or more reference signals (e.g., based at least in part on a beta value or a set of beta values associated with the one or more reference signals). The symbols from transmit processor264may be precoded by a TX-MIMO processor266if application, further processed by modulators254athrough254r(e.g., for DFT-s-OFDM, CP-OFDM, and/or the like), and transmitted to base station102. At base station102, the uplink signals from UE104and other UEs may be received by antennas234athrough234t, processed by demodulators232athrough232t, detected by a MIMO detector236if applicable, and further processed by a receive processor238to obtain decoded data and control information sent by UE104. Receive processor238may provide the decoded data to a data sink239and the decoded control information to controller (processor)240. Base station102may include communication unit244and communicate to a network controller231via communication unit244. Network controller231may include communication unit294, controller/processor290, and memory292.

In some aspects, one or more components of UE104may be included in a housing. Controller240of base station102, controller/processor280of UE104, and/or any other component(s) ofFIG.2may perform one or more techniques associated with joint MIMO communications and MIMO sensing.

Memories242and282may store data and program codes for the base station102and the UE104, respectively. A scheduler246may schedule UEs for data transmission on the downlink, uplink, and/or sidelink.

In some implementations, the UE104may include a radar receiver that includes: means for determining a sensing measurement accuracy of the radar receiver based on one or more sensing measurements associated with at least one target; and means for transmitting, based on the sensing measurement accuracy, a message to a network entity, the message including an indication to modify an allocation of sensing resources associated with the radar receiver for communications data. In some examples, the means for determining can include controller/processor280, memory282, receive processor258, transmit processor264, any combination thereof, or any other component(s) of the UE104. In some examples, the means for transmitting can include controller/processor280, transmit processor264, TX MIMO processor266, DEMODs254athrough254r, antennas252athrough252r, any combination thereof, or any other component(s) of the UE104.

In some implementations, the base station102may include: means for receiving a message from a radar receiver, the message including an indication to modify an allocation of sensing resources associated with the radar receiver for communications data; and means for determining, based on the message, at least a portion of the sensing resources for the communications data. In some examples, the means for receiving can include controller/processor240, transmit processor224, TX MIMO processor236, DEMODs232athrough232t, antennas234athrough234t, the scheduler246, any combination thereof, or any other component(s) of the base station102. In some examples, the means for determining can include controller/processor240, memory242, receive processor238, transmit processor220, the scheduler246, any combination thereof, or any other component(s) of the base station102.

In some implementations, the base station102may include a means for receiving a resource allocation request from a second network entity for an allocation of sensing resources for communications data, and a means for transmitting a message to one or more radar devices, the message including information associated with an allocation of at least a portion of resources associated with the one or more radar devices for the communications data. In some examples, the means for receiving can include controller/processor240, transmit processor224, TX MIMO processor236, DEMODs232athrough232t, antennas234athrough234t, the scheduler246, any combination thereof, or any other component(s) of the base station102. In some examples, the means for transmitting can include controller/processor240, transmit processor224, TX MIMO processor236, DEMODs232athrough232t, antennas234athrough234t, the scheduler246, any combination thereof, or any other component(s) of the base station102.

Various radio frame structures may be used to support downlink, uplink, and sidelink transmissions between network nodes (e.g., base stations and UEs).FIG.3is a diagram300illustrating an example of a frame structure, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, according to some aspects of the disclosure. Other wireless communications technologies may have different frame structures and/or different channels.

LTE supports a single numerology (subcarrier spacing, symbol length, etc.). In contrast, NR may support multiple numerologies (μ). For example, subcarrier spacing (SCS) of 15 kHz, 30 kHz, 60 kHz, 120 kHz, and 240 kHz or greater may be available. Table 1 provided below lists some various parameters for different NR numerologies.

In one example, a numerology of 15 kHz is used. Thus, in the time domain, a 10 millisecond (ms) frame is divided into 10 equally sized subframes of 1 ms each, and each subframe includes one time slot. InFIG.3, time is represented horizontally (e.g., on the X axis) with time increasing from left to right, while frequency is represented vertically (e.g., on the Y axis) with frequency increasing (or decreasing) from bottom to top.

A resource grid may be used to represent time slots, each time slot including one or more time-concurrent resource blocks (RBs) (also referred to as physical RBs (PRBs)) in the frequency domain.FIG.3illustrates an example of a resource block (RB)302, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. Data or information for joint MIMO communications and MIMO sensing may be included in one or more RBs302. The RB302is arranged with the time domain on the horizontal (or x-) axis and the frequency domain on the vertical (or y-) axis. As shown, the RB302may be 180 kilohertz (kHz) wide in frequency and one slot long in time (with a slot being 1 milliseconds (ms) in time). In some cases, the slot may include fourteen symbols (e.g., in a slot configuration 0). The RB302includes twelve subcarriers (along the y-axis) and fourteen symbols (along the x-axis).

An intersection of a symbol and subcarrier can be referred to as a resource element (RE)304or tone. The RB302ofFIG.3includes multiple REs, including the resource element (RE)304. For instance, a RE304is 1 subcarrier×1 symbol (e.g., OFDM symbol), and is the smallest discrete part of the subframe. A RE304includes a single complex value representing data from a physical channel or signal. The number of bits carried by each RE304depends on the modulation scheme.

In some aspects, some REs304can be used to transmit downlink reference (pilot) signals (DL-RS). The DL-RS can include Positioning Reference Signal (PRS), Tracking Reference Signal (TRS), Phase Tracking Reference Signal (PTRS), Channel State Information Reference Signal (CSI-RS), Demodulation Reference Signal (DMRS), Primary Synchronization Signal (PSS), Secondary Synchronization Signal (SSS), etc. The resource grid ifFIG.3illustrates exemplary locations of REs304used to transmit DL-RS (labeled “R”).

FIG.4is a block diagram illustrating an example of a computing system470of an electronic device407, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. The electronic device407is an example of a device that can include hardware and software for the purpose of connecting and exchanging data with other devices and systems using a communications network (e.g., a 3rdGeneration Partnership network, such as a 5thGeneration (5G)/New Radio (NR) network, a 4thGeneration (4G)/Long Term Evolution (LTE) network, a WiFi network, or other communications network). For example, the electronic device407can include, or be a part of, a mobile device (e.g., a mobile telephone), a wearable device (e.g., a network-connected or smart watch), an extended reality device (e.g., a virtual reality (VR) device, an augmented reality (AR) device, or a mixed reality (MR) device), a personal computer, a laptop computer, a tablet computer, an Internet-of-Things (IoT) device, a wireless access point, a router, a vehicle or component of a vehicle, a server computer, a robotics device, and/or other device used by a user to communicate over a wireless communications network. In some cases, the device407can be referred to as user equipment (UE), such as when referring to a device configured to communicate using 5G/NR, 4G/LTE, or other telecommunication standard. In some cases, the device can be referred to as a station (STA), such as when referring to a device configured to communicate using the Wi-Fi standard.

The computing system470includes software and hardware components that can be electrically or communicatively coupled via a bus489(or may otherwise be in communication, as appropriate). For example, the computing system470includes one or more processors484. The one or more processors484can include one or more CPUs, ASICs, FPGAs, APs, GPUs, VPUs, NSPs, microcontrollers, dedicated hardware, any combination thereof, and/or other processing device/s and/or system/s. The bus489can be used by the one or more processors484to communicate between cores and/or with the one or more memory devices486.

The computing system470may also include one or more memory devices486, one or more digital signal processors (DSPs)482, one or more subscriber identity modules (SIMs)474, one or more modems476, one or more wireless transceivers478, one or more antennas487, one or more input devices472(e.g., a camera, a mouse, a keyboard, a touch sensitive screen, a touch pad, a keypad, a microphone or a microphone array, and/or the like), and one or more output devices480(e.g., a display, a speaker, a printer, and/or the like).

The one or more wireless transceivers478can receive wireless signals (e.g., signal488) via antenna487from one or more other devices, such as other user devices, network devices (e.g., base stations such as evolved Node Bs (eNBs) and/or gNodeBs (gNBs), WiFi access points (APs) such as routers, range extenders or the like, etc.), cloud networks, and/or the like. In some examples, the computing system470can include multiple antennas or an antenna array that can facilitate simultaneous transmit and receive functionality. Antenna487can be an omnidirectional antenna such that RF signals can be received from and transmitted in all directions. The wireless signal488may be transmitted via a wireless network. The wireless network may be any wireless network, such as a cellular or telecommunications network (e.g., 3G, 4G, 5G, etc.), wireless local area network (e.g., a WiFi network), a Bluetooth™ network, and/or other network. In some examples, the one or more wireless transceivers478may include an RF front end including one or more components, such as an amplifier, a mixer (also referred to as a signal multiplier) for signal down conversion, a frequency synthesizer (also referred to as an oscillator) that provides signals to the mixer, a baseband filter, an analog-to-digital converter (ADC), one or more power amplifiers, among other components. The RF front-end can generally handle selection and conversion of the wireless signals488into a baseband or intermediate frequency and can convert the RF signals to the digital domain.

In some cases, the computing system470can include a coding-decoding device (or CODEC) configured to encode and/or decode data transmitted and/or received using the one or more wireless transceivers478. In some cases, the computing system470can include an encryption-decryption device or component configured to encrypt and/or decrypt data (e.g., according to the Advanced Encryption Standard (AES) and/or Data Encryption Standard (DES) standard) transmitted and/or received by the one or more wireless transceivers478.

The one or more SIMs474can each securely store an international mobile subscriber identity (IMSI) number and related key assigned to the user of the electronic device407. The IMSI and key can be used to identify and authenticate the subscriber when accessing a network provided by a network service provider or operator associated with the one or more SIMs474. The one or more modems476can modulate one or more signals to encode information for transmission using the one or more wireless transceivers478. The one or more modems476can also demodulate signals received by the one or more wireless transceivers478in order to decode the transmitted information. In some examples, the one or more modems476can include a WiFi modem, a 4G (or LTE) modem, a 5G (or NR) modem, and/or other types of modems. The one or more modems476and the one or more wireless transceivers478can be used for communicating data for the one or more SIMs474.

The computing system470can also include (and/or be in communication with) one or more non-transitory machine-readable storage media or storage devices (e.g., one or more memory devices486), which can include, without limitation, local and/or network accessible storage, a disk drive, a drive array, an optical storage device, a solid-state storage device such as a RAM and/or a ROM, which can be programmable, flash-updateable and/or the like. Such storage devices may be configured to implement any appropriate data storage, including without limitation, various file systems, database structures, and/or the like.

In various aspects, functions may be stored as one or more computer-program products (e.g., instructions or code) in memory device(s)486and executed by the one or more processor(s)484and/or the one or more DSPs482. The computing system470can also include software elements (e.g., located within the one or more memory devices486), including, for example, an operating system, device drivers, executable libraries, and/or other code, such as one or more application programs, which may comprise computer programs implementing the functions provided by various aspects, and/or may be designed to implement methods and/or configure systems, as described herein.

In some aspects, the electronic device407can include means for performing operations described herein. The means can include one or more of the components of the computing system470. For example, the means for performing operations described herein may include one or more of input device(s)472, SIM(s)474, modems(s)476, wireless transceiver(s)478, output device(s)480, DSP(s)482, processors484, memory device(s)486, and/or antenna(s)487.

In some aspects, the electronic device407can include means for providing joint MIMO communications and MIMO sensing. In some examples, any or all of these means can include the one or more wireless transceivers478, the one or more modems476, the one or more processors484, the one or more DSPs482, the one or more memory devices486, any combination thereof, or other component(s) of the electronic device407.

FIG.5is a diagram illustrating an example of a wireless device500utilizing RF monostatic sensing techniques, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, to determine one or more characteristics (e.g., location, speed or velocity, heading, etc.) of a target502object, in accordance with some aspects of the present disclosure. In particular,FIG.5is a diagram illustrating an example of a wireless device500(e.g., a transmit/receive sensing node) that utilizes RF sensing techniques (e.g., monostatic sensing) to perform one or more functions, such as detecting a presence and location of a target502(e.g., an object, user, or vehicle), which in this figure is illustrated in the form of a vehicle.

In some examples, the wireless device500can be a mobile phone, a tablet computer, a wearable device, a vehicle, an extending reality (XR) device, a computing device or component of a vehicle, or other device (e.g., device407ofFIG.4) that includes at least one RF interface. In some examples, the wireless device500can be a device that provides connectivity for a user device (e.g., for electronic device407ofFIG.4), such as a base station (e.g., a gNB, eNB, etc.), a wireless access point (AP), or other device that includes at least one RF interface.

In some aspects, wireless device500can include one or more components for transmitting an RF signal. The wireless device500can include at least one processor522for generating a digital signal or waveform. The wireless device500can also include a digital-to-analog converter (DAC)504that is capable of receiving the digital signal or waveform from the processor(s)522(e.g., a microprocessor), and converting the digital signal or waveform to an analog waveform. The analog signal that is the output of the DAC504can be provided to RF transmitter506for transmission. The RF transmitter506can be a Wi-Fi transmitter, a 5G/NR transmitter, a Bluetooth™ transmitter, or any other transmitter capable of transmitting an RF signal.

RF transmitter506can be coupled to one or more transmitting antennas such as Tx antenna512. In some examples, transmit (Tx) antenna512can be an omnidirectional antenna that is capable of transmitting an RF signal in all directions. For example, Tx antenna512can be an omnidirectional Wi-Fi antenna that can radiate Wi-Fi signals (e.g., 2.4 GHz, 5 GHz, 6 GHz, etc.) in a 360-degree radiation pattern. In another example, Tx antenna512can be a directional antenna that transmits an RF signal in a particular direction.

In some examples, wireless device500can also include one or more components for receiving an RF signal. For example, the receiver lineup in wireless device500can include one or more receiving antennas such as a receive (Rx) antenna514. In some examples, Rx antenna514can be an omnidirectional antenna capable of receiving RF signals from multiple directions. In other examples, Rx antenna514can be a directional antenna that is configured to receive signals from a particular direction. In further examples, the Tx antenna512and/or the Rx antenna514can include multiple antennas (e.g., elements) configured as an antenna array (e.g., a phase antenna array), which may be used for MIMO communications and/or sensing.

Wireless device500can also include an RF receiver510that is coupled to Rx antenna514. RF receiver510can include one or more hardware components for receiving an RF waveform such as a Wi-Fi signal, a Bluetooth™ signal, a 5G/NR signal, or any other RF signal. The output of RF receiver510can be coupled to an analog-to-digital converter (ADC)508. ADC508can be configured to convert the received analog RF waveform into a digital waveform. The digital waveform that is the output of the ADC508can be provided to the processor(s)522for processing. The processor(s)522(e.g., a digital signal processor (DSP)) can be configured for processing the digital waveform.

In one example, wireless device500can implement RF sensing techniques, for example monostatic sensing techniques, by causing a Tx waveform516to be transmitted from Tx antenna512. Although Tx waveform516is illustrated as a single line, in some cases, Tx waveform516can be transmitted in all directions by an omnidirectional Tx antenna512. In one example, Tx waveform516can be a Wi-Fi waveform that is transmitted by a Wi-Fi transmitter in wireless device500. In some cases, Tx waveform516can correspond to a Wi-Fi waveform that is transmitted at or near the same time as a Wi-Fi data communication signal or a Wi-Fi control function signal (e.g., a beacon transmission). In some examples, Tx waveform516can be transmitted using the same or a similar frequency resource as a Wi-Fi data communication signal or a Wi-Fi control function signal (e.g., a beacon transmission). In some aspects, Tx waveform516can correspond to a Wi-Fi waveform that is transmitted separately from a Wi-Fi data communication signal and/or a Wi-Fi control signal (e.g., Tx waveform516can be transmitted at different times and/or using a different frequency resource).

In some examples, Tx waveform516can correspond to a 5G NR waveform that is transmitted at or near the same time as a 5G NR data communication signal or a 5G NR control function signal. In some examples, Tx waveform516can be transmitted using the same or a similar frequency resource as a 5G NR data communication signal or a 5G NR control function signal. In some aspects, Tx waveform516can correspond to a 5G NR waveform that is transmitted separately from a 5G NR data communication signal and/or a 5G NR control signal (e.g., Tx waveform516can be transmitted at different times and/or using a different frequency resource).

In some aspects, one or more parameters associated with Tx waveform516can be modified that may be used to increase or decrease RF sensing resolution. The parameters may include frequency, bandwidth, number of spatial streams, the number of antennas configured to transmit Tx waveform516, the number of antennas configured to receive a reflected RF signal (e.g., Rx waveform518) corresponding to Tx waveform516, the number of spatial links (e.g., number of spatial streams multiplied by number of antennas configured to receive an RF signal), the sampling rate, or any combination thereof. The transmitted waveform (e.g., Tx waveform516) and the received waveform (e.g., Rx waveform518) can include one or more RF sensing signals, which are also referred to as radar reference signals (RSs).

In further examples, Tx waveform516can be implemented to have a sequence that has perfect or almost perfect autocorrelation properties. For instance, Tx waveform516can include single carrier Zadoff sequences or can include symbols that are similar to orthogonal frequency-division multiplexing (OFDM) Long Training Field (LTF) symbols. In some cases, Tx waveform516can include a chirp signal, as used, for example, in a Frequency-Modulated Continuous-Wave (FM-CW) radar system. In some configurations, the chirp signal can include a signal in which the signal frequency increases and/or decreases periodically in a linear and/or an exponential manner.

In some aspects, wireless device500can implement RF sensing techniques by performing alternating transmit and receive functions (e.g., performing a half-duplex operation). For example, wireless device500can alternately enable its RF transmitter506to transmit the Tx waveform516when the RF receiver510is not enabled to receive (i.e. not receiving), and enable its RF receiver510to receive the Rx waveform518when the RF transmitter506is not enabled to transmit (i.e. not transmitting). When the wireless device500is performing a half-duplex operation, the wireless device500may transmit Tx waveform516, which may be a radar RS (e.g., sensing signal).

In other aspects, wireless device500can implement RF sensing techniques by performing concurrent transmit and receive functions (e.g., performing a sub-band or full-band full-duplex operation). For example, wireless device500can enable its RF receiver510to receive at or near the same time as it enables RF transmitter506to transmit Tx waveform516. When the wireless device500is performing a full-duplex operation (e.g., either sub-band full-duplex or full-band full-duplex), the wireless device500may transmit Tx waveform516, which may be a radar RS (e.g., sensing signal).

In some examples, transmission of a sequence or pattern that is included in Tx waveform516can be repeated continuously such that the sequence is transmitted a certain number of times or for a certain duration of time. In some examples, repeating a pattern in the transmission of Tx waveform516can be used to avoid missing the reception of any reflected signals if RF receiver510is enabled after RF transmitter506. In one example implementation, Tx waveform516can include a sequence having a sequence length L that is transmitted two or more times, which can allow RF receiver510to be enabled at a time less than or equal to L in order to receive reflections corresponding to the entire sequence without missing any information.

By implementing alternating or simultaneous transmit and receive functionality (e.g. half-duplex or full-duplex operation), wireless device500can receive signals that correspond to Tx waveform516. For example, wireless device500can receive signals that are reflected from objects or people that are within range of Tx waveform516, such as Rx waveform518reflected from target502. Wireless device500can also receive leakage signals (e.g., Tx leakage signal520) that are coupled directly from Tx antenna512to Rx antenna514without reflecting from any objects. For example, leakage signals can include signals that are transferred from a transmitter antenna (e.g., Tx antenna512) on a wireless device to a receive antenna (e.g., Rx antenna514) on the wireless device without reflecting from any objects. In some cases, Rx waveform518can include multiple sequences that correspond to multiple copies of a sequence that are included in Tx waveform516. In some examples, wireless device500can combine the multiple sequences that are received by RF receiver510to improve the signal to noise ratio (SNR).

Wireless device500can further implement RF sensing techniques by obtaining RF sensing data associated with each of the received signals corresponding to Tx waveform516. In some examples, the RF sensing data can include channel state information (CSI) data relating to the direct paths (e.g., leakage signal520) of Tx waveform516together with data relating to the reflected paths (e.g., Rx waveform518) that correspond to Tx waveform516.

In some aspects, RF sensing data (e.g., CSI data) can include information that can be used to determine the manner in which an RF signal (e.g., Tx waveform516) propagates from RF transmitter506to RF receiver510. RF sensing data can include data that corresponds to the effects on the transmitted RF signal due to scattering, fading, and/or power decay with distance, or any combination thereof. In some examples, RF sensing data can include imaginary data and real data (e.g., I/Q components) corresponding to each tone in the frequency domain over a particular bandwidth.

In some examples, RF sensing data can be used by the processor(s)522to calculate distances and angles of arrival that correspond to reflected waveforms, such as Rx waveform518. In further examples, RF sensing data can also be used to detect motion, determine location, detect changes in location or motion patterns, or any combination thereof. In some cases, the distance and angle of arrival of the reflected signals can be used to identify the size, position, movement, and/or orientation of targets (e.g., target502) in the surrounding environment in order to detect target presence/proximity.

The processor(s)522of the wireless device500can calculate distances and angles of arrival corresponding to reflected waveforms (e.g., the distance and angle of arrival corresponding to Rx waveform518) by utilizing signal processing, machine learning algorithms, any other suitable technique, or any combination thereof. In other examples, wireless device500can transmit or send the RF sensing data to at least one processor of another computing device, such as a server or base station, that can perform the calculations to obtain the distance and angle of arrival corresponding to Rx waveform518or other reflected waveforms.

In one example, the distance of Rx waveform518can be calculated by measuring the difference in time from reception of the leakage signal to the reception of the reflected signals. For example, wireless device500can determine a baseline distance of zero that is based on the difference from the time the wireless device500transmits Tx waveform516to the time it receives leakage signal520(e.g., propagation delay). The processor(s)522of the wireless device500can then determine a distance associated with Rx waveform518based on the difference from the time the wireless device500transmits Tx waveform516to the time it receives Rx waveform518(e.g., time of flight, which is also referred to as round trip time (RTT)), which can then be adjusted according to the propagation delay associated with leakage signal520. In doing so, the processor(s)522of the wireless device500can determine the distance traveled by Rx waveform518which can be used to determine the presence and movement of a target (e.g., target502) that caused the reflection.

In further examples, the angle of arrival of Rx waveform518can be calculated by the processor(s)522by measuring the time difference of arrival of Rx waveform518between individual elements of a receive antenna array, such as antenna514. In some examples, the time difference of arrival can be calculated by measuring the difference in received phase at each element in the receive antenna array.

In some cases, the distance and the angle of arrival of Rx waveform518can be used by processor(s)522to determine the distance between wireless device500and target502as well as the position of the target502relative to the wireless device500. The distance and the angle of arrival of Rx waveform518can also be used to determine presence, movement, proximity, identity, or any combination thereof, of target502. For example, the processor(s)522of the wireless device500can utilize the calculated distance and angle of arrival corresponding to Rx waveform518to determine that the target502is moving towards wireless device500.

As noted above, wireless device500can include mobile devices (e.g., IoT devices, smartphones, laptops, tablets, etc.) or other types of devices. In some examples, wireless device500can be configured to obtain device location data and device orientation data together with the RF sensing data. In some instances, device location data and device orientation data can be used to determine or adjust the distance and angle of arrival of a reflected signal such as Rx waveform518. For example, wireless device500may be set on the ground facing the sky as a target502(e.g., a vehicle) moves towards it during the RF sensing process. In this instance, wireless device500can use its location data and orientation data together with the RF sensing data to determine the direction that the target502is moving.

In some examples, device position data can be gathered by wireless device500using techniques that include RTT measurements, time of arrival (TOA) measurements, time difference of arrival (TDOA) measurements, passive positioning measurements, angle of arrival (AOA) measurements, angle of departure (AoD) measurements, received signal strength indicator (RSSI) measurements, CSI data, using any other suitable technique, or any combination thereof. In further examples, device orientation data can be obtained from electronic sensors on the wireless device500, such as a gyroscope, an accelerometer, a compass, a magnetometer, a barometer, any other suitable sensor, or any combination thereof.

FIG.6is a diagram illustrating an example of a receiver604utilizing RF bistatic sensing techniques with one transmitter600, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, to determine one or more characteristics (e.g., location, speed or velocity, heading, etc.) of a target602object, in accordance with some aspects of the present disclosure. For example, the receiver604can use the RF bistatic sensing to detect a presence and location of a target602(e.g., an object, user, or vehicle), which is illustrated in the form of a vehicle inFIG.6. In one example, the receiver604may be in the form of a base station, such as a gNB.

The bistatic radar system ofFIG.6includes a transmitter600(e.g., a transmit sensing node), which in this figure is depicted to be in the form of a base station (e.g., gNB), and a receiver604(e.g., a receive sensing node) that are separated by a distance comparable to the expected target distance. As compared to the monostatic system ofFIG.5, the transmitter600and the receiver604of the bistatic radar system ofFIG.6are located remote from one another. Conversely, monostatic radar is a radar system (e.g., the system ofFIG.5) comprising a transmitter (e.g., the RF transmitter506of wireless device500ofFIG.5) and a receiver (e.g., the RF receiver510of wireless device500ofFIG.5) that are co-located with one another.

An advantage of bistatic radar (or more generally, multistatic radar, which has more than one receiver) over monostatic radar is the ability to collect radar returns reflected from a scene at angles different than that of a transmitted pulse. This can be of interest to some applications (e.g., vehicle applications, scenes with multiple objects, military applications, etc.) where targets may reflect the transmitted energy in many directions (e.g., where targets are specifically designed to reflect in many directions), which can minimize the energy that is reflected back to the transmitter. It should be noted that, in one or more examples, a monostatic system can coexist with a multistatic radar system, such as when the transmitter also has a co-located receiver.

In some examples, the transmitter600and/or the receiver604ofFIG.6can be a mobile phone, a tablet computer, a wearable device, a vehicle, or other device (e.g., device407ofFIG.4) that includes at least one RF interface. In some examples, the transmitter600and/or the receiver604can be a device that provides connectivity for a user device (e.g., for IoT device407ofFIG.4), such as a base station (e.g., a gNB, eNB, etc.), a wireless access point (AP), or other device that includes at least one RF interface.

In some aspects, transmitter600can include one or more components for transmitting an RF signal. The transmitter600can include at least one processor (e.g., the at least one processor522ofFIG.5) that is capable of determining signals (e.g., determining the waveforms for the signals) to be transmitted. The transmitter600can also include an RF transmitter (e.g., the RF transmitter506ofFIG.5) for transmission of a Tx signal comprising Tx waveform616. The RF transmitter can be a transmitter configured to transmit cellular or telecommunication signals (e.g., a transmitter configured to transmit 5G/NR signals, 4G/LTE signals, or other cellular/telecommunication signals, etc.), a Wi-Fi transmitter, a Bluetooth™ transmitter, any combination thereof, or any other transmitter capable of transmitting an RF signal.

The RF transmitter can be coupled to one or more transmitting antennas, such as a Tx antenna (e.g., the TX antenna512ofFIG.5). In some examples, a Tx antenna can be an omnidirectional antenna that is capable of transmitting an RF signal in all directions, or a directional antenna that transmits an RF signal in a particular direction. In some examples, the Tx antenna may include multiple antennas (e.g., elements) configured as an antenna array.

The receiver604can include one or more components for receiving an RF signal. For example, the receiver604may include one or more receiving antennas, such as an Rx antenna (e.g., the Rx antenna514ofFIG.5). In some examples, an Rx antenna can be an omnidirectional antenna capable of receiving RF signals from multiple directions, or a directional antenna that is configured to receive signals from a particular direction. In further examples, the Rx antenna can include multiple antennas (e.g., elements) configured as an antenna array.

The receiver604may also include an RF receiver (e.g., RF receiver510ofFIG.5) coupled to the Rx antenna. The RF receiver may include one or more hardware components for receiving an RF waveform such as a Wi-Fi signal, a Bluetooth™ signal, a 5G/NR signal, or any other RF signal. The output of the RF receiver can be coupled to at least one processor (e.g., the at least one processor522ofFIG.5). The processor(s) may be configured to process a received waveform (e.g., Rx waveform618).

In one or more examples, transmitter600can implement RF sensing techniques, for example bistatic sensing techniques, by causing a Tx waveform616to be transmitted from a Tx antenna. It should be noted that although the Tx waveform616is illustrated as a single line, in some cases, the Tx waveform616can be transmitted in all directions by an omnidirectional Tx antenna.

In one or more aspects, one or more parameters associated with the Tx waveform616may be used to increase or decrease RF sensing resolution. The parameters may include frequency, bandwidth, number of spatial streams, the number of antennas configured to transmit Tx waveform616, the number of antennas configured to receive a reflected RF signal (e.g., Rx waveform618) corresponding to the Tx waveform616, the number of spatial links (e.g., number of spatial streams multiplied by number of antennas configured to receive an RF signal), the sampling rate, or any combination thereof. The transmitted waveform (e.g., Tx waveform616) and the received waveform (e.g., the Rx waveform618) can include one or more radar RF sensing signals (also referred to as RF sensing RSs).

During operation, the receiver604(e.g., which operates as a receive sensing node) can receive signals that correspond to Tx waveform616, which is transmitted by the transmitter600(e.g., which operates as a transmit sensing node). For example, the receiver604can receive signals that are reflected from objects or people that are within range of the Tx waveform616, such as Rx waveform618reflected from target602. In some cases, the Rx waveform618can include multiple sequences that correspond to multiple copies of a sequence that are included in the Tx waveform616. In some examples, the receiver604may combine the multiple sequences that are received to improve the SNR.

In some examples, RF sensing data can be used by at least one processor within the receiver604to calculate distances, angles of arrival, or other characteristics that correspond to reflected waveforms, such as the Rx waveform618. In other examples, RF sensing data can also be used to detect motion, determine location, detect changes in location or motion patterns, or any combination thereof. In some cases, the distance and angle of arrival of the reflected signals can be used to identify the size, position, movement, and/or orientation of targets (e.g., target602) in the surrounding environment in order to detect target presence/proximity.

The processor(s) of the receiver604can calculate distances and angles of arrival corresponding to reflected waveforms (e.g., the distance and angle of arrival corresponding to the Rx waveform618) by using signal processing, machine learning algorithms, any other suitable technique, or any combination thereof. In other examples, the receiver604can transmit or send the RF sensing data to at least one processor of another computing device, such as a server, that can perform the calculations to obtain the distance and angle of arrival corresponding to the Rx waveform618or other reflected waveforms.

In one or more examples, the angle of arrival of the Rx waveform618can be calculated by a processor(s) of the receiver604by measuring the time difference of arrival of the Rx waveform618between individual elements of a receive antenna array of the receiver604. In some examples, the time difference of arrival can be calculated by measuring the difference in received phase at each element in the receive antenna array.

In some cases, the distance and the angle of arrival of the Rx waveform618can be used by the processor(s) of the receiver604to determine the distance between the receiver604and the target602as well as the position of target602relative to the receiver604. The distance and the angle of arrival of the Rx waveform618can also be used to determine presence, movement, proximity, identity, or any combination thereof, of the target602. For example, the processor(s) of the receiver604may use the calculated distance and angle of arrival corresponding to the Rx waveform618to determine that the target602is moving towards the receiver604.

FIG.7is a diagram illustrating an example of a receiver704, in the form of a smart phone, utilizing RF bistatic sensing techniques with multiple transmitters (including a transmitter700a, a transmitter700b, and a transmitter700c), which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, to determine one or more characteristics (e.g., location, velocity or speed, heading, etc.) of a target702object, in accordance with some aspects of the present disclosure. For example, the receiver704may use RF bistatic sensing to detect a presence and location of a target702(e.g., an object, user, or vehicle). The target702is depicted inFIG.7in the form of an object that does not have communications capabilities (which can be referred to as a device-free object), such as a person, a vehicle (e.g., a vehicle without the ability to transmit and receive messages, such as using C-V2X or DSRC protocols), or other device-free object. The bistatic radar system ofFIG.7is similar to the bistatic radar system ofFIG.6, except that the bistatic radar system ofFIG.7has multiple transmitters700a,700b,700c, while the bistatic radar system ofFIG.6has only one transmitter600.

The bistatic radar system ofFIG.7includes multiple transmitters700a,700b,700c(e.g., transmit sensing nodes), which are illustrated to be in the form of base stations. The bistatic radar system ofFIG.7also includes a receiver704(e.g., a receive sensing node), which is depicted in the form of a smart phone. The each of the transmitters700a,700b,700cis separated from the receiver704by a distance comparable to the expected distance from the target702. Similar to the bistatic system ofFIG.6, the transmitters700a,700b,700cand the receiver704of the bistatic radar system ofFIG.7are located remote from one another.

In one or more examples, the transmitters700a,700b,700cand/or the receiver704may each be a mobile phone, a tablet computer, a wearable device, a vehicle (e.g., a vehicle configured to transmit and receive communications according to C-V2X, DSRC, or other communication protocol), or other device (e.g., device407ofFIG.4) that includes at least one RF interface. In some examples, the transmitters700a,700b,700cand/or the receiver704may each be a device that provides connectivity for a user device (e.g., for IoT device407ofFIG.4), such as a base station (e.g., a gNB, eNB, etc.), a wireless access point (AP), or other device that includes at least one RF interface.

The transmitters700a,700b,700cmay include one or more components for transmitting an RF signal. Each of the transmitters700a,700b,700cmay include at least one processor (e.g., the processor(s)522ofFIG.5) that is capable of determining signals (e.g., determining the waveforms for the signals) to be transmitted. Each of the transmitters700a,700b,700ccan also include an RF transmitter (e.g., the RF transmitter506ofFIG.5) for transmission of Tx signals comprising Tx waveforms716a,716b,716c,720a,720b,720c. In one or more examples, Tx waveforms716a,716b,716care RF sensing signals, and Tx waveforms720a,720b,720care communications signals. In one or more examples, the Tx waveforms720a,720b,720care communications signals that may be used for scheduling transmitters (e.g., transmitters700a,700b,700c) and receivers (e.g., receiver704) for performing RF sensing of a target (e.g., target702) to obtain location information regarding the target. The RF transmitter can be a transmitter configured to transmit cellular or telecommunication signals (e.g., a transmitter configured to transmit 5G/NR signals, 4G/LTE signals, or other cellular/telecommunication signals, etc.), a Wi-Fi transmitter, a Bluetooth™ transmitter, any combination thereof, or any other transmitter capable of transmitting an RF signal.

The RF transmitter may be coupled to one or more transmitting antennas, such as a Tx antenna (e.g., the TX antenna512ofFIG.5). In one or more examples, a Tx antenna can be an omnidirectional antenna that is capable of transmitting an RF signal in all directions, or a directional antenna that transmits an RF signal in a particular direction. The Tx antenna may include multiple antennas (e.g., elements) configured as an antenna array.

The receiver704ofFIG.7may include one or more components for receiving an RF signal. For example, the receiver704can include one or more receiving antennas, such as an Rx antenna (e.g., the Rx antenna514ofFIG.5). In one or more examples, an Rx antenna can be an omnidirectional antenna capable of receiving RF signals from multiple directions, or a directional antenna that is configured to receive signals from a particular direction. In some examples, the Rx antenna may include multiple antennas (e.g., elements) configured as an antenna array (e.g., a phase antenna array), which may be used for MIMO communications and/or sensing.

The receiver704can also include an RF receiver (e.g., RF receiver510ofFIG.5) coupled to the Rx antenna. The RF receiver may include one or more hardware components for receiving an RF waveform such as a Wi-Fi signal, a Bluetooth™ signal, a 5G/NR signal, or any other RF signal. The output of the RF receiver can be coupled to at least one processor (e.g., the processor(s)522ofFIG.5). The processor(s) may be configured to process a received waveform (e.g., Rx waveform718, which is a reflection (echo) RF sensing signal).

In some examples, the transmitters700a,700b,700ccan implement RF sensing techniques, for example bistatic sensing techniques, by causing Tx waveforms716a,716b,716c(e.g., radar sensing signals) to be transmitted from a Tx antenna associated with each of the transmitters700a,700b,700c. Although the Tx waveforms716a,716b,716care illustrated as single lines, in some cases, the Tx waveforms716a,716b,716cmay be transmitted in all directions (e.g., by an omnidirectional Tx antenna associated with each of the transmitters700a,700b,700c).

In one or more aspects, one or more parameters associated with the Tx waveforms716a,716b,716cmay be used to increase or decrease RF sensing resolution. The parameters can include, but are not limited to, frequency, bandwidth, number of spatial streams, the number of antennas configured to transmit Tx waveforms716a,716b,716c, the number of antennas configured to receive a reflected (echo) RF signal (e.g., Rx waveform718) corresponding to each of the Tx waveforms716a,716b,716c, the number of spatial links (e.g., number of spatial streams multiplied by number of antennas configured to receive an RF signal), the sampling rate, or any combination thereof. The transmitted waveforms (e.g., Tx waveforms716a,716b,716c) and the received waveforms (e.g., the Rx waveform718) may include one or more radar RF sensing signals (also referred to as RF sensing RSs). It should be noted that although only one reflected sensing signal (e.g., Rx waveform718) is shown inFIG.7, it is understood that a separate reflection (echo) sensing signal will be generated by each sensing signal (e.g., Tx waveforms716a,716b,716c) reflecting off of the target702.

During operation of the system ofFIG.7, the receiver704(e.g., which operates as a receive sensing node) can receive signals that correspond to Tx waveforms716a,716b,716c, which are transmitted by the transmitters700a,700b,700c(e.g., which each operate as a transmit sensing node). The receiver704can receive signals that are reflected from objects or people that are within range of the Tx waveforms716a,716b,716c, such as Rx waveform718reflected from the target702. In one or more examples, the Rx waveform718may include multiple sequences that correspond to multiple copies of a sequence that are included in its corresponding Tx waveform716a,716b,716c. In some examples, the receiver704may combine the multiple sequences that are received to improve the SNR.

In some examples, RF sensing data can be used by at least one processor within the receiver704to calculate distances, angles of arrival (AOA), TDOA, angle of departure (AoD), or other characteristics that correspond to reflected waveforms (e.g., Rx waveform718). In further examples, RF sensing data can also be used to detect motion, determine location, detect changes in location or motion patterns, or any combination thereof. In one or more examples, the distance and angle of arrival of the reflected signals can be used to identify the size, position, movement, and/or orientation of targets (e.g., target702) in order to detect target presence/proximity.

The processor(s) of the receiver704can calculate distances and angles of arrival corresponding to reflected waveforms (e.g., the distance and angle of arrival corresponding to the Rx waveform718) by using signal processing, machine learning algorithms, any other suitable technique, or any combination thereof. In one or more examples, the receiver704can transmit or send the RF sensing data to at least one processor of another computing device, such as a server, that can perform the calculations to obtain the distance and angle of arrival corresponding to the Rx waveform718or other reflected waveforms (not shown).

In one or more examples, a processor(s) of the receiver704can calculate the angle of arrival (AOA) of the Rx waveform718by measuring the TDOA of the Rx waveform718between individual elements of a receive antenna array of the receiver704. In some examples, the TDOA can be calculated by measuring the difference in received phase at each element in the receive antenna array. In one illustrative example, to determine TDOA, the processor(s) can determine the difference time of arrival of the Rx waveform718to the receive antenna array elements, using one of them as a reference. The time difference is proportional to distance differences.

In some cases, the processor(s) of the receiver704can use the distance, the AOA, the TDOA, other measured information (e.g., AoD, etc.), any combination thereof, of the Rx waveform718to determine the distance between the receiver704and the target702, and determine the position of target702relative to the receiver704. In one example, the processor(s) can apply a multilateration or other location-based algorithm using the distance, AOA, and/or TDOA information as input to determine a position (e.g., 3D position) of the target702. In other examples, the processor(s) can use the distance, the AOA, and/or the TDOA of the Rx waveform718to determine a presence, movement (e.g., velocity or speed, heading or direction or movement, etc.), proximity, identity, any combination thereof, or other characteristic of the target702. For instance, the processor(s) of the receiver704may use the distance, the AOA, and/or the TDOA corresponding to the Rx waveform718to determine that the target is moving towards the receiver704.

FIG.8is a diagram illustrating geometry for bistatic (or monostatic) sensing, in accordance with some aspects of the present disclosure.FIG.8shows a bistatic radar North-reference coordinate system in two-dimensions. In particular,FIG.8shows a coordinate system and parameters defining bistatic radar operation in a plane (referred to as a bistatic plane) containing a transmitter800, a receiver804, and a target802. A bistatic triangle lies in the bistatic plane. The transmitter800, the target802, and the receiver804are shown in relation to one another. The transmitter800and the receiver804are separated by a baseline distance L. The extended baseline is defined as continuing the baseline distance L beyond either the transmitter800or the receiver804. The target802and the transmitter800are separated by a distance RT, and the target802and the receiver804are separated by a distance RR.

Angles θTand θRare, respectively, the transmitter800and receiver804look angles, which are taken as positive when measured clockwise from North (N). The angles θTand θRare also referred to as angles of arrival (AOA) or lines of sight (LOS). A bistatic angle (β) is the angle subtended between the transmitter800, the target802, and the receiver804in the radar. In particular, the bistatic angle is the angle between the transmitter800and the receiver804with the vertex located at the target802. The bistatic angle is equal to the transmitter800look angle minus the receiver804look angle θR(e.g., β=θT−θR).

When the bistatic angle is exactly zero (0), the radar is considered to be a monostatic radar; when the bistatic angle is close to zero, the radar is considered to be pseudo-monostatic; and when the bistatic angle is close to 180 degrees, the radar is considered to be a forward scatter radar. Otherwise, the radar is simply considered to be, and referred to as, a bistatic radar. The bistatic angle (β) can be used in determining the radar cross section of the target.

FIG.9is a diagram illustrating an example of a bistatic range910of bistatic sensing, in accordance with some aspects of the present disclosure. In this figure, a transmitter (Tx)900, a target902, and a receiver (Rx)904of a radar are shown in relation to one another. The transmitter900and the receiver904are separated by a baseline distance L, the target902and the transmitter900are separated by a distance Rtx, and the target902and the receiver904are separated by a distance Rrx.

Bistatic range910(shown as an ellipse) refers to the measurement range made by radar with a separate transmitter900and receiver904(e.g., the transmitter900and the receiver904are located remote from one another). The receiver904measures the time of arrival from when the signal is transmitted by the transmitter900to when the signal is received by the receiver904from the transmitter900via the target902. The bistatic range910defines an ellipse of constant bistatic range, referred to an iso-range contour, on which the target902lies, with foci centered on the transmitter900and the receiver904. If the target902is at range Rrx from the receiver904and range Rtx from the transmitter900, and the receiver904and the transmitter900are located a distance L apart from one another, then the bistatic range is equal to Rrx+Rtx−L. It should be noted that motion of the target902causes a rate of change of bistatic range, which results in bistatic Doppler shift.

Generally, constant bistatic range points draw an ellipsoid, with the transmitter900and the receiver904positions as the focal points. The bistatic iso-range contours are where the ground slices the ellipsoid. When the ground is flat, this intercept forms an ellipse (e.g., bistatic range910). Note that except when the two platforms have equal altitude, these ellipses are not centered on a specular point.

FIG.10is a diagram illustrating an example of a system1000for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. The system1000may employ multistatic sensing for cooperative sensing of UEs1006a,1006b,1006c. InFIG.10, the system1000is shown to include a plurality of network devices and network entities. The plurality of network devices includes UEs1006a,1006b,1006c, which may be in various different types of forms including, but not limited to, mobile devices or phones (e.g., UE1006b), extended reality (XR) devices such as augmented reality (AR) or virtual reality (VR) headsets (e.g., UE1006a), network-connected or smart watches, vehicles (e.g., UE1006c), and/or other types of network devices. The network entities may be in the form of a radar server1010. The network entities can be in the form of base stations1002a,1002b,1002c,1004(e.g., a gNB or eNB), or a portion of a base station having a disaggregated architecture (e.g., one or more of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC of the base station). In one or more examples, the network entities (e.g., the base stations1002a,1002b,1002c,1004, and radar server1010) may be co-located together, or may be located remote from one another.

The system1000may include more or less network devices and/or more or less network entities, than as shown inFIG.10. In addition, the system1000may include more or less different types of network devices and/or network entities (e.g., network servers), than as shown inFIG.10. In addition, in one or more examples, the network devices (e.g., UEs1006a,1006b,1006c) may be equipped with heterogeneous capability, which may include, but is not limited to, C-V2X/DSRC capability, 4G/5G cellular connectivity, GPS capability, camera capability, or other sensor-based capability (e.g., light or sound-based sensors such as a depth sensor using any suitable technology for determining depth).

The network devices (e.g., UEs1006a,1006b,1006c) and network entities (e.g., base stations1002a,1002b,1002c,1004, and radar server1010) may be capable of performing communications (e.g., 5G NR communications) with each other. In such cases, the UEs1006a,1006b,1006cmay transmit signals (e.g., communications signals) to each other. The UEs1006a,1006b,1006cand the base stations1002a,1002b,1002c,1004may transmit signals (e.g., communications signals) to each other. When the radar server1010is located remote from the base stations1002a,1002b,1002c,1004, the radar server1010and the base stations1002a,1002b,1002c,1004may transmit signals (e.g., communication signals) to each other.

In one or more examples, the network devices and/or network entities (e.g., base stations1002a,1002b,1002c,1004) may be capable of transmitting and receiving sensing signals of some kind (e.g., camera, RF sensing signals, optical sensing signals, etc.). In some cases, at least some of the network devices and/or network entities (e.g., base stations1002a,1002b,1002c,1004) may transmit and/or receive sensing signals (e.g., RF sensing signals, such as radar target signals1014a,1014b, shown as beams transmitted from the network entities) to detect nearby UEs (e.g., UEs1006a,1006b,1006c) and/or objects using one or more RF sensing techniques (e.g., monostatic, bistatic, and/or multistatic sensing for cooperative sensing), as previously described. In some cases, the network devices and/or network entities can detect nearby UEs and/or objects based on one or more images or frames captured using one or more cameras.

The base station1004, which may operate as a radar transmitter, and the base stations1002a,1002b,1002c, which may operate as radar receivers, may perform RF sensing (e.g., bistatic and/or multistatic sensing for cooperative sensing) of the targets (e.g., UEs1006a,1006b,1006c) to obtain RF sensing measurements (e.g., RTT, TOA, and/or TDOA measurements) of the targets (e.g., UEs1006a,1006b,1006c). In one or more examples, the system1000may utilize more than one radar receiver (e.g., base stations1002a,1002b,1002c), more than one radar transmitter (e.g., base station1004), more than one network entity (e.g., radar server1010), and/or more than one target (e.g., UEs1006a,1006b,1006c) for performing bistatic or multistatic sensing. In some examples, at least one radar transmitter (e.g., base station1004) may be co-located with a radar receiver (e.g., base stations1002a,1002b,1002c) for performing monostatic sensing. The use of bistatic/multistatic sensing, which includes the radar transmitter and radar receiver(s) located remotely from one another, avoids self-interference that may occur in monostatic sensing. The cooperative sensing scheme shown in the system1000ofFIG.10allows for wide-area bistatic/multistatic sensing that may be employed in cellular networks, and allows for a means to manage the interference in the sensing and the joint communications and sensing (JCS).

The RF sensing measurements of the targets (e.g., UEs1006a,1006b,1006c) can be used (e.g., by at least one processor(s) of the radar server1010) to determine one or more characteristics (e.g., location, distance, movement, heading, size, and/or other characteristics) of the targets (e.g., UEs1006a,1006b,1006c). The characteristics of the targets (e.g., UEs1006a,1006b,1006c) can be indicative of the sensing environment of the radar receivers (e.g., base stations1002a,1002b,1002c), and can be used (e.g., by at least one processor(s) of the radar server1010) to determine the sensing measurement accuracy of the radar receivers (e.g., base stations1002a,1002b,1002c). In one or more examples, additional measurements (e.g., light detection and ranging (LIDAR) measurements, ultrasound measurements, and/or positioning measurements), which may be obtained from radar reference signals1012a,1012b,1012c(shown as beams), may also be used to determine the sensing measurement accuracy of the radar receivers (e.g., base stations1002a,1002b,1002c).

In some cases, the system of1000FIG.10may perform radar-based sensing. For example, the radar receivers (e.g., base stations1002a,1002b,1002c) may determine the characteristics of the targets (e.g., UEs1006a,1006b,1006c), and may determine the sensing measurement accuracy of the radar receivers (e.g., base stations1002a,1002b,1002c). Additionally or alternatively, in some cases, the system1000may perform network-based sensing. For instance, the network entity (e.g., radar server1010) may determine the characteristics of the targets (e.g., UEs1006a,1006b,1006c), and may determine the sensing measurement accuracy for the radar receivers (e.g., base stations1002a,1002b,1002c).

In one or more examples, the system1000may perform MIMO operations, such as multiple user-MIMO (MU-MIMO) operations. In MU-MIMO, multiple users (e.g., base stations1002a,1002b,1002c) share the same time and frequency resources, while the transmitter (e.g., base station1004) is equipped with multiple antennas (e.g., at least one antenna array, which includes a plurality of antenna elements, such as physical antenna ports1404ofFIG.14, described below) and serves many receivers (e.g., base stations1002a,1002b,1002c) simultaneously. Each receiver (e.g., base stations1002a,1002b,1002c) need only employ a single antenna and, as such, complex hardware is only required at the transmitter side (e.g., base station1004). In some examples, the system1000may perform Massive MIMO (mMIMO) operations. mMIMO is a form of MU-MIMO that employs a larger number of antennas on the transmitter side (e.g., base station1004) than MU-MIMO and, as such, the number of users (e.g., base stations1002a,1002b,1002c) served can be increased significantly as compared to MU-MIMO. In one or more examples, when the system1000performs MIMO operations (e.g., MU-MIMO operations), the network device and/or network entity (e.g., base station1004) operating as the transmitter may include at least one antenna array (e.g., a direct radiating antenna array and/or a phase antenna array), which can include a plurality of antenna elements (e.g., antenna horns, patch antenna elements, cupped-dipole antenna elements, and/or dipole antenna elements). Each of the antenna elements and/or groupings of the antenna elements can be used to form a plurality of antenna signals1012a,1012b,1012c,1014a,1014b(shown as beams) to be transmitted from the transmitter (e.g., base station1004). In one or more examples, the network entity (e.g., radar server1010) can manage and/or initiate beam coordination of the antenna signals1012a,1012b,1012c,1014a,1014bfor cooperative sensing.

During operation of the system1000for MU-MIMO (e.g., mMIMO) radar-based sensing, for example when performing bistatic/multistatic sensing of targets (e.g., UEs1006a,1006c), a radar transmitter (e.g., base station1004) may transmit RF sensing signals (e.g., radar target signals1014a,1014b) towards the targets (e.g., UEs1006a,1006c). The sensing signals (e.g., radar target signals1014a,1014b) can reflect off of the targets (e.g., UEs1006a,1006c) to produce RF reflection sensing signals1016a,1016b,1016c,1016d,1016e. Radar receivers (e.g., base stations1002a,1002b,1002c, and UE1006b) can receive the reflection sensing signals. At least one processor (e.g., processor522ofFIG.5) of each of the radar receivers (e.g., base stations1002a,1002b,1002c, and UE1006b) may then determine or compute the characteristics (e.g., location, distance, movement, heading, size, etc.) of the targets (e.g., UEs1006a,1006c) by using sensing measurements from the received reflection sensing signals. As previously noted, the characteristics of the targets (e.g., UEs1006a,1006c) may be indicative of the sensing environment related to the radar receivers (e.g., base stations1002a,1002b,1002c, and UE1006b).

In some cases, during operation, the radar transmitter (e.g., base station1004) may transmit RF radar reference signals1012a,1012b,1012ctowards the radar receivers (e.g., base stations1002a,1002b,1002c). The radar receivers (e.g., base stations1002a,1002b,1002c) can receive the radar reference signals1012a,1012b,1012c. At least one processor (e.g., processor522ofFIG.5) of each of the radar receivers (e.g., base stations1002a,1002b,1002c) may then determine (compute) performance metrics (e.g., operating range, maximum range, and/or range/Doppler accuracy) for the radar receivers (e.g., base stations1002a,1002b,1002c) by using sensing measurements from the received radar reference signals1012a,1012b,1012cas well as, optionally, using information regarding the sensing environment related to the radar receivers (e.g., base stations1002a,1002b,1002c).

In one or more examples, the radar reference signals1012a,1012b,1012cmay be employed for monostatic sensing. For these examples for monostatic sensing, the radar reference signals1012a,1012b,1012cwill reflect off of the radar receivers (e.g., base stations1002a,1002b,1002c) and produce reflection radar reference signals, which will propagate back towards the radar transmitter (e.g., base station1004). The radar transmitter (e.g., base station1004) can then determine (compute) performance metrics (e.g., operating range, maximum range, and/or range/Doppler accuracy) for the radar receivers (e.g., base stations1002a,1002b,1002c) by using sensing measurements from the reflection radar reference signals as well as, optionally, using information regarding the sensing environment related to the radar receivers (e.g., base stations1002a,1002b,1002c).

In some examples, the radar receivers (e.g., base stations1002a,1002b,1002cand UE1006b) may transmit the determined characteristics (e.g., location, distance, movement, heading, size, etc.) of the targets (e.g., UEs1006a,1006c) and/or the computed performance metrics (e.g., operating range, maximum range, and/or range/Doppler accuracy) for the radar receivers (e.g., base stations1002a,1002b,1002c) to a network entity (e.g., radar server1010).

In some examples, the network entity (e.g., radar server1010) can determine the characteristics (e.g., location, distance, movement, heading, size, etc.) of the targets (e.g., UEs1006a,1006c) and/or the performance metrics (e.g., operating range, maximum range, and/or range/Doppler accuracy) for the radar receivers (e.g., base stations1002a,1002b,1002c). For example, during operation of the system for MU-MIMO (e.g., mMIMO) network-based RF sensing, for example when performing bistatic/multistatic sensing of the targets (e.g., UEs1006a,1006c), a radar transmitter (e.g., base station1004) can transmit RF sensing signals (e.g., radar target signals1014a,1014b) towards the targets (e.g., UEs1006a,1006c). The sensing signals (e.g., radar target signals1014a,1014b) may reflect off of the targets (e.g., UEs1006a,1006c) to produce RF reflection sensing signals1016a,1016b,1016c,1016d,1016e. Radar receivers (e.g., base stations1002a,1002b,1002c, and UE1006b) can receive the reflection sensing signals. The radar receivers (e.g., base stations1002a,1002b,1002c, and UE1006b) may then generate sensing measurements from the received reflected sensing signals.

In some examples, during operation, the radar transmitter (e.g., base station1004) can transmit RF radar reference signals1012a,1012b,1012ctowards the radar receivers (e.g., base stations1002a,1002b,1002c). The radar receivers (e.g., base stations1002a,1002b,1002c) may receive the radar reference signals1012a,1012b,1012c. The radar receivers (e.g., base stations1002a,1002b,1002c) may then generate sensing measurements from the received radar reference signals1012a,1012b,1012c.

In one or more examples, the radar reference signals1012a,1012b,1012cmay be employed for monostatic sensing. For these examples for monostatic sensing, the radar reference signals1012a,1012b,1012cwill reflect off of the radar receivers (e.g., base stations1002a,1002b,1002c) and produce reflection radar reference signals, which will propagate back towards the radar transmitter (e.g., base station1004). The radar transmitter (e.g., base station1004) can then generate sensing measurements from the reflection radar reference signals.

In some examples, the radar receivers (e.g., base stations1002a,1002b,1002c, and UE1006b) and/or the radar transmitter (e.g., base station1004) may transmit the sensing measurements from the received reflected sensing signals and/or the sensing measurements from the received radar reference signals1012a,1012b,1012c(and/or the reflection radar reference signals) to the network entity (e.g., radar server1010). At least one processor (e.g., processor522ofFIG.5) of the network entity (e.g., radar server1010) may determine or compute the characteristics (e.g., location, distance, movement, heading, size, etc.) of the targets (e.g., UEs1006a,1006c) by using the sensing measurements from the received reflection sensing signals. The characteristics of the targets (e.g., UEs1006a,1006c) can be indicative of the sensing environment related to the radar receivers (e.g., base stations1002a,1002b,1002c, and UE1006b).

At least one processor (e.g., processor522ofFIG.5) of the network entity (e.g., radar server1010) may then determine (compute) performance metrics (e.g., operating range, maximum range, and/or range/Doppler accuracy) for the radar receivers (e.g., base stations1002a,1002b,1002c) by using the sensing measurements from the received radar reference signals1012a,1012b,1012c(and/or the reflection radar reference signals) as well as, optionally, using information regarding the sensing environment related to the radar receivers (e.g., base stations1002a,1002b,1002c).

FIG.11is a diagram illustrating an example of a system1100for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. The system1100may perform MIMO (e.g., MU-MIMO, mMIMO, etc.) downlink communications and monostatic MIMO sensing of a UE (e.g., UE1108a). InFIG.11, the system1100is shown to include a plurality of network devices and a network entity. The plurality of network devices includes UEs1108a,1108b,1106a,1106b,1106k, which may be in various different types of forms including, but not limited to, mobile devices or phones (e.g., UEs1106a,1106b,1106k), extended reality (XR) devices such as augmented reality (AR) or virtual reality (VR) headsets, network-connected or smart watches, vehicles (e.g., UEs1108a,1108b), and/or other types of devices. The network entity can be in the form of a base station1102(e.g., a gNB or eNB), or a portion of a base station having a disaggregated architecture (e.g., one or more of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC of the base station).

The system1100may include more or less network devices and/or more or less network entities, than as shown inFIG.11. In addition, the system1100may include more or less different types of network devices and/or network entities (e.g., network servers), than as shown inFIG.11. In addition, in one or more examples, the network devices (e.g., UEs1108a,1108b,1106a,1106b,1106k) may be equipped with heterogeneous capability, which may include, but is not limited to, C-V2X/DSRC capability, 4G/5G cellular connectivity, GPS capability, camera capability, or other sensor-based capability (e.g., light or sound-based sensors such as a depth sensor using any suitable technology for determining depth).

The network devices (e.g., UEs1108a,1108b,1106a,1106b,1106k) and network entity (e.g., base station1102) may be capable of performing communications (e.g., 5G NR communications) with each other. In such cases, for example, the network entity (e.g., base station1102) may transmit communications signals (e.g., communications signals1104a,1104b,1104c) to the UEs (e.g., UEs1106a,1106b,1106k).

In one or more examples, the network devices and/or network entity (e.g., base station1102) may be capable of transmitting and receiving sensing signals of some kind (e.g., camera, RF sensing signals, optical sensing signals, etc.). In some cases, the network devices and/or network entity (e.g., base station1102) may transmit and receive sensing signals (e.g., RF sensing signals1110a) for using one or more sensors to detect nearby UEs (e.g., UE1108a) and/or objects. In some cases, the network devices and/or network entity (e.g., base station1102) can detect nearby UEs and/or objects based on one or more images or frames captured using one or more cameras.

The base station1102, which may operate as both a radar transmitter and a radar receiver, may perform RF sensing (e.g., monostatic sensing) of at least one target (e.g., UE1108a) to obtain RF sensing measurements (e.g., RTT, TOA, and/or TDOA measurements) of the target(s) (e.g., UEs1108a). The RF sensing measurements of the target(s) (e.g., UE1108a) can be used (e.g., by at least one processor(s) of the base station1102or a radar server) to determine one or more characteristics (e.g., location, distance, movement, heading, size, and/or other characteristics) of the target(s) (e.g., UE1108a). The characteristics of the target(s) (e.g., UE1108a) can be indicative of the sensing environment of the base station1102, and can be used (e.g., by at least one processor(s) of the base station1102or radar server) to determine the sensing measurement accuracy of the base station1102.

In some examples, the system of1100FIG.11may perform radar-based sensing, in which the base station1102may determine the characteristics of at least one target (e.g., UE1108a), and may determine the sensing measurement accuracy the base station1102. Additionally or alternatively, in some examples, the system1100ofFIG.11may perform network-based sensing, in which the base station1102may determine the characteristics of at least one target (e.g., UE1108a), and may determine the sensing measurement accuracy for the base station1102.

In one or more examples, the system1100may perform MU-MIMO (e.g., mMIMO) operations. In MU-MIMO, multiple users (e.g., UEs1108a,1108b,1106a,1106b,1106k) share the same time and frequency resources, while the base station1102is equipped with multiple antennas (e.g., at least one antenna array, which includes a plurality of antenna elements, such as physical antenna ports1404ofFIG.14) and serves many users (e.g., UEs1108a,1108b,1106a,1106b,1106k) simultaneously. In one or more examples, when the system1100performs MIMO operations (e.g., MU-MIMO operations), the base station1102may include at least one antenna array (e.g., a direct radiating antenna array and/or a phase antenna array), which can include a plurality of antenna elements (e.g., antenna horns, patch antenna elements, cupped-dipole antenna elements, and/or dipole antenna elements).

Each of the antenna elements and/or groupings of the antenna elements of the antenna array(s) can be used to form a plurality of antenna beams to be transmitted from the base station1102to the users (e.g., UEs1108a,1106a,1106b,1106k). Each of the antenna beams may include at least one respective signal (e.g., signals1110a,1104a,1104b,1104k), which may be a communication signal, a sensing signal, or a joint communications and sensing signal. In the system1100ofFIG.11, the antenna beams are shown to include a sensing signal1110aand a plurality of communications signals1104a,1104b,1104k. In one or more examples, a network entity (e.g., a radar server) can manage and/or initiate beam coordination of the antenna beams of the base station1102for cooperative sensing.

During operation of the system1100for MU-MIMO (e.g., mMIMO) radar-based sensing, for example when performing monostatic sensing of a target (e.g., UE1108a), a base station1102(operating as a radar transmitter) may transmit an RF sensing signal1110atowards the target (e.g., UE1108a). The sensing signal1110acan reflect off of the target (e.g., UEs1108a) to produce an RF reflection sensing signal1110b, which is reflected back towards the base station1102. The base station1102(also operating as a radar receiver) can receive the reflection sensing signal1110b. At least one processor (e.g., processor522ofFIG.5) of the base station1102may then determine or compute the characteristics (e.g., location, distance, movement, heading, size, etc.) of the target (e.g., UE1108a) by using sensing measurements from the received reflection sensing signal1110b. In some examples, the base station1102may transmit the determined characteristics (e.g., location, distance, movement, heading, size, etc.) of the target (e.g., UE1108a) to a network entity (e.g., a radar server).

In some examples, a network entity (e.g., radar server) can determine the characteristics (e.g., location, distance, movement, heading, size, etc.) of the target (e.g., UE1108a). For example, during operation of the system for MU-MIMO (e.g., mMIMO) network-based RF sensing, for example when performing monostatic sensing of the target (e.g., UE1108a), the base station1102(operating as a radar transmitter) can transmit an RF sensing signal1110atowards the target (e.g., UE1108a). The sensing signal1110amay reflect off of the target (e.g., UE1108a) to produce an RF reflection sensing signal1110b. The base station1102(operating also as a radar receiver) can receive the reflection sensing signal1110b. The base station1102may then generate sensing measurements from the received reflected sensing signal1110b.

In some examples, base station1102may transmit the sensing measurements from the received reflected sensing signal1110bto a network entity (e.g., radar server). At least one processor (e.g., processor522ofFIG.5) of the network entity (e.g., radar server) may determine or compute the characteristics (e.g., location, distance, movement, heading, size, etc.) of the target (e.g., UE1108a) by using the sensing measurements from the received reflection sensing signal1110b.

In one or more examples, the system1100ofFIG.11, which may perform monostatic MU-MIMO sensing, may employ at least one unified waveform for joint MIMO communications and MIMO sensing (e.g., a JCS waveform). In some examples, a multi-antenna JCS transceiver (e.g., a network entity, such as base station1102) may schedule and generate the waveform(s).

In one or more examples, the base station1102may have Ntnumber of transmit antenna elements (e.g., NtTx) in its antenna array(s) and Nrnumber of receive antenna elements (e.g., NrRx) in its antenna array(s). The base station1102may serve k number of users (e.g., UEs1108a,1108b,1106a,1106b,1106k). During operation, the base station1102(e.g., gNB) may detect targets (e.g., UEs1108a,1106a,1106b,1106k) and estimate parameters or characteristics (e.g., location, distance, movement, heading, size, etc.) of the targets.

Since, for example during a target detection phase, prior information regarding the number of the targets (e.g., UE1108a) is unknown to the base station1102, the base station1102(e.g., gNB) can maximize the degrees of freedom in its hardware (e.g., maximize the number of antenna elements utilized to transmit the different waveforms). In doing so, the base station1102(e.g., gNB) can transmit a rank Ntwaveform (e.g., orthogonal waveform) for the MIMO sensing of the targets. For example, in a MIMO radar system, each transmit antenna element of the base station1102(e.g., gNB) may transmit an orthogonal waveform. If there are a total of Nttransmit antenna elements in the antenna array, then maximally the base station1102(e.g., gNB) can transmit Ntnumber of waveforms that are orthogonal to each other, thereby forming a waveform with rank Nt.

However, the transmitting of a rank Nt waveform for the MIMO sensing of the targets may lead to a conflict between the sensing and the communications. For instance, in some MU-MIMO communications, the number of degrees of freedom (DoFs) is limited by the minimum number of transmit antennas Ntof the base station1102(e.g., gNB), which is min (Nt; J), where J is less than Nt(J<Nt), especially for mMIMO scenarios. The term J is the number of layers (e.g., communication orthogonal waveforms) that the base station1102(e.g., gNB) may schedule for its MU-MIMO downlink (DL) communications.

The base station1102(e.g., gNB) can estimate the rank of the channel, such as based on channel state information (CSI) feedback from the UEs (e.g., UE1108a). Based on the estimated rank of the channel, the base station1102(e.g., gNB) can determine the scheduling of the time/frequency resources for the waveform. However, the scheduling of the time/frequency resources and the waveform according to the CSI for MU-MIMO downlink communications (e.g., baseline for LTE/NR) may not fully exploit the waveform diversity for MIMO sensing. As such, the design metrics for MIMO communications and sensing can be conflicting. The systems and techniques described herein provide for unified waveforms (e.g., JCS waveforms) to efficiently enable joint MIMO sensing and MIMO (e.g., MU-MIMO, mMIMO, etc.) downlink communications for achieving a high spectral efficiency.

In one or more examples, the base station1102(e.g., gNB) may schedule and generate a JCS waveform (e.g., waveform X of rank Nt) for a joint transmission scheme to serve both communication and sensing purposes. In some cases, a matrix SCrepresents or includes communications resources of the JCS waveform and a matrix SArepresents or includes sensing resources of the JCS waveform. In some examples, the base station1102(e.g., gNB) can augment the data matrix SC(including the communications resources) for the waveform X by adding Nt−J number of dedicated sensing streams (including sensing resources) to the matrix SA, which may result in the waveform having a maximum of Nt−J dedicated sensing streams (with sensing resources). For instance, the Nt−J number of dedicated sensing streams (and corresponding sensing resources) may be used for sensing and may contain no information (while the communications resources include communications data). Then, the generated waveform X is rank Ntand can be represented as follows:
X=WCSC+WASA

where the matrix SCis rank J, and the matrix SAis rank Nt−J. WCand WAare matrices. For waveform X, orthogonality between WCSCand WASAis desirable. Waveform X is a JCS waveform of rank Ntthat can be employed for joint MIMO communications and MIMO sensing (e.g., monostatic sensing, bistatic sensing, or multistatic sensing).

As noted above, the Nt−J number of dedicated sensing steams is the maximum amount of sensing streams that can be allocated for waveform X. For example, during a target detection phase, when the base station1102(e.g., gNB or portion thereof, such as a CU, DU, RU, etc. of a disaggregated gNB) does not have any knowledge regarding the target(s), the base station1102may add the maximum number (e.g., Nt−J number) of sensing streams (sensing resources) for waveform X to maximize the degrees of freedom in an effort to locate the target(s). However, for example, during a target tracking phase where the base station1102has some general knowledge regarding the location(s) of the target(s), the base station1102may use less than the maximum number (e.g., Nt−J number) of sensing streams for waveform X because less degrees of freedom are needed to locate the target(s).

In some aspects, this joint precoder design (e.g., of the JCS waveform) enables spatial domain multiplexing (SDM), which allows for spatially correlated (e.g., spatially aligned) UEs to be able to use the JCS waveform for both communications and sensing. For example, the communication waveform can be reused for sensing when the targets (e.g., UEs1108a,1106a,1106b,1106k) and UEs (e.g., UE1108b) are spatially correlated (e.g., a target(s) and a UE(s) are spatially aligned in the same direction with each other).

In one or more examples, if the sensing is stand alone (e.g., without any cross-base station or cross-device coordination for the sensing) and monostatic (e.g., where the base station is solely performing the sensing itself), the base station1102may control the scheduling of the dedicated sensing streams (e.g., sensing resources). For example, in such examples, the base station1102may determine the waveform parameters for each of the sensing streams.

Conversely, if the sensing is network-based cooperative sensing (e.g., where the sensing server, such as radar server1010ofFIG.10, assists in the scheduling of the sensing resources), the sensing server (e.g., radar server1010ofFIG.10) may guide the base station1102to perform the scheduling of the dedicated sensing streams (sensing resources). For such network-based cooperative sensing, the base station1102may report its partial CSI, the number of layers for the downlink MIMO communications, and/or other information to the sensing server. After the sensing server receives partial CSI from one or more base stations (e.g., base station1102), the sensing server may guide the base stations for scheduling the additional sensing streams (e.g., additional sensing streams from the additional Nt−J number of dedicated sensing streams). In one or more examples, the sensing server may determine which base station of the base stations should operate as the sensing transmitter (e.g., radar transmitter), by considering the partial CSI from the base stations and the hardware capability of the base stations. For example, if the supported dedicated sensing streams supported by base station 1 may be greater than (>) the supported dedicated sensing streams supported by base station 2, then the sensing server may choose base station 1 to operate as the MIMO sensing transmitter (e.g., radar transmitter) to maximize the degrees of freedom, and may choose base station 2 to operate as the MIMO sensing receiver (e.g., radar receiver).

In one or more examples, the sensing server may signal (e.g., transmit signaling with) the sensing waveform parameters to the radar transmitter (e.g., base station 1) and to the radar receiver (e.g., base station 2). In other examples, the radar transmitter (e.g., base station 1) may signal (e.g., transmit signaling with) the number of dedicated sensing streams it plans to transmit to the sensing server (e.g., radar server1010ofFIG.10). It should be noted that the radar transmitter (e.g., base station 1) may also signal (e.g., transmit signaling with) other parameters associated with the sensing waveforms to the sensing server. The parameters and/or streams may be transmitted in one or more information elements (IEs) or fields of one or more messages. After receiving the parameters from the radar transmitter (e.g., base station 1), the sensing server may signal (e.g., transmit signaling) this information (e.g., the number of dedicated sensing streams and/or parameters associated with the sensing waveforms) to the radar receiver (e.g., base station 2).

In some cases, if a target (e.g., UE1108a) and a UE (e.g., UE1106a) are spatially correlated (e.g., spatially aligned with each other) and the dedicated sensing streams share the same time and frequency, the dedicated sensing streams may impact the performance of the downlink communications. In such cases, in one or more examples, if the sensing streams are OFDM based (e.g., the sensing streams include OFDM waveforms), the JCS waveform may be scheduled in one or more demodulation reference signal (DMRS) symbols, and the dedicated sensing streams can be orthogonal to DMRS antenna ports (e.g., logical antenna ports1414ofFIG.14) used to transmit the one or more DMRS symbols. Further in such cases, in one or more examples, if the sensing streams are OFDM based (e.g., the sensing streams include OFDM waveforms), the JCS waveform may be scheduled in one or more physical downlink shared channel (PDSCH) symbols. In some examples, when scheduled in one or more PDSCH symbols, the waveform orthogonality between the sensing streams and data streams (communication streams) may not be guaranteed because the PDSCH is a random signal. In some cases, if the sensing streams are non-OFDM based, the waveform orthogonality between the sensing streams and the data streams (communication streams) may not be guaranteed. The dedicated sensing streams, by default, are transparent to the UE (e.g., UE1108a), unless the UE is also operating as the radar receiver for the sensing.

In one or more examples, to assist in interference cancellation at the UE side, the base station1102may signal (e.g., transmit signaling with) information associated with the sensing streams to the UEs (e.g., UE1108a). In one or more examples, the information regarding the sensing streams may include, but is not limited to, additional antenna ports (e.g., logical antenna ports1414ofFIG.14) allocated for dedicated sensing streams, the time and frequency resource where the sensing streams are being added, the parameters for the sensing waveforms for each layer of the sensing streams, the power offset between the DMRS (or the PDSCH) and the sensing streams, any combination thereof, and/or other information. In some aspects, if the UE (e.g., UE1108a) is served by multiple transmission/reception points (TRPs), the UE may receive multiple sets of assistance information (e.g., assistance data (AD)). In some cases, each set of assistance information corresponds to a dedicated sensing stream associated with a specific TRP (e.g., base station, such as a gNB).

FIG.12is a diagram illustrating an example of a system1200for joint MIMO communications and MIMO sensing, where the system1200can utilize a JCS waveform for both communications and sensing (e.g., monostatic sensing) of a UE, in accordance with some aspects of the present disclosure. The system1200ofFIG.12is similar to the system1100ofFIG.11, except that the base station1102shown in the system1200ofFIG.12is additionally transmitting a communications signal1104cto a UE (e.g., UE1108a). Specifically, inFIG.12, the base station1102is shown to be transmitting both a communications signal1104cand a sensing signal1110ato UE1108a. As such, if the communications signal1104cand the sensing signal1110ashare the same time and frequency, there could be a conflict between the signals because the signals are directed towards the same network device. In order to obviate this possible confliction, the base station1102may employ the disclosed JCS waveform for the communications and the sensing of UE1108a.

FIG.13is a graph1300illustrating an example of a joint communications and sensing (JCS) waveform that may be employed for the disclosed system for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. InFIG.13, the x-axis of the graph1300denotes the angle (from negative 90 degrees to positive 90 degrees), and the y-axis of the graph1300denotes the magnitude in decibels (dBs).

In particular, inFIG.13, a cut of the beam pattern of an example JCS waveform is illustrated in the graph1300. The beam pattern of the JCS waveform exhibits 8 distinct antenna beams, which may radiate in a plurality of different directions and may be formed by an antenna array of a JCS transceiver (e.g., base station1102ofFIG.11). The two wide antenna beams on either side of the beam pattern include communication signals to be transmitted to UEs (e.g., UEs1106a,1106b,1106kofFIG.11), which are located at approximately −75 degrees and 80 degrees. The six narrow antenna beams located between the two wide antenna beams include sensing signals to be transmitted towards UEs (e.g., UE1108aofFIG.11), which are located at −45 degrees, −30 degrees, −10 degrees, 8 degrees, 25 degrees, and 55 degrees.

FIG.14is a diagram1400illustrating an example of a mapping of antenna ports (e.g., logical antenna ports1414) to physical antenna ports1404, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. In 5G NR and 4G LTE, MIMO is a key technology that is frequently employed (e.g., MIMO transmission is often utilized in the downlink). The term “antenna port,” as related to MIMO, is a logical concept related to the physical layer (e.g., Layer 1), not a physical concept related to a physical RF antenna located on a base station.

According to the 3GPP specification, an “antenna port” (e.g., logical antenna port1414) is defined such that the channel over which a symbol on the antenna port is conveyed can be inferred from the channel over which another symbol on the same antenna port is conveyed. As such, each individual downlink transmission that is transmitted from a specific antenna port, the identity of which is known to the UE, the UE can assume that two transmitted signals have experienced the same channel if and only if they are transmitted from the same antenna port. Thus, each antenna port, at least for downlink transmissions, can be assumed to correspond to a specific reference signal, and a UE receiver can assume that the reference signal can be used to estimate the channel (as well as derive channel-state information (CSI)) corresponding to the antenna port.

The 3GPP specification 38.211 for 5G NR defines sets of antenna ports (e.g., logical antenna ports1414) for the downlink as follows: the physical downlink shared channel (PDSCH) utilizes antenna ports starting from 1000 (the 1000 series), the physical downlink control channel (PDCCH) utilizes antenna ports starting from 2000 (the 2000 series), the channel state information-reference signal (CSI-RS) utilizes antenna ports starting from 3000 (the 3000 series), and the synchronization signal-block/physical broadcast channel (SS-Block/PBCH) utilizes antenna ports starting from 4000 (the 4000 series). The 3GPP specification 38.211 for 5G NR defines sets of antenna ports (e.g., logical antenna ports1414) for the uplink as follows: the physical uplink shared channel/demodulation reference signal (PUSCH/DMRS) utilizes antenna ports starting from 0 (the 0 series), the sounding reference signals (SRS), precoded PUSCH, utilizes antenna ports starting from 1000 (the 1000 series), the physical uplink control channel (PUCCH) utilizes antenna ports starting from 2000 (the 2000 series), and the physical random access channel (PRACH) utilizes antenna ports starting from 4000 (the 4000 series). It should be noted that different transmission layers for a channel (e.g., PDSCH) may use different antenna ports in the defined series. For example, antenna ports1000and1001may be utilized for a two-layer PDSCH transmission.

It should be noted that an “antenna port” is an abstract concept that does not necessarily correspond to a specific physical antenna port (e.g., physical antenna port1404). There is no strict mapping of antenna ports (e.g., logical antenna ports1414) to physical antenna ports (e.g., physical antenna ports1404) in 5G NR or 4G LTE. The mapping of an antenna port to a physical antenna port is controlled by beamforming, where a certain antenna beam needs to transmit a signal on certain antenna ports to form a desired antenna beam. There is a possibility that multiple antenna ports may be mapped to one physical antenna port, and/or a single antenna port may be mapped to multiple physical antenna ports.

InFIG.14, in particular, an overview of an example of 5G physical layer processing1412is shown. The 5G physical layer processing1412is shown to include a beam forming network1408, a resource mapper1410, and a plurality of antenna ports (e.g., logical antenna ports1414). The logical antenna ports1414are numbered from antenna port P0 to antenna port P4999, and are divided into a plurality of different series, which are separated out by rows in the figure. The plurality of different series of logical antenna ports1414includes series 0 spanning from antenna port P0 to antenna port P0999, series 1000 spanning from antenna port P1000 to antenna port P1999, series 2000 spanning from antenna port P2000 to antenna port P2999, series 3000 spanning from antenna port P3000 to antenna port 3999, and series 4000 spanning from antenna port P4000 to antenna port P4999.

Also inFIG.14, a physical antenna array1402is shown to include a plurality of physical antenna ports1404. InFIG.14, the physical antenna array1402is shown to include a total of 35 physical antenna ports1404. It should be noted that, in one or more examples, the physical antenna array1402may include more or less physical antenna ports1404, than as is shown inFIG.14. The physical antenna array1402may be in the form of various different types of physical antennas including, but not limited to, a direct radiating antenna array or a phased antenna array. The physical antenna array1402may include various different types of physical antenna elements, which may include, but are not limited to, horn antennas, patch antenna elements, cupped-dipole antenna elements, and/or dipole antenna elements. Each physical antenna element of the physical antenna array1402corresponds to a different physical antenna port1404of the physical antenna array1402.

During operation of the 5G physical layer processing1412, the beam forming network1408together with the resource mapper1410map the logical antenna ports1414to the physical antenna ports1404of the physical antenna array1402as required to form desired antenna beams1406a(Beam 1),1406b(Beam 2),1406c(Beam 3). Specifically, the logical antenna ports1414are mapped to the physical antenna ports1404such that signals are transmitted on certain physical antenna ports1404as required to form the desired antenna beams1406a,1406b,1406c.

As such, the logical antenna ports1414can be mapped to specific physical antenna ports1404of the physical antenna array1402. For example, antenna port P0 may be mapped to the first physical antenna port1404in the physical antenna array1402. It should be noted that multiple logical antenna ports1414may be mapped to only one physical antenna port1404, and/or a single logical antenna port from the multiple logical antenna ports1414may be mapped to multiple physical antenna ports1404.

FIG.15is a flow chart illustrating an example of a process1500for wireless communications utilizing joint MIMO communications and MIMO sensing. The process1500can be performed by a network entity (e.g., a base station such as an eNB or gNB, or one or more of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC of a base station having a disaggregated architecture) or by a component or system (e.g., a chipset) of the network entity. The operations of the process1500may be implemented as software components that are executed and run on one or more processors (e.g., processor1710ofFIG.17or other processor(s)). Further, the transmission and reception of signals by the wireless communications device in the process1500may be enabled, for example, by one or more antennas and/or one or more transceivers (e.g., wireless transceiver(s)).

At block1510, the network entity (or component thereof) may generate a waveform including communications resources and sensing resources based on a maximum of Nt−J sensing streams. The waveform has a rank Ntand the network entity includes Ntnumber of transmitting antenna elements. J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications (e.g., multiple-user MIMO (MU-MIMO) communications) and is less than Nt. In some cases, the network entity includes at least one antenna array including the transmitting antenna elements.

In some aspects, the waveform is defined using a matrix SCand a matrix SA, as described herein. For instance, the matrix SCmay represent the communications resources and the matrix SAmay represent the sensing resources. In one illustrative example, the matrix SCis rank J and the matrix SAis rank Nt−J. In some cases, the waveform includes a first waveform WCSCassociated with the communications resources and a second waveform WASAassociated with the sensing resources, wherein WCand WAare matrices. In some examples, the first waveform WCSCand the second waveform WASAare orthogonal to each other. In some aspects, the communications resources include communications data, and the sensing resources include no data.

In some cases, the network entity (or component thereof) may schedule the waveform. In some cases, the waveform is scheduled by a radar server. In some aspects, the waveform is scheduled (e.g., by the network entity or component thereof, by the radar server, etc.) within a plurality of demodulation reference signal (DMRS) symbols. In such aspects, the Nt−J sensing streams may be orthogonal to a plurality of DMRS ports associated with the plurality of DMRS symbols. In some aspects, the waveform is scheduled (e.g., by the network entity or component thereof, by the radar server, etc.) within a plurality of physical downlink shared channel (PDSCH) symbols.

At block1520, the network entity (or component thereof) may transmit, via a number of sensing streams based on the maximum of Nt−J sensing streams, the waveform to one or more network devices for MIMO communications and MIMO sensing. The network devices may include at least one user equipment (UE) or other network device(s) (e.g., a mobile device, an XR device such as a VR device, AR device, MR device etc., a wearable such as a network-connected watch etc., a vehicle or component or system of the vehicle, or other network device). In some aspects, the network entity (or component thereof) may reuse the communications resources for sensing the one or more network devices based on at least two of the one or more network devices being spatially correlated (e.g., spatially aligned with each other).

FIG.16is a flow chart illustrating an example of a process1600for wireless communications utilizing joint MIMO communications and MIMO sensing. The process1600can be performed by a network device (e.g., a UE such as a mobile device, an XR device such as a VR device, AR device, MR device etc., a wearable such as a network-connected watch etc., a vehicle or component or system of the vehicle, or other network device) or by a component or system (e.g., a chipset) of the network device. The operations of the process1600may be implemented as software components that are executed and run on one or more processors (e.g., processor1710ofFIG.17or other processor(s)). Further, the transmission and reception of signals by the wireless communications device in the process1600may be enabled, for example, by one or more antennas and/or one or more transceivers (e.g., wireless transceiver(s)).

At block1610, the network device (or component thereof) may receive, from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform including communications resources and sensing resources. For instance, the network entity may be a base station (e.g., a gNB, an eNB, etc.) or a CU, a DU, a RU, a Near-RT RIC, or a Non-RT RIC of a base station having a disaggregated architecture. The waveform has a rank Ntand the network entity includes Ntnumber of transmitting antenna elements. J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications (e.g., multiple-user MIMO (MU-MIMO) communications) and is less than Nt. In some cases, the network entity includes at least one antenna array including the transmitting antenna elements.

In some aspects, the waveform is defined using a matrix SCand a matrix SA, as described herein. For instance, the matrix SCmay represent the communications resources and the matrix SAmay represent the sensing resources. In one illustrative example, the matrix SCis rank J and the matrix SAis rank Nt−J. In some cases, the waveform includes a first waveform WCSCassociated with the communications resources and a second waveform WASAassociated with the sensing resources, wherein WCand WAare matrices. In some examples, the first waveform WCSCand the second waveform WASAare orthogonal to each other. In some aspects, the communications resources include communications data, and the sensing resources include no data.

In some cases, the waveform is scheduled by the network entity (or component thereof). In some cases, the waveform is scheduled by a radar server. In some aspects, the waveform is scheduled (e.g., by the network entity or component thereof, by the radar server, etc.) within a plurality of demodulation reference signal (DMRS) symbols. In such aspects, the Nt−J sensing streams may be orthogonal to a plurality of DMRS ports associated with the plurality of DMRS symbols. In some aspects, the waveform is scheduled (e.g., by the network entity or component thereof, by the radar server, etc.) within a plurality of physical downlink shared channel (PDSCH) symbols.

At block1620, the network device (or component thereof) may process at least the communications resources of the waveform. In some aspects, the communications resources are reused (e.g., by the network entity, the network device, or other device or server) for sensing the one or more network devices based on at least two of the one or more network devices being spatially correlated (e.g., spatially aligned with each other).

FIG.17is a block diagram illustrating an example of a computing system1700, which may be employed by the disclosed systems and techniques for joint MIMO communications and MIMO sensing, in accordance with some aspects of the present disclosure. In particular,FIG.17illustrates an example of computing system1700, which can be for example any computing device making up internal computing system, a remote computing system, a camera, or any component thereof in which the components of the system are in communication with each other using connection1705. Connection1705can be a physical connection using a bus, or a direct connection into processor1710, such as in a chipset architecture. Connection1705can also be a virtual connection, networked connection, or logical connection.

Example system1700includes at least one processing unit (CPU or processor)1710and connection1705that communicatively couples various system components including system memory1715, such as read-only memory (ROM)1720and random access memory (RAM)1725to processor1710. Computing system1700can include a cache1712of high-speed memory connected directly with, in close proximity to, or integrated as part of processor1710.

Processor1710can include any general purpose processor and a hardware service or software service, such as services1732,1734, and1736stored in storage device1730, configured to control processor1710as well as a special-purpose processor where software instructions are incorporated into the actual processor design. Processor1710may essentially be a completely self-contained computing system, containing multiple cores or processors, a bus, memory controller, cache, etc. A multi-core processor may be symmetric or asymmetric.

To enable user interaction, computing system1700includes an input device1745, which can represent any number of input mechanisms, such as a microphone for speech, a touch-sensitive screen for gesture or graphical input, keyboard, mouse, motion input, speech, etc. Computing system1700can also include output device1735, which can be one or more of a number of output mechanisms. In some instances, multimodal systems can enable a user to provide multiple types of input/output to communicate with computing system1700.

Computing system1700can include communications interface1740, which can generally govern and manage the user input and system output. The communication interface may perform or facilitate receipt and/or transmission wired or wireless communications using wired and/or wireless transceivers, including those making use of an audio jack/plug, a microphone jack/plug, a universal serial bus (USB) port/plug, an Apple™ Lightning™ port/plug, an Ethernet port/plug, a fiber optic port/plug, a proprietary wired port/plug, 3G, 4G, 5G and/or other cellular data network wireless signal transfer, a Bluetooth™ wireless signal transfer, a Bluetooth™ low energy (BLE) wireless signal transfer, an IBEACON™ wireless signal transfer, a radio-frequency identification (RFID) wireless signal transfer, near-field communications (NFC) wireless signal transfer, dedicated short range communication (DSRC) wireless signal transfer, 802.11 Wi-Fi wireless signal transfer, wireless local area network (WLAN) signal transfer, Visible Light Communication (VLC), Worldwide Interoperability for Microwave Access (WiMAX), Infrared (IR) communication wireless signal transfer, Public Switched Telephone Network (PSTN) signal transfer, Integrated Services Digital Network (ISDN) signal transfer, ad-hoc network signal transfer, radio wave signal transfer, microwave signal transfer, infrared signal transfer, visible light signal transfer, ultraviolet light signal transfer, wireless signal transfer along the electromagnetic spectrum, or some combination thereof.

The communications interface1740may also include one or more range sensors (e.g., LIDAR sensors, laser range finders, RF radars, ultrasonic sensors, and infrared (IR) sensors) configured to collect data and provide measurements to processor1710, whereby processor1710can be configured to perform determinations and calculations needed to obtain various measurements for the one or more range sensors. In some examples, the measurements can include time of flight, wavelengths, azimuth angle, elevation angle, range, linear velocity and/or angular velocity, or any combination thereof. The communications interface1740may also include one or more Global Navigation Satellite System (GNSS) receivers or transceivers that are used to determine a location of the computing system1700based on receipt of one or more signals from one or more satellites associated with one or more GNSS systems. GNSS systems include, but are not limited to, the US-based GPS, the Russia-based Global Navigation Satellite System (GLONASS), the China-based BeiDou Navigation Satellite System (BDS), and the Europe-based Galileo GNSS. There is no restriction on operating on any particular hardware arrangement, and therefore the basic features here may easily be substituted for improved hardware or firmware arrangements as they are developed.

Specific details are provided in the description above to provide a thorough understanding of the aspects and examples provided herein, but those skilled in the art will recognize that the application is not limited thereto. Thus, while illustrative aspects of the application have been described in detail herein, it is to be understood that the inventive concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations, except as limited by the prior art. Various features and aspects of the above-described application may be used individually or jointly. Further, aspects can be utilized in any number of environments and applications beyond those described herein without departing from the broader scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive. For the purposes of illustration, methods were described in a particular order. It should be appreciated that in alternate aspects, the methods may be performed in a different order than that described.

The phrase “coupled to” or “communicatively coupled to” refers to any component that is physically connected to another component either directly or indirectly, and/or any component that is in communication with another component (e.g., connected to the other component over a wired or wireless connection, and/or other suitable communication interface) either directly or indirectly.

Illustrative aspects of the disclosure include:

Aspect 1. An apparatus for wireless communications, the apparatus comprising: at least one memory; and at least one processor coupled to the at least one memory, the at least one processor configured to: receive, from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform comprising communications resources and sensing resources, the waveform having a rank Nt, wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and process at least the communications resources of the waveform.

Aspect 2. The apparatus of Aspect 1, wherein the waveform is defined using a matrix SCand a matrix SA, wherein the matrix SCrepresents the communications resources and the matrix SArepresents the sensing resources.

Aspect 3. The apparatus of Aspect 2, wherein the matrix SCis rank J.

Aspect 4. The apparatus of any of Aspects 2 or 3, wherein the matrix SAis rank Nt−J.

Aspect 5. The apparatus of any of Aspects 2 to 4, wherein the waveform comprises a first waveform WCSC associated with the communications resources and a second waveform WASA associated with the sensing resources, wherein WC and WA are matrices.

Aspect 6. The apparatus of Aspect 5, wherein the first waveform WCSC and the second waveform WASA are orthogonal to each other.

Aspect 7. The apparatus of any of Aspects 1 to 6, wherein the communications resources are reused for sensing one or more network devices based on at least two of the one or more network devices being spatially correlated.

Aspect 8. The apparatus of any of Aspects 1 to 7, wherein the MIMO communications are multiple-user MIMO (MU-MIMO) communications.

Aspect 9. The apparatus of any of Aspects 1 to 8, wherein the communications resources comprise communications data, and wherein the sensing resources comprise no data.

Aspect 10. The apparatus of any of Aspects 1 to 9, wherein the waveform is scheduled within a plurality of demodulation reference signal (DMRS) symbols, and wherein the Nt−J sensing streams are orthogonal to a plurality of DMRS ports associated with the plurality of DMRS symbols.

Aspect 11. The apparatus of any of Aspects 1 to 10, wherein the waveform is scheduled within a plurality of physical downlink shared channel (PDSCH) symbols.

Aspect 12. The apparatus of any of Aspects 1 to 11, wherein the network entity is a base station.

Aspect 13. The apparatus of Aspect 12, wherein the base station is one of a next generation node B (gNB) or an evolved node B (eNB).

Aspect 14. The apparatus of any of Aspects 1 to 13, wherein the network entity is at least one of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC of a base station.

Aspect 15. The apparatus of any of Aspects 1 to 14, wherein the apparatus includes a user equipment (UE).

Aspect 16. The apparatus of any of Aspects 1 to 15, wherein the waveform is scheduled by the network entity or a radar server.

Aspect 17. A method for wireless communications at a user equipment (UE), the method comprising: receiving, at the UE from a network entity via a number of sensing streams based on a maximum of Nt−J sensing streams, a waveform comprising communications resources and sensing resources, the waveform having a rank Nt, wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and processing at least the communications resources of the waveform.

Aspect 18. The method of Aspect 17, wherein the waveform is defined using a matrix SCand a matrix SA, wherein the matrix SCrepresents the communications resources and the matrix SArepresents the sensing resources.

Aspect 19. The method of any of Aspects 17 or 18, wherein the matrix SCis rank J.

Aspect 20. The method of any of Aspects 17 to 19, wherein the matrix SAis rank Nt−J.

Aspect 21. The method of any of Aspects 17 to 20, wherein the waveform comprises a first waveform WCSCassociated with the communications resources and a second waveform WASAassociated with the sensing resources, wherein WCand WAare matrices.

Aspect 22. The method of Aspect 21, wherein the first waveform WCSCand the second waveform WASAare orthogonal to each other.

Aspect 23. The method of any of Aspects 17 to 22, wherein the communications resources are reused for sensing one or more network devices based on at least two of the one or more network devices being spatially correlated.

Aspect 24. The method of any of Aspects 17 to 23, wherein the MIMO communications are multiple-user MIMO (MU-MIMO) communications.

Aspect 25. The method of any of Aspects 17 to 24, wherein the communications resources comprise communications data, and wherein the sensing resources comprise no data.

Aspect 26. The method of any of Aspects 17 to 25, wherein the waveform is scheduled within a plurality of demodulation reference signal (DMRS) symbols, and wherein the Nt−J sensing streams are orthogonal to a plurality of DMRS ports associated with the plurality of DMRS symbols.

Aspect 27. The method of any of Aspects 17 to 26, wherein the waveform is scheduled within a plurality of physical downlink shared channel (PDSCH) symbols.

Aspect 28. The method of any of Aspects 17 to 27, wherein the network entity is a base station.

Aspect 29. The method of Aspect 28, wherein the base station is one of a next generation node B (gNB) or an evolved node B (eNB).

Aspect 30. The method of any of Aspects 17 to 29, wherein the network entity is at least one of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC of a base station.

Aspect 31. The method of any of Aspects 17 to 30, wherein the waveform is scheduled by a radar server by the network entity.

Aspect 32. The method of any of Aspects 17 to 30, wherein the waveform is scheduled by a radar server.

Aspect 33. An apparatus for wireless communications, the apparatus comprising: at least one memory; and at least one processor coupled to at least one memory, the at least one processor configured to: generate a waveform comprising communications resources and sensing resources based on a maximum of Nt−J sensing streams, the waveform having a rank Nt, wherein the apparatus comprises Ntnumber of transmitting antenna elements, and wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and transmit, via a number of sensing streams based on the maximum of Nt−J sensing streams, the waveform to one or more network devices for MIMO communications and MIMO sensing.

Aspect 34. The apparatus of Aspect 33, wherein the waveform is defined using a matrix SCand a matrix SA, wherein the matrix SCrepresents the communications resources and the matrix SArepresents the sensing resources.

Aspect 35. The apparatus of any of Aspects 33 or 34, wherein the matrix SCis rank J.

Aspect 36. The apparatus of any of Aspects 33 to 35, wherein the matrix SAis rank Nt−J.

Aspect 37. The apparatus of any of Aspects 33 to 36, wherein the waveform comprises a first waveform WCSCassociated with the communications resources and a second waveform WASAassociated with the sensing resources, wherein WCand WAare matrices.

Aspect 38. The apparatus of Aspect 37, wherein the first waveform WCSC and the second waveform WASA are orthogonal to each other.

Aspect 39. The apparatus of any of Aspects 33 to 38, wherein the at least one processor is configured to: reuse the communications resources for sensing the one or more network devices based on at least two of the one or more network devices being spatially correlated.

Aspect 40. The apparatus of any of Aspects 33 to 39, wherein the MIMO communications are multiple-user MIMO (MU-MIMO) communications.

Aspect 41. The apparatus of any of Aspects 33 to 40, wherein the communications resources comprise communications data, and wherein the sensing resources comprise no data.

Aspect 42. The apparatus of any of Aspects 33 to 41, wherein the apparatus comprises at least one antenna array including the transmitting antenna elements.

Aspect 43. The apparatus of any of Aspects 33 to 42, wherein the waveform is scheduled within a plurality of demodulation reference signal (DMRS) symbols, and wherein the Nt−J sensing streams are orthogonal to a plurality of DMRS ports associated with the plurality of DMRS symbols.

Aspect 44. The apparatus of any of Aspects 33 to 43, wherein the waveform is scheduled within a plurality of physical downlink shared channel (PDSCH) symbols.

Aspect 45. The apparatus of any of Aspects 33 to 44, wherein the apparatus is a base station.

Aspect 46. The apparatus of Aspect 45, wherein the base station is one of a next generation node B (gNB) or an evolved node B (eNB).

Aspect 47. The apparatus of any of Aspects 33 to 46, wherein the apparatus is at least one of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC of a base station.

Aspect 48. The apparatus of any of Aspects 33 to 47, wherein the one or more network devices includes at least one user equipment (UE).

Aspect 49. The apparatus of any of Aspects 33 to 48, wherein the at least one processor is configured to: schedule the waveform.

Aspect 50. The apparatus of any of Aspects 33 to 48, wherein the waveform is scheduled by a radar server.

Aspect 51. A method for wireless communications at a network entity, the method comprising: generating, at the network entity, a waveform comprising communications resources and sensing resources based on a maximum of Nt−J sensing streams, the waveform having a rank Nt, wherein the network entity comprises Ntnumber of transmitting antenna elements, and wherein J is a number of layers scheduled for multiple-input multiple-output (MIMO) communications and is less than Nt; and transmitting, via a number of sensing streams based on the maximum of Nt−J sensing streams, the waveform to one or more network devices for MIMO communications and MIMO sensing.

Aspect 52. The method of Aspect 51, wherein the waveform is defined using a matrix SCand a matrix SA, wherein the matrix SCrepresents the communications resources and the matrix SArepresents the sensing resources.

Aspect 53. The method of any of Aspects 51 or 52, wherein the matrix SCis rank J.

Aspect 54. The method of any of Aspects 51 to 53, wherein the matrix SAis rank Nt−J.

Aspect 55. The method of any of Aspects 51 to 54, wherein the waveform comprises a first waveform WCSCassociated with the communications resources and a second waveform WASAassociated with the sensing resources, wherein WCand WAare matrice.

Aspect 56. The method of Aspect 55, wherein the first waveform WCSCand the second waveform WASAare orthogonal to each other.

Aspect 57. The method of any of Aspects 51 to 56, further comprising reusing the communications resources for sensing the one or more network devices based on at least two of the one or more network devices being spatially correlated.

Aspect 58. The method of any of Aspects 51 to 57, wherein the MIMO communications are multiple-user MIMO (MU-MIMO) communications.

Aspect 59. The method of any of Aspects 51 to 58, wherein the communications resources comprise communications data, and wherein the sensing resources comprise no data.

Aspect 60. The method of any of Aspects 51 to 59, wherein the network entity comprises at least one antenna array including the transmitting antenna elements.

Aspect 61. The method of any of Aspects 51 to 60, wherein the waveform is scheduled within a plurality of demodulation reference signal (DMRS) symbols, and wherein the Nt−J sensing streams are orthogonal to a plurality of DMRS ports associated with the plurality of DMRS symbols.

Aspect 62. The method of any of Aspects 51 to 61, wherein the waveform is scheduled within a plurality of physical downlink shared channel (PDSCH) symbols.

Aspect 63. The method of any of Aspects 51 to 62, wherein the network entity is a base station.

Aspect 64. The method of Aspect 63, wherein the base station is one of a next generation node B (gNB) or an evolved node B (eNB).

Aspect 65. The method of any of Aspects 51 to 64, wherein the network entity is at least one of a central unit (CU), a distributed unit (DU), a radio unit (RU), a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC), or a Non-Real Time (Non-RT) RIC of a base station.

Aspect 66. The method of any of Aspects 51 to 65, wherein the one or more network devices includes at least one user equipment (UE).

Aspect 67. The method of any of Aspects 51 to 66, further comprising: scheduling, at the network entity, the waveform.

Aspect 68. The method of any of Aspects 51 to 66, wherein the waveform is scheduled by a radar server.