METHOD AND APPARATUS FOR COMPOSITE BEAM OPERATION AND OVERHEAD REDUCTION

A method includes identifying child beams of a current composite beam. The method also includes determining an order at which the child beams of the current composite beam are measured based on a likelihood that each child beam of the current composite beam is an optimal beam, among the child beams, to be a serving narrow beam. The method also includes determining a threshold for use in deciding whether to measure one or more additional child beams or select an already measured child beam when selecting the optimal beam. The method also includes selecting the optimal beam, among the child beams, to be the serving narrow beam based on the determined order and the determined threshold.

TECHNICAL FIELD

The present disclosure relates generally to wireless communication systems and, more specifically, the present disclosure relates to a method and apparatus for composite beam operation and overhead reduction.

BACKGROUND

An important part of 5G mmWave communications is beam forming, which is the process in which the transmit energy is narrowly focused into the receiver antenna array, resulting in high channel gains and throughput. However, additional information is needed by the transmitter to decide where to point its transmission such that the receiver is within the beam width of the formed narrow beam. To this end, beam sweeping has been frequently used for successful beamforming and is adopted in the 3GPP NR standard. In this scheme, the transmitter has a set of predefined narrow beams covering the whole desired angular region. The transmitter sends a pilot signal using one narrow beam at a time and asks the receiver to measure the reference signal received power (RSRP) of each beam. Then the receiver feeds back the index of the beam that has the maximum RSRP to the transmitter, and the transmitter uses this beam to transmit data to the receiver.

SUMMARY

The present disclosure relates to wireless communication systems and, more specifically, the present disclosure relates to a method and apparatus for composite beam operation and overhead reduction.

In one embodiment, a method includes identifying child beams of a current composite beam. The method also includes determining an order at which the child beams of the current composite beam are measured based on a likelihood that each child beam of the current composite beam is an optimal beam, among the child beams, to be a serving narrow beam. The method also includes determining a threshold for use in deciding whether to measure one or more additional child beams or select an already measured child beam when selecting the optimal beam. The method also includes selecting the optimal beam, among the child beams, to be the serving narrow beam based on the determined order and the determined threshold.

In another embodiment, a device includes a transceiver and a processor operably connected to the transceiver. The processor is configured to: identify child beams of a current composite beam; determine an order at which the child beams of the current composite beam are measured based on a likelihood that each child beam of the current composite beam is an optimal beam, among the child beams, to be a serving narrow beam; determine a threshold for use in deciding whether to measure one or more additional child beams or select an already measured child beam when selecting the optimal beam; and select the optimal beam ; among the child beams, to be the serving narrow beam based on the determined order and the determined threshold.

In yet another embodiment, a non-transitory computer readable medium includes program code that, when executed by a processor of a device, causes the device to: identify child beams of a current composite beam; determine an order at which the child beams of the current composite beam are measured based on a likelihood that each child beam of the current composite beam is an optimal beam, among the child beams, to be a serving narrow beam; determine a threshold for use in deciding whether to measure one or more additional child beams or select an already measured child beam when selecting the optimal beam; and select the optimal beam, among the child beams, to be the serving narrow beam based on the determined order and the determined threshold.

DETAILED DESCRIPTION

Aspects, features, and advantages of the disclosure are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the disclosure. The disclosure is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the disclosure. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive. The disclosure is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings.

The present disclosure covers several components which can be used in conjunction or in combination with one another or can operate as standalone schemes. Certain embodiments of the disclosure may be derived by utilizing a combination of several of the embodiments listed below. Also, it should be noted that further embodiments may be derived by utilizing a particular subset of operational steps as disclosed in each of these embodiments. This disclosure should be understood to cover all such embodiments.

In addition, in 5G/NR communication systems, development for system network improvement is under way based on advanced small cells, cloud radio access networks (RANs), ultra-dense networks, device-to-device (D2D) communication, wireless backhaul, moving network, cooperative communication, coordinated multi-points (CAP), reception-end interference cancelation and the like.

In some embodiments, the network130facilitates communications between at least one server134and various client devices, such as a client device136. The server134includes any suitable computing or processing device that can provide computing services for one or more client devices. The server134could, for example, include one or more processing devices, one or more memories storing instructions and data, and one or more network interfaces facilitating communication over the network130.

The client device136represents any suitable computing or processing device that interacts with at least one server or other computing device(s) over the network130. In this example, the client device is represented as a desktop computer, but other examples of client devices can include a mobile telephone, laptop computer, or tablet computer. However, an other or additional client devices could be used in the wireless network100.

In this example, client devices can communicate indirectly with the network130. For example, some client devices can communicate via one or more base stations, such as cellular base stations or eNodeBs. Also, client devices can communicate via one or more wireless access points (not shown), such as IEEE 802.11 wireless access points. Note that these are for illustration only and that each client device136could communicate directly with the network130or indirectly with the network130via any suitable intermediate device(s) or network(s).

As described in more detail below, a computing device, such as the server134or the client device136, may perform operations in connection with beam management. For example, the server134or the client device136may perform operations in connection with composite beam operation and overhead reduction as discussed herein.

The controller/processor225can include one or more processors or other processing devices that control the overall operation of the gNB102. For example, the controller/processor225could control the reception of UL channel signals and the transmission of DL channel signals by the transceivers210a-210nin accordance with well-known principles. The controller/processor225could support additional functions as well, such as more advanced wireless communication functions. For instance, the controller/processor225could support composite beam operation and overhead reduction as discussed herein. Any of a wide variety of other functions could be supported in the gNB102by the controller/processor225.

The transceiver(s)310receives, from the antenna305, an incoming RE signal transmitted by a gNB of the network100. The transceiver(s)310down-converts the incoming RF signal to generate an intermediate frequency (IF) or baseband signal. The IF or baseband signal is processed by RX processing circuitry in the transceiver(s)310and/or processor340, which generates a processed baseband signal by filtering, decoding, and/or digitizing the baseband or IF signal. The RX processing circuitry sends the processed baseband signal to the speaker330(such as for voice data) or is processed by the processor340(such as for web browsing data).

TX processing circuity in the transceivers)310and/or processor340receives analog or digital voice data from the microphone320or other outgoing baseband data (such as web data, e-mail, or interactive video game data) from the processor340. The TX processing circuitry encodes, multiplexes, and/or digitizes the outgoing baseband data to generate a processed baseband or IF signal. The transceiver(s)310up-converts the baseband or IF signal to an RF signal that is transmitted via the antenna(s)305.

FIG.4illustrates an example beamforming architecture400according to embodiments of the present disclosure. The embodiment of the beamforming architecture400illustrated inFIG.4is for illustration only.FIG.4does not limit the scope of this disclosure to any particular implementation of the beamforming architecture400. In certain embodiments, one or more of gNB102or UE116can include the beamforming architecture400. For example, one or more of antenna205and its associated systems or antenna305and its associated systems can be configured the same as or similar to the beamforming architecture400.

Rel.14 LTE and Rel.15 NR support up to 32 CSI-RS antenna ports which enable an eNB to be equipped with a large number of antenna elements (such as 64 or 128). In this case, a plurality of antenna elements is mapped onto one CSI-RS port. For mmWave bands, although the number of antenna elements can be larger for a given form factor, the number of CSI-RS ports—which can correspond to the number of digitally precoded ports—tends to be limited due to hardware constraints (such as the feasibility to install a large number of analog-to-digital converts/digital-to-analog converts (ADCs/DACs at mmWave frequencies)).

In the example shown inFIG.4, the beamforming architecture400includes analog phase shifters405, an analog beamformer (BF)410, a hybrid BF415, a digital BF420, and one or more antenna arrays425. In this case, one CSI-RS port is mapped onto a large number of antenna elements in antenna arrays425, which can be controlled by the bank of analog phase shifters405. One CSI-RS port can then correspond to one sub-array which produces a narrow analog beam through analog beamforming by analog BF410. The analog beam can be configured to sweep across a wider range of angles by varying the phase shifter bank405across symbols or subframes. The number of sub-arrays (equal to the number of RF chains) is the same as the number of CSI-RS ports NCSI-PORT. The digital BF420performs a linear combination across NCSI-PORT analog beams to further increase precoding gain. While analog beams are wideband (hence not frequency-selective), digital precoding can be varied across frequency sub-bands or resource blocks.

Since the above system utilizes multiple analog beams for transmission and reception (wherein one or a small number of analog beams are selected out of a large number, for instance, after a training duration—to be performed from time to time), the term “multi-beam operation” is used to refer to the overall system aspect. This includes, for the purpose of illustration, indicating the assigned DL or UL transmit (TX) beam (also termed “beam indication”), measuring at least one reference signal for calculating and performing beam reporting (also termed “beam measurement” and “beam reporting”, respectively), and receiving a DL or UL transmission via a selection of a corresponding receive (RX) beam.

Additionally, the beamforming architecture400is also applicable to higher frequency bands such as >52.6 GHz (also termed the FR4), In this case, the beamforming architecture400can employ only analog beams. Due to the O2 absorption loss around 60 GHz frequency (˜10 decibels (dB) additional loss @100 m distance), larger numbers of and sharper analog beams (hence larger number of radiators in the array) will be needed to compensate for the additional path loss.

As discussed above, an important part of 5G mmWave communications is beamforming, which is the process in which the transmit energy is narrowly focused into the receiver antenna array, resulting in high channel gains and throughput. However, additional information is needed by the transmitter to decide where to point its transmission such that the receiver is within the beam width of the formed narrow beam. To this end, beam sweeping has been frequently used for successful beamforming and is adopted in the 3GPP NR standard. In this scheme, the transmitter has a set of predefined narrow beams covering the whole desired angular region. The transmitter sends a pilot signal using one narrow beam at a time and asks the receiver to measure the reference signal received power (RSRP) of each beam. Then the receiver feeds back the index of the beam that has the maximum RSRP to the transmitter, and the transmitter uses this beam to transmit data to the receiver.

However, the best beam to use is determined by the time-varying channel between transmitter and receiver. Hence, the beam sweeping process has to be repeated every now and then to make sure that the transmitter is using the best beam to send data to the receiver. For example, in the 3GPP 5G NR standard, this process is done every SSB period, denoted hereafter by TSS, which can be set to 20 ms. Every TSSthe BS has to determine which beam to use through beam sweeping, then use it to transmit data during the remaining time of TSS. Hence, the overhead of beam sweeping is observed every TSS. Ideally, this overhead is minimized while maintaining reasonably fresh measurements of the channel. Hereafter, the time used to perform beam sweeping is referred to by TBS.FIG.5illustrates a timeline500showing periodic, beam sweeping in 5G NR. As shown inFIG.5, every SSB period502includes a beam sweeping period504.

Assuming that the BS has a set of narrow beams with a size of N, then it is clear from the discussion so far that the BS has to measure N beams to determine which beam to use every TSS. To reduce this overhead, an improved scheme, denoted as composite beam (CB) beamforming, has been used. In this scheme, a composite beam is formed by combining two narrow beams, resulting in a total of N/2 composite beams. Then the BS transmits a pilot signal on each of the composite beams to determine which composite beam is optimal to use. After which, the BS transmits a pilot signal on each of the narrow beams forming the optimal composite beam and asks the UE to report the measured RSRP of these two beams. The BS then selects the narrow beam with the highest RSRP as the serving beam. Hence, the BS needs to only measure

beams. The

NBs are measured through MAC-CE signaling, and the remaining two NBs are measured through CSI-RS signaling.

Forming the CBs can be achieved through separating the antenna array into two separate subarrays, each having a set of NBs. Then a NB from the first subarray is paired with a NB from the second subarray forming a CB. Then after finding the best NB, only a single subarray is used to beam form towards the desired user. In this case, each subarray could be used to serve a certain user. However, the CBs can be formed utilizing the whole array, where a set of NBs are designed for the whole array, then each two NBs are paired to form a CB. In this case, the whole array is used to beamform towards the desired user, and the BS can focus the energy in a single direction at any given time.

It is noted that a composite beam system can also be implemented with three (or more) narrow beams for a single SSB index. The term “narrow beam” is used here since a large antenna. array, which is a typical setup for 5G mmWave network deployment, is capable of forming narrow beams.

The problem in the baseline approach is the need to measure two NBs (or more if more NBs are used to form each CB) beams every TSSthrough CSI-RS signaling. This reduces the time available to the BS to transmit data to the UE. Also, higher overheads increase the latency, which is critical in 5G communications.

To address these and other issues, this disclosure provides systems and methods for composite beam operation and overhead reduction. The disclosed embodiments reduce the beam measurement overhead by reducing the number of beams the BS has to measure. This is achieved by the BS using one or more novel procedures to determine how many child beams it needs to measure before determining the serving beam. The procedures focus on carefully choosing the order in which the narrow beams are measured and calculating a threshold to determine when to stop measuring the narrow beams' RSRP and choose the best out of the ones already measured. As a result, the disclosed embodiments provide multiple important properties, including increasing the data throughput and reducing the latency experienced by the UE.

Some of the embodiments discussed below are described in the context of mmWave bands. Of course, these are merely examples. It will be understood that the principles of this disclosure may be implemented in any number of other composite beam systems with any beam-width. Also, it is noted that despite a focus on the RSRP in the description below, the UE measurements of the channel could be reference signal received quality (RSRQ), channel quality indicator (CQI), signal-to-noise-ratio (SNR), signal-to-interference-noise-ratio (SINR), and the like. The embodiments in this disclosure can be applied to those measurement metrics as well.

FIG.6illustrates an example process600for composite beam operation and overhead reduction according to embodiments of the present disclosure. For ease of explanation, the process600will be described as performed by the BS102ofFIG.1; however, the process600could be performed by any other suitable device or system. The embodiment of the process600shown inFIG.6is for illustration only. Other embodiments of the process600could be used without departing from the scope of this disclosure.

Using the process600, the BS102can choose the order at which the child beams of the current best composite beam are measured. Broadly speaking, the main idea is to properly order the narrow beams of the current best CB before measuring them and only measure the first one as a reference point. Then only measure the second beam if the RSRP of the first one is low and there is a potential gain from measuring the second beam. The order takes into account the previously used NBs and CBs and is based on the likelihood that each child narrow beam of the current CB is the best beam. An example of determining the likelihood is based on the distance between the previous NB and each child of the current CB. Smaller distance increases the chance that the NB will be searched first. The BS102can also adaptively determine the threshold used by the BS102to determine whether to search more child beams or choose the best out the ones already measured. If the RSRP of the child beam is higher than the threshold, then the BS102will stop measuring the rest of the beams and make the beam with the highest RSRP the serving beam.

As shown inFIG.6, the process600includes operation601, in which the BS102determines the child NBs of the current CB622. In this example, there are two child NBs, which are denoted as N0and N1.

At operation603, the BS102determines an order for the child NBs N0and N1of the current CB622. In one option, the BS102orders the child NBs based on the likelihood that they are the best NB. That is, the determined order can be an order from mostly likely to be the best beam to least likely to be the best beam. The likelihood could be computed based on the angular distance between the child NBs and the previous NB. For example, if the previous NB points to the direction (θ0, ϕ0) and the child NBs of the best CB point to the directions (θ1, ϕ1), (θ2, ϕ2), . . . , (θN, ϕN), then the angular distance between (θ0, ϕ0) and (θi, ϕi) could be computed as:

The child NB with the smaller diis searched first. The child beam with the larger diis searched later. Hereafter, the closest beam is considered the first beam and is denoted asand the other one is considered the second beam and is denoted as. The pointing angles of each NB could be stored in the BS102and retrieved via a simple lookup table.

In another option, the BS102could adopt spatial distance to order the child NBs. For example, the BS102first identifies the coverage region of each NB over the ground, and then determines the distance between the previous NB and child NBs based on their coverage regions. As a particular example, the spatial distance could be the distance between the centers of two coverage regions. The first child NB should be searched first since it is more likely to be the best next NB.

In yet another option, the BS102could take into account the UE movement speed624and movement direction when determining the order to search the child NBs. For example, a UE with a high speed (e.g., a car on the highway or a high-speed train) could traverse a long distance in a short time between CB measurements. Therefore, the closet NB may not be the best child NB. However, in this option, the BS102can take care of the UE movement speed while determining the threshold θ.

In still another option, the BS102could consider the typical UE mobility pattern when determining the order to search the child NBs. A UE mobility pattern can be defined by a sequence or group of best NB indices for the UE over a time duration. It can also be defined by the geographical location change of the UE over a time duration. For example, assume that a UE is moving along a road, street, or sidewalk. By examining the road/street/sidewalk in the cell, it can be determined how the NB changes as the UE moves along the road/street/sidewalk. In one approach, a UE can be dropped at all possible locations within the cell, and then the UE is permitted to perform one or more random walks within the cell. During the walk, the best NB sequence of the UEs is noted. For example, one such sequence could be [NB1, NB2, NB2, NB5, NB5, NB5, NB2, . . . ]. From these sequences, the mobility pattern of the UE can be determined.

According to one technique, the BS102could model the mobility pattern as a Markov chain. That is, given the UE is served by NB-X now, what is the probability that the UE will be served by a beam in the next time step,FIG.7illustrates an example state diagram700modeling the UE mobility pattern based on UE report history according to embodiments of the present disclosure. As shown inFIG.7, the state diagram700includes multiple beams701-704(identified as NB1 through NB4). The state diagram700shows example results of dominant mobility pattern obtained from the analysis, If the UE moves from the coverage region of a first beam701-704to a second beam701-704with relatively high chance, there is an arrow711-715pointing from the first beam701-704to the second beam701-704. Most of the arrows711-715are likely to be two-way, but one-way arrows (e.g., arrow713) are also possible, such as along a one-way road. The thickness of the arrows711-715inFIG.7can represent the occurrence chance of the transition. The narrow beams701-704with high transition probabilities could be assigned to a same parent wide beam, while the narrow beams701-704with zero or low transition probabilities could be assigned to different wide beams. InFIG.7, there is no arrow between the beams701and703, and a thick arrow711between the beams701and702. Therefore, the BS102could choose to design a hierarchical codebook where the beams701and702belong to the same parent, and the beams703and704belong to another parent.

According to another technique, the BS102could learn the mobility pattern by training a recurrent neural network (RNN), for example, a LSTM (Long Short-Term Memory) network. Given the history records of the NB, the RNN models predict the probability of the next best NB.

Turning again toFIG.6, at operation605, the BS102determines a threshold θ and measures the RSRP of the first beam. The threshold θ, under which an RSRP is considered low, is determined by additional information known by the BS102about the connected UEs and their environment. The BS102uses the threshold θ to determine whether or not to measure the second beam.

A significant issue for the BS102is determining the value of θ. If θ is set to a very high value, then both beamsandare measured, which has the potential to track the best beam better at the expense of higher overhead. If θ is set to a very low value, then the BS102only measures one beam each time, which is set as the serving beam. This reduces the overhead, but at the expense of a higher probability of not selecting the best beam. Furthermore, a fixed θ does not ensure an optimal performance for all users. Some users might benefit from a large θ, while others might benefit from a low θ.

Apart from the two trivial cases just mentioned (very high and very low values of θ), the objective of the BS102is to dynamically calculate the threshold θ based on some or all of the information available at the BS102. For example, the BS102can determine the threshold θ using any one or more of the following: the serving distance621between the BS102and the UE, the current CB622, the previous NB and CB623used to serve the UE and their measured RSRP, the UE speed624, the beam width625of the current best CB, and the LOS/NLOS status626of the UE's link. This can be represented as a function given by:

θ=F( . . . ),where F( . . . ) is a predetermined function that takes into account one or more of {the serving distance621, the current CB622, the previous NB and CB623and their measured RSRP, the UE speed624, the beam width625, and the LOS/NLOS status626} to determine the current threshold. The effect of some of these parameters on the threshold θ is as follows:-Serving distance621: The larger the serving distance between the BS102and the UE the lower the chance that the UE has moved outside the realm of its previous narrow beam, which means that the chance that the closest NB is the best beam is higher. Hence, the larger the serving distance, the lower the threshold θ.-Current CB622: The higher the RSRP of the current CB, the higher the threshold θ.-Previous NB623: The higher the RSRP of the previous NB, the higher the threshold θ.-UE speed624: The higher the UE speed, the higher the chance that the closest NB is not the best beam. Hence, the threshold θ is expected to be higher for high UE speeds.-Beam width625: The larger the beam width of the current CB, the higher the chance that the closest NB is in fact the best NB, since the other beam is reasonably far from the previous NB. Hence, the higher the beam width, the lower the threshold θ.-LOS/NLOS status626: If the UE's link switches from LOS to NLOS or from NLOS to LOS, then there is a high chance that the closest beam is not the optimal one, since this transition can lead to a big change in the angle-of-arrival. Hence, a transition like this yields a high value of the threshold θ. If the UE's link was LOS and is still LOS, then it is highly likely that the closest beam is the optimal beam since it means that no significant changes in the environment happen, and hence, the threshold θ is expected to be low. If the UE's link was NLOS and is still NLOS, then there is no guarantee that a major change happened in the environment and no guarantee that the environment remained the same. In such a case, there may not be enough information to increase or decrease the threshold θ, so the threshold θ can be kept the same as in the previous time slot.-UE receiving beam: If the BS detects a change in the UE receiving beam, then the closest beam has a lower probability of being the optimal beam. Hence, searching all the child beams can be beneficial in this case, i.e., a high threshold θ can be used.

The most generic form of F( . . . ) is given next.

Another option is to include an indicator for a change in the UE receiving beam, which if triggered, a full search is performed. Other simpler forms of F( . . . ) are also possible depending on the information available to the BS102.

Once the BS102determines the threshold θ and measures the RSRP of the first beamat operation605, then at operation607, the BS102determines if the RSRP of the first beamis greater than the threshold θ. If the RSRP of the first beamis greater than the threshold θ, then at operation609, the BS102sets the first beamas the serving beam. Alternatively, if the RSRP of the first beamis not greater than the threshold θ, then at operation611, the BS102measures the RSRP of the second beam. Then, at operation613, the BS102determines if the RSRP of the first beamis greater than the RSRP of the second beam. If so, then at operation609, the BS102sets the first beamas the serving beam. If not, then at operation615, the BS102sets the second beamas the serving beam.

FIG.8illustrates another example process800for composite beam operation and overhead reduction according to embodiments of the present disclosure. For ease of explanation, the process800will be described as performed by the BS102ofFIG.1; however, the process800could be performed by any other suitable device or system. The embodiment of the process800shown inFIG.8is for illustration only. Other embodiments of the process800could be used without departing from the scope of this disclosure.

The process800can be useful in implementations where the BS102has limited information about the UE, such as its speed, serving distance, and the like. Hence, the process800differs from the process600in that the process800only relies on the BS CB codebook and the available RSRP measurements. In other words, all the inputs needed to find the beam ordering and thresholding are based on the RSRP measurements and properties of the beam codebook itself; additional information about the served UEs is not required.

As shown inFIG.8, some of the operations of the process800are the same as, or similar to, corresponding operations in the process600. However, the procedure to determine the threshold θ is different in the process800as compared to the process600.

At operation801, the BS102determines the child NBs of the current CB622. In this example, there are two child NBs, which are denoted as N0and N1. At operation803, the BS102determines an order for the child NBs N0and N1, and denotes the first beam asand denotes the second beam as. The ordering of the child NBs in operation803can be based on the distance between the NBs, such as in operation603. At operation804, the BS102measures the RSRP of the first beam.

At operation805, the BS102determines the threshold θ. The threshold θ is determined based on the RSRP of the current CB622. In other words, when the best CB is determined, the threshold θ is found based on the RSRP of that CB, such as by the following:

θ=RSRP(CB)−{tilde over (θ)},where the RSRP value is in dB scale, and {tilde over (θ)} is a tunable parameter. Hence, if the RSRP of the current NB is high, the threshold is set to a high value. An example value of {tilde over (θ)} is 3 dB. This value is based on the observation that if the CB is formed as the sum of two NBs, the best NB should have an RSRP at least half of the RSRP of the CB. Similar reasoning can be applied to the case of >2 NBs per CB. However, this option works best when each NB is formed from a separate subarray, i.e., the RSRP of a CB is equal to the sum of its child NBs, meaning than the CB has an RSRP at least as good as the best NB. This reasoning is not valid for the case of a single array case, since the CB RSRP could be smaller than the NB RSRP of the best NB, i.e., all the energy is focused in a narrower region.

Once the BS102measures the RSRP of the first beamat operation804and determines the threshold θ at operation805, then at operation807, the BS102determines if the RSRP of the first beamis greater than the threshold θ. If the RSRP of the first beamis greater than the threshold θ, then at operation809, the BS102sets the first beamas the serving beam. Alternatively, if the RSRP of the first beamis not greater than the threshold θ, then at operation811, the BS102measures the RSRP of the second beam. Then, at operation813, the BS102determines if the RSRP of the first beamis greater than the RSRP of the second beam. If so, then at operation809, the BS102sets the first beamas the serving beam. If not, then at operation815, the BS102sets the second beamas the serving beam.

FIG.9illustrates another example process900for composite beam operation and overhead reduction according to embodiments of the present disclosure. For ease of explanation, the process900will be described as performed by the BS102ofFIG.1; however, the process900could be performed by any other suitable device or system. The embodiment of the process900shown inFIG.9is for illustration only. Other embodiments of the process900could be used without departing from the scope of this disclosure.

Like the process800, the process900can be useful in implementations where the BS102has limited information about the UE, such as its speed, serving distance, and the like. Hence, the process900differs from the process600in that the process900only relies on the BS CB codebook and the available RSRP measurements. In other words, all the inputs needed to find the beam ordering and thresholding are based on the RSRP measurements and properties of the beam codebook itself; additional information about the served UEs is not required.

As shown inFIG.9, some of the operations of the process900are the same as, or similar to, corresponding operations in the process800. However, the procedure to determine the threshold θ is different in the process900as compared to the process800.

At operation901, the BS102determines the child NBs of the current CB622. In this example, there are two child NBs, which are denoted as N0and N1. At operation903, the BS102determines an order for the child NBs N0and N1, and denotes the first beam asand denotes the second beam as. The ordering of the child NBs in operation903can be based on the distance between the NBs, such as in operation603. At operation904, the BS102measures the RSRP of the first beam.

At operation905, the BS102determines the threshold θ. Different from the process800, in operation905, only the beam width of the current CB and the RSRP of the previous NB are used in determining the threshold θ:

θ=RSRP⁡(NBt-1)+α4Beam⁢Widthwhere α4is a design parameter that can be predetermined as discussed above for α1, α2, α3. This option works for the single array case as well as the subarrays case discussed above.

Once the BS102measures the RSRP of the first beamat operation904and determines the threshold θ at operation905, then at operation907, the BS102determines if the RSRP of the first beamis greater than the threshold θ. If the RSRP of the first beamis greater than the threshold θ, then at operation909, the BS102sets the first beamas the serving beam. Alternatively, if the RSRP of the first beamis not greater than the threshold θ, then at operation911, the BS102measures the RSRP of the second beam. Then, at operation913, the BS102determines if the RSRP of the first beamis greater than the RSRP of the second beam. If so, then at operation909, the BS102sets the first beamas the serving beam. If not, then at operation915, the BS102sets the second beamas the serving beam.

FIG.10illustrates yet another example process1000for composite beam operation and overhead reduction according to embodiments of the present disclosure. For ease of explanation, the process1000will be described as performed by the BS102ofFIG.1; however, the process1000could be performed by any other suitable device or system. The embodiment of the process1000shown inFIG.10is for illustration only. Other embodiments of the process1000could be used without departing from the scope of this disclosure.

Like the processes800and900, the process1000can be useful in implementations where the BS102has limited information about the UE, such as its speed, serving distance, and the like. Hence, the process1000differs from the process600in that the process1000only relies on the BS CB codebook and the available RSRP measurements. The process1000also considers the case where pairing the NBs into CBs is done in a way such that all the CBs have roughly the same beam width. In this case, a fixed threshold θ could be sufficient, since the F function is identical for the different CBs.

As shown inFIG.10, some of the operations of the process1000are the same as, or similar to, corresponding operations in the process800. However, the procedure to determine the threshold θ is different in the process1000as compared to the process800.

At operation1001, the BS102determines the child NBs of the current CB622. In this example, there are two child NBs, which are denoted as N0and N1. At operation1003, the BS102determines an order for the child NBs N0and N1, and denotes the first beam asand denotes the second beam as. The ordering of the child NBs in operation1003can be based on the distance between the NBs, such as in operation603. At operation1004, the BS102measures the RSRP of the first beam.

At operation1005, rather than calculating the threshold θ, the BS102receives or obtains a predetermined threshold θ as an input. In some embodiments, the threshold θ could be (i) the previous RSRP of the serving NB in the previous time slot, (ii) the required RSRP to support UE data rate requirement, (iii) the average RSRP of the serving NB over a time interval (for example, the previous second or the previous minute), or any other suitable threshold value.

Once the BS102measures the RSRP of the first beamat operation1004and obtains the threshold θ at operation1005, then at operation1007. the BS102determines if the RSRP of the first beamis greater than the threshold θ. If the RSRP of the first beamis greater than the threshold θ, then at operation1009, the BS102sets the first beamas the serving beam. Alternatively, if the RSRP of the first beamis not greater than the threshold θ, then at operation1011, the BS102measures the RSRP of the second beam. Then, at operation1013, the BS102. determines if the RSRP of the first beamis greater than the RSRP of the second beam. If so, then at operation1009, the BS102sets the first beamas the serving beam. If not, then at operation1015, the BS102sets the second beamas the serving beam.

AlthoughFIGS.6through10illustrate various processes and details related to composite beam operation and overhead reduction, various changes may be made toFIGS.6through10. For example, various components inFIGS.6through10could be combined, further subdivided, or omitted and additional components could be added according to particular needs. In addition, various operations inFIGS.6through10could overlap, occur in parallel, occur in a different order, or occur any number of times.

FIG.11illustrates a method1100for composite beam operation and overhead reduction according to embodiments of the present disclosure, as may be performed by one or more components of the network100(e.g., the BS102). The embodiment of the method1100shown inFIG.11is for illustration only. One or more of the components illustrated inFIG.11can be implemented in specialized circuitry configured to perform the noted functions or one or more of the components can be implemented by one or more processors executing instructions to perform the noted functions.

As illustrated inFIG.11, the method1100begins at step1101. At step1101, a BS identifies child beams of a current composite beam. This could include, for example, the BS102identifying the child beams N0and N1of a current composite beam, such as by performing operations601,801,901, or1001.

At step1103, the BS determines an order at which the child beams of the current composite beam are measured based on a likelihood that each child beam of the current composite beam is an optimal beam, among the child beams, to be a serving narrow beam. This could include, for example, the BS102determining an order of the child beams N0and N1as a first beamand a second beam, such as by performing operations603,803,903, or1003.

At step1105, the BS determines a threshold for use in deciding whether to measure one or more additional child beams or select an already measured child beam when selecting the optimal beam. This could include, for example, the BS102determining or obtaining the threshold θ, such as by performing operations605,805,905, or1005.

At step1107, the BS selects the optimal beam, among the child beams, to be the serving narrow beam based on the determined order and the determined threshold. This could include, for example, the BS102setting the first beamor the second beamas the serving beam, such as by performing some of the operations607-615,807-815,907-915, or1007-1015.

AlthoughFIG.11illustrates one example of a method1100for composite beam operation and overhead reduction, various changes may be made toFIG.11. For example, while shown as a series of steps, various steps inFIG.11could overlap, occur in parallel, occur in a different order, or occur any number of times.