PATENT DOCUMENT

Publication Number: US-10707929-B2
Application Number: US-201515756991-A
Country: US
Kind Code: B2

Title: Methods of processing signals, apparatus, and base station

Abstract:
A method of processing signals in a radio processing apparatus of a base station may include obtaining a plurality of aggregated data symbols, wherein each of the plurality of aggregated data symbols corresponds to a receive terminal of a plurality of receive terminals of the base station and is composed of transmitted data symbols from a plurality of transmit terminals; applying a compression filter to the plurality of aggregated data symbols to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals; and transmitting the plurality of isolated data symbols to a baseband processing apparatus of the base station.

Claims:
What is claimed is: 
     
       1. An apparatus for processing radio frequency signals in a base station, the apparatus comprising:
 a pre-processing circuit configured to obtain a plurality of aggregated data symbols, wherein each of the plurality of aggregated data symbols corresponds to a receive terminal of a plurality of receive terminals of the base station and is composed of transmitted data symbols from a plurality of transmit terminals; and 
 a compression processing circuit configured to:
 apply a compression filter, received from a baseband processing apparatus in communication with the compression processing circuit, to the plurality of aggregated data symbols to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals; and 
 transmit the plurality of isolated data symbols to a baseband processing apparatus of the base station. 
 
 
     
     
       2. The apparatus of  claim 1 , wherein the compression processing circuit is further configured to receive the compression filter from the baseband processing apparatus in a compressed form. 
     
     
       3. The apparatus of  claim 1 , wherein the compression processing circuit is configured to calculate the compression filter by:
 calculating a plurality of channel response estimates based on a plurality of reference symbols corresponding to the plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals; and 
 calculating the compression filter based on the plurality of channel response estimates. 
 
     
     
       4. The apparatus of  claim 3 , wherein the plurality of reference symbols comprise demodulation reference symbols (DMRS). 
     
     
       5. The apparatus of  claim 1 , wherein the compression processing circuit is configured to calculate the compression filter. 
     
     
       6. The apparatus of  claim 1 , wherein the number of aggregated data symbols of the plurality of data symbols is greater than the number of isolated data symbols of the plurality of isolated data symbols. 
     
     
       7. The apparatus of  claim 6 , wherein the number of aggregated data symbols of the plurality of data symbols is correlated with the number of receive terminals of the plurality of receive terminals, and wherein the number of isolated data symbols of the plurality of isolated data symbols is correlated with the number of transmit terminals of the plurality of transmit terminals. 
     
     
       8. The apparatus of  claim 1 , wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     
     
       9. The apparatus of  claim 1 , wherein the apparatus is a remote radio unit (RRU) and the baseband processing apparatus is a baseband unit (BBU). 
     
     
       10. The apparatus of  claim 1 , wherein the apparatus and the baseband processing apparatus are connected by an interconnection data link, and wherein the transmitting the plurality of isolated data symbols to the baseband processing apparatus comprises transmitting the plurality of isolated data symbols over the interconnection data link. 
     
     
       11. A base station comprising:
 a plurality of receive antennas; 
 baseband processing circuitry, configured to calculate a compression filter; 
 radio processing circuitry; and 
 a data link between the radio processing circuitry and the baseband processing circuitry, 
 wherein the radio processing circuitry is configured to:
 receive a plurality of aggregated data symbols from the plurality of receive antennas, wherein each of the plurality of aggregated data symbols is composed of transmitted data symbols from a plurality of transmit terminals and corresponds to an antenna of the plurality of antennas; 
 apply the compression filter, received from the baseband processing circuitry over the data link, to the plurality of aggregated data symbols to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive antennas and the plurality of transmit terminals; and 
 transmit the plurality of isolated data symbols to the baseband processing circuitry over the data link. 
 
 
     
     
       12. The base station of  claim 11 , wherein the baseband processing circuitry is configured to perform symbol detection on the plurality of isolated data symbols to generate plurality of detected data symbols. 
     
     
       13. The base station of  claim 11 , wherein the radio processing circuitry is configured to calculate the compression filter by:
 calculating a plurality of channel response estimates based on a plurality of reference symbols corresponding to the plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals; and 
 calculating the compression filter based on the plurality of channel response estimates. 
 
     
     
       14. The base station of  claim 13 , wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     
     
       15. The base station of  claim 11 , wherein the baseband processing circuitry is configured to calculate the compression filter by calculating a plurality of channel response estimates based on the plurality of reference symbols, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals. 
     
     
       16. The base station of  claim 11 , wherein the data link comprises an interconnection data link. 
     
     
       17. The base station of  claim 11 , wherein the number of aggregated data symbols of the plurality of data symbols is greater than the number of isolated data symbols of the plurality of isolated data symbols. 
     
     
       18. An apparatus for processing baseband frequency signals in a base station, the apparatus having one or more digital processing circuits, wherein the apparatus is configured to:
 calculate a plurality of channel response estimates based on a plurality of reference symbols associated with a plurality of transmit terminals, each of the plurality of channel response estimates approximating a wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of a plurality of receive terminals of the base station; 
 calculate a compression filter based on the plurality of channel response estimates; 
 transmit the compression filter to a radio processing apparatus of the base station; 
 receive a plurality of received data symbols from the radio processing apparatus; and 
 perform symbol detection of the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols. 
 
     
     
       19. The apparatus of  claim 18 , configured to calculate the compression filter based on the plurality of channel response estimates by:
 calculating the compression filter based on the plurality of channel response estimates and a plurality of additional channel response estimates. 
 
     
     
       20. The apparatus of  claim 18 , wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme.

Description:
RELATED APPLICATIONS 
     The present application is a national stage entry according to 35 U.S.C. § 371 of PCT application No.: PCT/CN2015/089343 filed on Sep. 10, 2015, which is incorporated herein by reference in its entirety. 
     TECHNICAL FIELD 
     Various embodiments relate generally to methods of processing signals, apparatuses, and base stations. 
     BACKGROUND 
     Many conventional wireless communication protocols utilize Multiple Input Multiple Output (MIMO) technologies in order to increase data transmission rates and user capacity. MIMO has emerged as an important focus in Third Generation Partnership (3GPP) mobile communication standards, in particular recent 3GPP Releases for Long Term Evolution (LTE) network configurations which have provided for the use of 2, 4, or 8 antennas. 
     Large scale MIMO, which may involve more than 8 antennas, has similarly become a focus for next generation wireless communication protocols. Such large scale MIMO systems may deploy 32 or even 64 antennas to acquire further spatial multiplexing and beamforming gain. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the drawings, like reference characters generally refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead generally being placed upon illustrating the principles of the invention. In the following description, various embodiments of the invention are described with reference to the following drawings, in which: 
         FIG. 1  shows a mobile communication network; 
         FIG. 2  shows the mobile communication network of  FIG. 1  in further detail; 
         FIG. 3  shows an internal architecture of base station according to an exemplary aspect of the disclosure; 
         FIGS. 4A-4C  show several charts illustrating Discrete Cosine Transform (DCT) truncation; 
         FIG. 5  shows an internal architecture of base station according to a further exemplary aspect of the disclosure; 
         FIG. 6  shows an internal architecture of a baseband processing apparatus according to an exemplary aspect of the disclosure; 
         FIG. 7  shows a method of processing signals at a radio processing apparatus of a base station; 
         FIG. 8  shows a method of transmitting data between a radio processing apparatus and a baseband processing apparatus of a base station; and 
         FIG. 9  shows a method of processing signals at a baseband processing apparatus configured to be implemented in a base station. 
     
    
    
     DESCRIPTION 
     The following details description refers to the accompanying drawings that show, by way of illustration, specific details and embodiments in which the invention may be practiced. 
     The word “exemplary” is used herein to mean “serving as an example, instance, or illustration”. Any embodiment or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments or designs. 
     The words “plural” and “multiple” in the description and the claims, if any, are used to expressly refer to a quantity greater than one. Accordingly, any phrases explicitly invoking the aforementioned words (e.g. “a plurality of [objects]”, “multiple [objects]”) referring to a quantity of objects is intended to expressly refer more than one of the said objects. The terms “group”, “set”, “collection”, “series”, “sequence”, “grouping”, “selection”, etc., and the like in the description and in the claims, if any, are used to refer to a quantity equal to or greater than one, i.e. one or more. Accordingly, the phrases “a group of [objects]”, “a set of [objects]”, “a collection of [objects]”, “a series of [objects]”, “a sequence of [objects]”, “a grouping of [objects]”, “a selection of [objects]”, “[object] group”, “[object] set”, “[object] collection”, “[object] series”, “[object] sequence”, “[object] grouping”, “[object] selection”, etc., used herein in relation to a quantity of objects is intended to refer to a quantity of one or more of said objects. It is appreciated that unless directly referred to with an explicitly stated plural quantity (e.g. “two [objects]” “three of the [objects]”, “ten or more [objects]”, “at least four [objects]”, etc.) or express use of the words “plural”, “multiple”, or similar phrases, references to quantities of objects are intended to refer to one or more of said objects. 
     It is appreciated that any vector and/or matrix notation utilized herein is exemplary in nature and is employed solely for purposes of explanation. Accordingly, it is understood that the approaches detailed in this disclosure are not limited to being implemented solely using vectors and/or matrices, and that the associated processes and computations may be equivalently performed with respect to sets, sequences, groups, etc., of data, observations, information, signals, etc. 
     Furthermore, it is appreciated that references to a “vector” may refer to a vector of any size or orientation, e.g. including a 1×1 vector (e.g. a scalar), a 1×M vector (e.g. a row vector), and an M×1 vector (e.g. a column vector). Similarly, it is appreciated that references to a “matrix” may refer to matrix of any size or orientation, e.g. including a 1×1 matrix (e.g. a scalar), a NM matrix (e.g. a row vector), and an M×1 matrix (e.g. a column vector). 
     As used herein, a “circuit” is understood as any kind of a logic implementing entity, which may be special purpose circuitry or a processor executing software stored in a memory, firmware, or any combination thereof. Furthermore, a “circuit” may be a hard-wired logic circuit or a programmable logic circuit such as a programmable processor, for example a microprocessor (for example a Complex Instruction Set Computer (CISC) processor or a Reduced Instruction Set Computer (RISC) processor). A “circuit” may also be a processor executing software, for example any kind of computer program, for example a computer program using a virtual machine code such as for example Java. Any other kind of implementation of the respective functions which will be described in more detail below may also be understood as a “circuit”. It may also be understood that any two (or more) of the described circuits may be combined into one circuit. In particular with respect to the use of “circuitry” in the claims included herein, the use of “circuit” (including “processing circuit”) may be understood as collectively referring to two or more circuits. 
     As used herein, “memory” may be understood as an electrical component in which data or information can be stored for retrieval. References to “memory” included herein may thus be understood as referring to volatile or non-volatile memory, including random access memory (RAM), read-only memory (ROM), flash memory, solid-state storage, magnetic tape, hard disk drive, optical drive, etc. Furthermore, it is appreciated that registers, shift registers, processor registers, data buffers, etc., are also embraced herein by the “term” memory. It is appreciated that a single component referred to as “memory” or “a memory” may be composed of more than one different type of memory, and thus may refer to a collective component comprising one or more types of memory. It is readily understood that any single memory “component” may be distributed or/separated multiple substantially equivalent memory components, and vice versa. Furthermore, it is appreciated that while “memory” may be depicted, such as in the drawings, as separate from one or more other components, it is understood that memory may be integrated within another component, such as on a common integrated chip. 
     Similarly, a “processing circuit” (or equivalently “processing circuitry”) is understood as referring to any circuit that performs processing, such as e.g. any circuit that performs processing on an electrical or optical signal. A processing circuit may thus refer to any analog or digital circuitry that alters a characteristic or property of an electrical or optical signal. A processing circuit may thus refer to an analog circuit, digital circuit, logic circuit, processor, microprocessor, Central Processing Unit (CPU), Graphics Processing Unit (GPU), Digital Signal Processor (DSP), Field Programmable Gate Array (FPGA), integrated circuit, or Application Specific Integrated Circuit (ASIC). Accordingly, a processing circuit may refer to a circuit that performs processing on an electrical or optical signal as hardware or as software, such as software executed on hardware. Furthermore, it is understood that a single a processing circuit may be equivalently split into two separate processing circuits, and conversely that two separate processing circuits may be combined into a single equivalent processing circuit. 
     The term “base station” used in reference to an access point of a mobile communication network may be understood as a macro base station, micro base station, Node B, evolved NodeBs (eNB), Home eNodeB, Remote Radio Head (RRHs), relay point, etc. 
     As used herein, a “cell” in the context of telecommunications may be understood as a sector served by a base station. Accordingly, a cell may be a set of geographically co-located antennas that correspond to a particular sectorization of a base station. A base station may thus serve one or more “cells” (or sectors), where each cell is characterized by a distinct communication channel. 
     It is appreciated that the ensuing description may detail exemplary scenarios involving mobile device operating according to certain 3GPP (Third Generation Partnership Project) specifications, notably Long Term Evolution (LTE) and Long Term Evolution-Advanced (LTE-A). It is understood that such exemplary scenarios are demonstrative in nature, and accordingly may be similarly applied to other mobile communication technologies and standards, such as WLAN (wireless local area network), WiFi, UMTS (Universal Mobile Telecommunications System), GSM (Global System for Mobile Communications), Bluetooth, CDMA (Code Division Multiple Access), Wideband CDMA (W-CDMA), etc. The examples provided herein are thus understood as being applicable to various other mobile communication technologies, both existing and not yet formulated, particularly in cases where such mobile communication technologies share similar features as disclosed regarding the following examples. 
     The term “network” as utilized herein, e.g. in reference to a communication network such as a mobile communication network, is intended to encompass both an access component of a network (e.g. a radio access network (RAN) component) and a core component of a network (e.g. a core network component). 
     As utilized herein, the term “idle mode” used in reference to a mobile terminal refers to a radio control state in which the mobile terminal is not allocated at least one dedicated communication channel of a mobile communication network. The term “connected mode” used in reference to a mobile terminal refers to a radio control state in which the mobile terminal is allocated at least one dedicated communication channel of a mobile communication network. 
     Unless explicitly specified, the terms “transmit” and “send” encompass both direct and indirect transmission/sending. Similarly, the term “receive” encompasses both direct and indirect reception unless explicitly specified. 
     Large scale Multiple Input Multiple Output (MIMO) (or “massive” MIMO) may be implemented into mobile communication technologies in order to increase spatial multiplexing and beamforming gain. While conventional mobile communication protocols, such as Long Term Evolution (LTE) standards as specified by the Third Generation Partnership Project (3GPP), may conventionally utilize e.g. 2, 4, or 8 layer MIMO systems to support wireless communications, large scale MIMO architectures may expand to e.g. 32 or 64 layers. As spatial antenna diversity is a key component in MIMO systems, large scale MIMO architectures may involve upwards of 32 transmission and/or reception antennas. 
     As each antenna (or each set of combined antennas if combination of physical antennas is performed) may produce an independent data stream, massive MIMO schemes may need to support data transport of each individual data stream until symbol detection is performed to recover the original transmitted symbols. Massive MIMO schemes having 32 or more antennas may thus need to capable of supporting 32 or more individual data streams, and thus may need to support high data throughput levels. 
     In a mobile communication application, base stations that are part of uplink massive MIMO schemes may need to transport large quantities of data from the receive antennas to various upstream processing components until symbol detection is performed to recover the data symbols transmitted by each user terminal. Several different base station architectures may be realized in order to support massive MIMO schemes. In particular, both “thick” and “thin” base station architectures, where each architecture may offer specific advantages and disadvantages. 
     Base stations may conventionally be composed of a Remote Radio Unit (RRU) component and a Baseband Unit (BBU) component, where a BBU may serve multiple RRUs. BBUs may perform baseband processing of mobile communication signals, and may provide or receive digital mobile communication signals to or from one or more RRUs. RRUs may be responsible for radio frequency processing of mobile communication signals, and may include digital as well as analog circuitry in order to receive and perform initial processing on wireless radio frequency signals. A BBU may exchange digital mobile communication data with one or more RRUs over an optical fiber or similar high-speed connection, such as using a Common Public Radio Interface (CPRI) standard over an optical fiber data link. 
     In the aforementioned “thick” base station architecture, a BBU may be integrated into the same equipment (i.e. at the same physical location) as the RRU. As an RRU typically processes mobile communication data at a remote location (e.g. in close proximity to the base station antennas), thick base station architectures may demand similar remote placement of a BBU. However, remote placement of BBUs may inhibit many of the advantages of Coordinated Multipoint (CoMP), Inter-cell Interference Coordination (ICIC), and Carrier Aggregation (CA), which may rely on central location of multipole BBUs in centralized BBU pools in order to allow straightforward data sharing with other BBUS and/or RRUs. The lack of centralized BBU pools in “thick” architectures may generally result in reduced efficiency. Furthermore, the RRU-BBU integration employed in thick base station architectures may consume additional space and/or energy, which may in turn increase operation and maintenance costs. 
     Alternatively, “thin” base station architectures, which deploy only basic radio processing at remotely-located RRUs while maintaining centralized placement of BBUs, may resolve many of the aforementioned problems associated with thick base station architectures. As the RRUs only supports basic radio operations, much of the complex signal processing is tasked to centrally located BBUs, thereby allowing for relatively simple baseband information exchange and reductions in both RRU power and spatial usage. However, the interface between the RRU and BBU must be capable of handling large data streams, as data must be exchanged between the isolated locations of the RRU and BBU. As previously indicated, the data link between RRU and BBU may be required to support transmission of independent data streams each corresponding to a different receive antenna. 
     While the resulting data throughput levels in conventional MIMO schemes (i.e. ≤8 layers) may be relatively manageable, massive MIMO may substantially increase the link burden between the RRU and BBU. For example, a 20 MHz LTE uplink MIMO scheme with 64 antennas may require a data rate exceeding 30 GBps, which may be unreasonable for many existing base station configurations. The data link between RRU and BBU may thus present a significant barrier in realization of effective massive MIMO schemes. 
     Accordingly, the link burden issues of thin base station architectures in uplink MIMO paths (i.e. from RRU to BBU) may alleviated by effectively compressing data received at the RRU (e.g. from multiple user terminals) and subsequently transmitting the compressed data to the BBU over the RRU-BBU uplink interface. As opposed to transmitting independent data streams each corresponding to a respective receive antenna, the RRU may compress the data streams into essentially one per user and transmit the resulting reduced data streams to the BBU. As will be detailed herein, the RRU may utilize a channel estimation-based compression filter to efficiently compress the data before transmission to the BBU, thereby substantially reducing data throughput requirements. In certain advantageous aspects of the disclosure, the compression may be lossless and thus may not result in any performance degradation. 
       FIG. 1  shows mobile communication network  100 . Mobile communication network  100  may include at least base station  102  and user equipment (UEs) UE 1 -UE K , where K denotes the number of UEs participating in an uplink MIMO scheme (i.e. the number of layers in the MIMO scheme). UE 1 -UE K  may each be in an active radio connection state with base station  102 , and accordingly may each be allocated uplink wireless resources to transmit uplink data to base station  102 . 
     Base station  102  may operate according to an uplink MIMO scheme. Accordingly, UE 1 -UE K  may each utilize the same time-frequency wireless uplink resource to transmit uplink data intended for base station  100 .  FIG. 1  shows uplink resource grids  104 - 112 , which each illustrate uplink resources divided onto a time (horizontal axis) and frequency (vertical axis) grid. 
     UE 1 -UE K  may each transmit a stream of uplink data to base station  102 . Each of UE 1 -UE K  may transmit the respective uplink data stream by distributing the uplink data into discrete data symbols, where each data symbol is composed of one or more logical bits representing part of the uplink data. UE 1 -UE K  may then transmit the resulting symbols using assigned time-frequency resources, such as by mapping each of the resulting symbols to a carrier frequency (corresponding to the horizontal rows of uplink resource grids ( 106 - 112 ) and transmitting each of the resulting symbols during a symbol period (corresponding to the vertical columns of uplink resource grids  106 - 112 ). 
     In accordance with an uplink MIMO scheme including UE 1 -UE K , each of UE 1 -UE K  may transmit data symbols utilizing the same time-frequency uplink resources as the other UEs, i.e. utilizing the same carrier frequency during the same symbol period. As shown in  FIG. 1 , UE 1 -UE K  may each transmit respective data symbols x 1 -x K  using the same carrier frequency during the same symbol period as the other UEs (symbol period and carrier frequency arbitrarily represented in  FIG. 1 ). 
     Base station  102  may therefore receive a wireless signal containing data symbols x 1 -x K  at the same carrier frequency and same symbol period (relative to base station  102 ) as shown in uplink resource grid  104 . As will be further detailed, each of data symbols x 1 -x K  received at base station  102  may be modified by the wireless channels according to channel responses h 1 -h K  between each of UE 1 -UE K  and base station  102 , where each channel response h k , k={1, 2, . . . , K} denotes the wireless channel response between UE k  and each antenna Ant 1 -Ant NRX  of base station  102 . It is understood that for purposes of simplicity, the following description of base station  102  may refer to as N RX  as the number of physical receive antennas at base station  102 . However, as will be later described, N RX  may alternatively refer to the number of separate data streams obtained from an antenna array having a quantity of physical antennas greater than or equal to N RX , where one or more of the antennas in the antenna array may undergo analog combination to produce N RX  total data streams. 
     As UE 1 -UE K  may each respectively transmit data symbols x 1 -x K  using the same wireless resources (i.e. same time-frequency resource), base station  104  may need to process wirelessly received signals in order to recover each of data symbols x 1 -x K . Base station  102  may rely on spatial antenna diversity and reference signals transmitted by each of UE 1 -UE K  in order to recover data symbols x 1 -x K . Despite the additional requisite processing, such an uplink MIMO scheme may conserve wireless resources as compared to single input and single output schemes, which may involve using different wireless resources for each transmitting user terminal. 
     Base station  102  may include an antenna array including a plurality of antennas, Ant 1 -Ant NRX , where each antenna exhibits spatial diversity with the other antennas. Base station  102  may utilize the resulting spatial diversity in order to recover each data symbol x k  transmitted by each of UE 1 -UE K . As shown in further detail in  FIG. 2  (only one UE of UE 1 -UE K  explicitly shown), each antenna Ant i , i={1, 2, . . . , N RX }, may therefore receive a composite wireless signal composed of individual contributions from each of UE 1 -UE K . For example, each Ant i  may receive a wireless signal given as h i,1 x 1 +h i,2 x 2 +h i,3 x 3 + . . . +h i,4 x 4 , where h i,k  indicates the channel response between UE 1  and Ant k . As denoted in  FIG. 2 , the channel response vector h k  may denote the channel response between UE k  and each antenna Ant 1 -Ant NRX , i.e. h k =[h 1,k , h 2,k , . . . , h N     RX     ,k ,] T  (where the superscript A T  for arbitrary matrix A denotes the transpose of matrix A). 
     Base station  102  may therefore receive data symbol vector y composed of N RX  total data symbols (one for each antenna Ant 1 -Ant NRX ) for the assigned common wireless resource used for data symbols x 1 -x K , where y is given as follows: 
                     y   =         ∑     k   =   1     K     ⁢     y   k       =       ∑     k   =   1     K     ⁢       h   k     ⁢     x   k             ,           (   1   )               
where the i th  horizontal row of y denotes the wireless signal received by Ant i  as referenced above.
 
     As previously indicated, base station  102  may exploit the spatial diversity between Ant 1 -Ant NRX  to recover data symbols x 1 -x K  (forming data symbol vector x=[x 1 , x 2 , . . . , x K ] T ) using reference symbols transmitted by each of UE 1 -UE K . UE 1 -UE K  may distribute such reference symbols within the data stream transmitted by each UE. As the reference symbols may be predefined, base station  102  may utilize the reference symbols in order to derive channel estimates for UE 1 -UE K , i.e. to derive a channel response estimate vector h k  for each UE k . Base station  102  may then apply each h k  to the received symbols y to recover data symbols x 1 -x K . For example, base station  102  may solve y=Hx for H (or an estimate thereof) in order to recover x from y, where H=[h 1 , h 2 , . . . , h K ] T . 
     It is appreciated that while the scenario detailed above has relied on an assumption that each data symbol x 1 -x K  originates from a different UE, it may be equally applicable that multiple of data symbols x 1 -x K  originate from the same UE (i.e. using separate transmitting antennas at the UE), such as in Single User MIMO (SU-MIMO). Such variations are accordingly also embraced herein. 
     By deriving channel response estimates Ĥ and applying to Ĥ to received symbols y, base station  102  may derive K data symbols x 1 -x K  from the N RX  data symbols y 1 -y N     RX    originally received at each of Ant 1 -Ant NRX . For example, base station  102  may apply H using minimum mean squares estimation (MMSE) symbol detection to recover x 1 -x K  from y. As such uplink MIMO schemes may be executed over extended periods of time (with time wireless resources increasing in time and specific frequency resources shared by UE 1 -UE K  potentially changing), base station  102  may receive a constant stream of data symbols over time. Base station  102  may thus constantly perform data recovery on each set of N RX  received data symbols y at a given time t to recover the original K data symbols x 1 -x K  transmitted by each of UE 1 -UE K . 
     The channel estimation procedures for uplink MIMO data recovery may be implemented in a BBU, which may perform symbol detection using the estimated channel matrix Ĥ in order to recover data symbol estimate {circumflex over (x)} while accounting for noise and other interference. The RRU may thus be conventionally tasked with generating the N RX  data streams of y (by wireless reception with Ant 1 -Ant NRX , digitalization, and other pre-processing) and transmitting the corresponding data to the BBU over the RRU-BBU interconnection link. The amount of data transmitted between the RRU and BBU may thus be proportional to N RX , as the RRU may transmit data corresponding to each of the N RX  antennas Ant 1 -Ant NRX . 
     However, in an advantageous aspect of the disclosure, the RRU may apply a compression filter based on channel estimates in order to reduce the amount of data from N RX  proportions to K proportions. As previously detailed, base station  102  may perform data recovery in order to derive K data symbols (i.e. one per user/layer) from N RX  total received data symbols (i.e. one per antenna) based on channel estimates Ĥ. Accordingly, the RRU may apply a compression filter similarly based on channel estimation in order to compress the N RX  data streams at the RRU into K data streams, and subsequently transmit the K data streams over the RRU-BBU interconnection link. As many such MIMO schemes may use more receive antennas than users/layers, i.e. N RX &gt;K (where N RX  must satisfy N RX ≥K for data recovery), such a compression may allow for drastic reduction requirements in data throughput for the RRU-BBU interconnection link. This reduction may be critical for MIMO schemes utilizing upwards of 32 antennas, as N RX ≥32 may result in unrealizable data throughput. Thin base station architectures may therefore be implemented without the severe drawbacks of link burden in the RRU-BBU interconnection link. 
     As will be detailed, there exist several base station configurations realizing the aforementioned data compression at the RRU. In a first configuration, an RRU may calculate the compression filter locally, such as based on uplink reference signals received from UE 1 -UE k . In a second configuration, an RRU may receive an externally-calculated compression filter, such as from a BBU. The RRU may then compress the received MIMO data and transmit the resulting compressed MIMO data to the BBU. There additionally exist multiple options for compression of other related data being transmitted over the RRU-BBU interconnection link, such as compressing the compression filter before transmission from the BBU to the RRU (in the proposed configuration) or compressing reference symbols at the RRU before transmission to the BBU. 
     The following exemplary descriptions may specifically refer to mobile communication protocols, such as LTE. However, it is appreciated that these descriptions are understood to be demonstrative in nature, and may thus be applied in essentially any MIMO scheme to reduce link burden between two independently located components. Furthermore, while it is appreciated that the related channel estimations are performed using reference signals such as Demodulation Reference Signals (DMRS) and Sounding Reference Signal (SRS), it is understood that such channel estimations may be obtained as a result of other procedures, such as e.g. utilizing a similar reference point to derive a channel estimate. The connected MIMO data compression may thus be employed in a wide range of applications, such as e.g. any number of other mobile communication protocols. 
       FIG. 3  shows a block diagram illustrating an exemplary internal configuration of base station  300 . As will be detailed, base station  300  may be configured according to the first configuration introduced above. Base station  300  may include antenna array  302 , analog combiner  304 , RRU  306 , RRU-BBU interconnection link  308 , and BBU  310 . RRU  306  may implement channel estimation in order to effectively compress received uplink MIMO data, thereby reducing link burden on RRU-BBU interconnection line  308  (i.e. consistent with the first configuration). RRU  306  may therefore include AGC, ADC, &amp; FFT hardware  306   a , RB selection hardware  306   b , and CE &amp; compression hardware  306   c.    
     It is understood that the components of base station  300 , in particular RRU  306  and BBU  310  and all internal components thereof (e.g. AGC, ADC, &amp; FFT hardware  306   a , RB selection hardware  306   b , and CE &amp; compression hardware  306   c ), may be structurally implemented as hardware, software executed on hardware, or a mixture of hardware and software. Specifically, RRU  306  and BBU  310  may include one or more digital processing circuits, such as logic circuits, processors, microprocessors, Central Processing Units (CPUs), Graphics Processing Units (GPUs) (including General-Purpose Computing on GPU (GPGPU)), Digital Signal Processors (DSPs), Field Programmable Gate Arrays (FPGAs), integrated circuits, Application Specific Integrated Circuits (ASICs), or any combination thereof. It is understood that a person of skill in the art will appreciate the corresponding structure disclosed herein, be it in explicit reference to a physical structure and/or in the form of mathematical formulas, prose, flow charts, or any other manner providing sufficient structure (such as e.g. regarding an algorithm). The components of base station  300  components may be detailed herein substantially in terms of functional operation in recognition that a person of skill in the art may readily appreciate the various possible structural realizations of each component that will provide the desired functionality. 
     Base station  300  may be configured according to a thin base station architecture. In a functional realization of base station  300 , antenna array  302 , analog combiner  304 , and RRU  306  may therefore be placed at a remote location, such as at the top of a tower into which base station  300  is integrated. BBU  310  may be placed at a central location, such as in a base station cabinet. It is appreciated that BBU  310  may serve one or more further RRUs in addition to RRU  306 . 
     RRU  306  may exchange data with BBU  310  over RRU-BBU interconnection link  308 , which may be e.g. an optical fiber. While the following description may focus on the uplink path, it is understood that base station  300  may additionally be capable of operating on the downlink path. 
     Base station  300  may operate in a substantially similar uplink MIMO scenario as detailed regarding base station  102  of  FIGS. 1 and 2 . Base station  300  may receive wireless uplink signals from UE 1 -UE K  according to an uplink MIMO scheme. Base station  300  may receive wireless uplink signals using antenna array  302 . Analog combiner  304  may then combine the resulting uplink data signals, such as by combining the uplink data signals from sets of two or antennas of antenna array  302  in the analog domain. Analog combiner  304  may thus yield N RX  analog data streams (as indicated in  FIG. 3 ), which may be subsequently received by RRU  306 . N RX  may thus indicate the number of analog data streams produced by analog combiner  306 , which may be equal to or less than the actual number of physical receive antennas in antenna array  302 . 
     RRU  306  may process the analog data streams received from analog combiner  306  using processing circuitry. RRU  306  may perform automatic gain control (AGC) and analog-to-digital conversion (ADC) on the N RX  analog data streams received from analog combiner  304  and subsequently perform Fast Fourier Transform (FFT) processing in order to generate frequency domain symbols (AGC, ADC, &amp; FFT hardware  306   a ). RRU  306  may then perform resource block (RB) selection to eliminate null subcarriers in the uplink signals (RB selection hardware  306   b ). Per uplink symbol period, RRU  306  may thus obtain N RX  received uplink MIMO data symbols y (expressed herein as a vector), as previously detailed regarding  FIGS. 1 and 2  and Equation 1. 
     RRU  306  may therefore further include CE and compression hardware  306   c , which may be composed of digital processing circuitry. RRU  306  may thus require extra calculation and processing hardware, which may be utilized in order to perform channel estimation and calculate compression filters. 
     RRU  306  may then transmit resulting data to BBU  310  over RRU-BBU interconnection link  308 . BBU  310  may receive the data and perform equalization and coordinated processing. BBU  310  may be composed of processing circuitry. 
     Base station  300  may be configured according to the first configuration introduced above, where RRU  306  may be configured to locally calculate the compression filter. The operation of base station  300  may be summarized as follows:
         a. Perform channel estimation at RRU  306  on received symbol vector y to obtain estimated channel response matrix Ĥ   b. Compress received symbol at RRU  306  vector y using Ĥ to generate compressed received symbol vector y compressed  and compressed estimated channel response matrix Ĥ compressed      c. Transmit y compressed  and Ĥ compressed  (along with received SRS symbols) from RRU  306  to BBU  310  over RRU-BBU interconnection link  308     d. Perform symbol detection at BBU  310  using y compressed  and Ĥ compressed  to generate detected symbol vector {circumflex over (x)}       

     The compression performed by RRU  306  may be lossless, and thus may offer decreased link burden on RRU-BBU interconnection link  308  without performance degradation. 
     As detailed regarding  FIG. 1  and  FIG. 2 , base station  300  may implement an uplink MIMO scheme in order to receive uplink data from UE 1 -UE K  using shared uplink wireless (time and frequency) resources. UE 1 -UE K  may each transmit reference signals along with uplink traffic and control data, such as e.g. by transmitting reference signals during certain symbol periods (i.e. by multiplexing reference symbols within an uplink data stream also containing traffic and control data symbols). 
     For example, in an LTE network configuration, UE 1 -UE K  may each transmit DMRS symbols, such as by time-multiplexing DMRS symbols into an uplink data stream containing further data symbols. DMRS may then be utilized in order to wireless obtain channel estimates and recover data, as previously detailed. UE 1 -UE K  may only transmit DMRS when the UE is actively transmitting additional uplink data, such as in uplink time periods (e.g. uplink subframes) when the UE is scheduled to transmit uplink data. 
     UE 1 -UE K  may also transmit SRS, which similarly may be transmitted as reference symbols time-multiplexed with other uplink traffic and data symbols. In contrast to DMRS, UE 1 -UE K  may transmit SRS symbols during each uplink subframe, i.e. regardless if the UE is scheduled to transmit uplink data. For example, UE 1 -UE K  may transmit SRS symbols during the last symbol period of each uplink subframe. 
     In an LTE network configuration, each UE 1 -UE K  may therefore transmit DMRS and SRS symbols along with further uplink data symbols during each uplink subframe. Specifically, UE 1 -UE K  may transmit Physical Uplink Shared Channel (PUSCH) data symbols containing traffic and Physical Uplink Control Channel (PUCCH) data symbols containing control data. In the uplink MIMO schemes detailed herein, uplink MIMO may be utilized in order to multiplex at least PUSCH data symbols from each of UE 1 -UE K  onto shared wireless resources, thereby conserving wireless resources and potentially increasing uplink data rates. However, it is appreciated that the teachings detailed herein may be similarly applied to communication protocols other than LTE. Other communication protocols using MIMO based on reference symbols may be particularly applicable. 
     RRU  306  may utilize DMRS symbols received from UE 1 -UE K  in order to perform channel estimation and subsequent compression on uplink data from UE 1 -UE K . As previously detailed regarding  FIGS. 1 and 2 , the channel response characterizing the wireless channel between a given UE k  and the N RX  receive antennas may be denoted as h k =[h 1,k , h 2,k , . . . , h N     RX     ,k ,] T  (refer also to Equation 1). As the DRMS symbols transmitted by UE 1 -UE K  are predefined and time-multiplexed along with other uplink data symbols, RRU  306  may isolate the DMRS symbols and apply channel estimation processing (i.e. utilizing the predefined DMRS symbol sequences as pilot symbols to obtain attenuation and phase rotation of the DRMS symbols) in order to obtain an estimated channel response vector ĥ k =[ĥ 1,k , ĥ 2,k , . . . , ĥ N     RX     ,k ,] T  for each UE k  of UE 1 -UE K , where each element h i,k , i={1, . . . , N RX } denotes the estimated channel response between UE k  and the i th  receive antenna Ant i  of antenna array  302  (or e.g. grouped set of combined antennas in the event of analog combination at analog combiner  304 ). It is appreciated that each channel response estimate ĥ i,k  may be realized as a vector, such as a vector containing estimated channel response coefficients characterizing each associated wireless channel. 
     As previously detailed, base station  300  may receive N RX  data symbols in received data symbol vector y for each uplink MIMO symbol period, where y=Σ k=1   K =Σ k=1   K h k x k  as detailed regarding Equation 1. 
     RRU  306  may subsequently compress received data symbol vector y by applying estimated channel response vector ĥ k  to generate compressed received symbol vector y compressed , where y compressed  contains only K elements as opposed to the N RX -element y. 
     Specifically, RRU  306  may calculate the following (i.e. at Channel Estimation (CE) and compression hardware  306   c ):
 
 y   compressed =[ ĥ   1   ,ĥ   2   , . . . ,ĥ   K ] H   y   (2),
 
where A H  denotes the Hermitian transpose of A.
 
     As opposed to sending data proportional to N RX  corresponding to y during each uplink symbol period, RRU  306  may instead send data proportional to K in the form of y compressed  to BBU  310  over RRU-BBU interconnection link  308 . 
     By such compression using channel estimation within RRU  306 , the data link rate for RRU-BBU interconnection link  308  may thus be drastically reduced, in particular in massive MIMO schemes where large quantities of receive antennas (i.e. 32 or more) are used to receive uplink data from a relatively smaller quantity of users (i.e. 8 or less). 
     RRU  306  may additionally transmit a compressed estimated channel response matrix Ĥ compressed  (where y compressed =H compressed x) to BBU  310  to allow BBU  310  to perform further equalization to eliminate inter-UE interference, thereby improving final symbol detection results. As previously detailed, base station  300  may seek to recover data symbols x 1 -x K  of data symbol vector x (where x=[x 1 , x 2 , . . . , x K ] T ). Base station  300  may therefore recover a detected data symbol vector x. 
     RRU  306  may also calculate compressed estimated channel response matrix Ĥ compressed  based on DMRS symbols from UE 1 -UE K  as follows:
 
 Ĥ   compressed =[ ĥ   1   ,ĥ   2   , . . . ,ĥ   K ]×[ ĥ   1   ,ĥ   2   , . . . ,ĥ   K ]  (3).
 
     In summary, RRU  306  may determine estimated channel response matrix Ĥ based on DMRS symbols received from UE 1 -UE K , where Ĥ estimates the wireless channel response between each UE 1 -UE K  and each Ant 1 -Ant NRX . RRU  306  may then compress received data symbol vector y based on estimated channel response matrix Ĥ to generate compressed received data symbol vector y compressed . RRU  306  may similarly determine compressed estimated channel response matrix Ĥ compressed  based on estimated channel response matrix Ĥ. 
     RRU  306  may then transmit Ĥ compressed  and y compressed  to BBU  310  over RRU-BBU interconnection link  308 . As received symbol data has been reduced from dimension N RX (y) to dimension K (y compressed ), link burden on RRU-BBU interconnection link  308  is reduced. As depicted in  FIG. 3 , RRU  306  may also transmit SRS data symbols for UE 1 -UE K  to BBU  310 , which BBU  310  may utilize for channel estimation in frequency dependent scheduling. 
     BBU  310  may then recover the transmitted data symbols x corresponding to UE 1 -UE K  for a given symbol period by performing symbol detection to obtain {circumflex over (x)} using Minimum Mean Squared Error (MMSE) equalization as follows:
 
 {circumflex over (x)} =( Ĥ   compressed +σ n   2   I ) −1   y   compressed   (4),
 
where σ n   2  is the noise variance and I is the identity matrix.
 
     The compression scheme detailed thus far proves to be a lossless compression scheme, and thus achieves identical performance to non-compressed schemes. Specifically, in the non-compressed scheme, RRU  306  may transmit uncompressed received data symbol vector y to BBU  310  over RRU-BBU interconnection link  308 , where y satisfies the relationship provided in Equation 1. RRU  306  may additionally transmit DMRS and SRS data symbols for UE 1 -UE K  to BBU  310 . BBU  310  may then perform channel estimation based on DMRS symbols for UE 1 -UE K  in order to obtain estimated channel response matrix Ĥ as follows: 
     
       
         
           
             
               
                 
                   
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     BBU  310  may then apply Ĥ to recover x in the form of {circumflex over (x)} using MMSE equalization as follows:
 
 {circumflex over (x)} =( Ĥ   H   Ĥ+σ   n   2   I ) −1   Ĥy   (6).
 
     Applying the identities Ĥ compressed =Ĥ H Ĥ and y compressed =Ĥy, Equation 6 may be rewritten as:
 
 {circumflex over (x)} =( Ĥ   compressed +σ n   2   I ) −1   y   compressed   (7).
 
     Accordingly, the architecture of base station  300  as shown in  FIG. 3  proves lossless due to the resulting equivalence of detected symbol vector {circumflex over (x)} in Equation 4 and Equation 7. 
     By performing compression on user data at RRU  306 , base station  300  may compress data traffic on RRU-BBU interconnection link  308  from antenna number-proportional to user-proportional, such as by compressing PUSCH data contained in y corresponding to UE 1 -UE K  in an LTE configuration. Performing such compression of PUSCH data to transmit y compressed  in place of y results in a compression ratio of 
     
       
         
           
             
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     As detailed above, RRU  306  may transmit Ĥ compressed  and SRS symbols in addition to y compressed  over RRU-BBU interconnection link  308 . Base station  300  may achieve further compression on data transmitted on the RRU-BBU interconnection link  308  by additionally compressing Ĥ compressed  at RRU  306  before transmission to BBU  310 . As given by Equation 3 detailing the calculation of Ĥ compressed  from Ĥ, Ĥ compressed  is a Hermitian matrix, thereby satisfying Ĥ compressed (i,j)=Ĥ* compressed (j,i) (where the notation A* denotes the complex conjugate of A). Accordingly, the upper triangular matrix of Ĥ compressed  is sufficient to recover Ĥ compressed . RRU  306  may therefore transmit the upper triangular matrix of Ĥ compressed  to BBU  308 , thereby achieving a compression ratio of nearly 0.5 for transmission of Ĥ compressed . 
     RRU  306  may utilize Discrete Cosine Transform (DCT) DCT truncation in order to further compress Ĥ compressed . DCT truncation may be applied to transform estimation channel response information from the frequency domain to the DCT domain if a UE is assigned at several consecutive carriers. The effective length of the resulting DCT-domain sequence (i.e. along the x-axis) may thus be substantially shorter than the corresponding frequency-domain sequence, and thus may be truncated in order to further compress the associated data. 
       FIGS. 4A-4C  illustrate an example of such DCT-domain truncation compression.  FIG. 4A  shows an exemplary plot of channel response data in the frequency domain. As clearly discernible in  FIG. 4A , the frequency-domain sequence contains essential information along the entirety of the plotted x-axis. Performing truncation at any point of the frequency domain sequence would inevitably result in the loss of critical data, thereby introducing significant loss into such a compression procedure. 
     However, the same frequency-domain sequence may be transformed into the DCT-domain, as illustrated in  FIG. 4B  (note the equivalent scale in x-axis between  FIG. 4A  and  FIG. 4B ). As shown in  FIG. 4B , the DCT-domain sequence attenuates to nearly zero amplitude along the x-axis. The DCT-domain sequence may thus be truncated with minimal loss, such as shown in  FIG. 4C . The resulting truncated DCT-domain sequence may thus be substantially shorter than the corresponding frequency-domain sequence. 
     RRU  306  may therefore perform DCT truncation on Ĥ compressed  before transmission over RRU-BBU interconnection link  308 , thereby achieving a compression ratio of 0.125. RRU  306  may additionally or alternatively perform upper triangular matrix compression on Ĥ compressed  (i.e. by selecting to transmit the elements of Ĥ compressed  appearing in the upper triangle). RRU  306  may achieve a combined compression ratio of 0.06 by applying both DCT truncation and upper triangular matrix compression on Ĥ compressed , thereby further reducing link burden on RRU-BBU interconnection link  308 . 
     The first configuration detailed above as realized in base station  300  may substantially reduce data throughput requirements on RRU-BBU interconnection link  308  by compressing user data using a compression filter derived from channel response estimates calculated at RRU  306 . RRU  306  may further reduce link burden by additionally compressing the compression filter for transmission to BBU  310 . The resulting compression scheme may be lossless (i.e. in the case of user data compression and upper triangular matrix compression) or nearly lossless (i.e. with minimal loss incurred by truncation of channel response data in the DCT-domain). 
     In the second configuration introduced above, the RRU may similarly perform compression using a compression filter derived from channel response estimates. However, in order to realize a “thinner” RRU architecture (i.e. less components at the RRU), the channel estimation and related compression filter calculation may instead be performed at the BBU. The BBU may then transmit the appropriate compression filter to the RRU, which may apply the compression filter to received user data and transmit the resulting compressed data to the BBU over the RRU-BBU interconnection link. 
       FIG. 5  shows a block diagram illustrating an exemplary internal configuration of base station  500 . Base station  500  may be configured according to the second configuration introduced above. Base station  500  may include antenna array  502 , analog combiner  504 , RRU  306 , RRU-BBU interconnection link  508 , and BBU  310 . It is appreciated that antenna array  502  and analog combiner  504  may operate with substantially the same functionality as detailed regarding antenna array  302  and analog combiner  304  of base station  300 . 
     It is understood that the components of base station  500 , in particular RRU  506  and BBU  510  and all internal components thereof (e.g. AGC, ADC, &amp; FFT hardware  506   a , RB selection hardware  506   b , and compression hardware  506   c ), may be structurally implemented as hardware, software executed on hardware, or a mixture of hardware and software. Specifically, RRU  506  and BBU  510  may include one or more digital processing circuits, such as logic circuits, processors, microprocessors, Central Processing Units (CPUs), Graphics Processing Units (GPUs) (including General-Purpose Computing on GPU (GPGPU)), Digital Signal Processors (DSPs), Field Programmable Gate Arrays (FPGAs), integrated circuits, Application Specific Integrated Circuits (ASICs), or any combination thereof. It is understood that a person of skill in the art will appreciate the corresponding structure disclosed herein, be it in explicit reference to a physical structure and/or in the form of mathematical formulas, prose, flow charts, or any other manner providing sufficient structure (such as e.g. regarding an algorithm). The components of base station  500  components may be detailed herein substantially in terms of functional operation in recognition that a person of skill in the art may readily appreciate the various possible structural realizations of each component that will provide the desired functionality. 
     In contrast to base station  300 , BBU  510  may implement channel estimation in order to calculate and provide a compression filter to RRU  506 , which RRU  506  may then apply in order to compress received data symbol vector y into compressed received data symbol vector y compressed . Accordingly, RRU  506  may include AGC, ADC, &amp; FFT hardware  506   a , RB selection hardware  506   b , and compression hardware  506   c , while BBU  310  may include CE, EQ, and coordinated processing hardware. RRU  506  and BBU  510  may each be implemented using processing circuitry. RRU  506  may thus be realized with a “thinner” design, as all complex channel estimation processing hardware has been moved to BBU  310 . It is appreciated that include AGC, ADC, &amp; FFT hardware  506   a  and RB selection hardware  506   b  of RRU  506  may therefore operate with substantially the same functionality as detailed regarding AGC, ADC, &amp; FFT hardware  206   a  and RB selection hardware  306   b  of RRU  506 . Due to a slightly modified compression scheme, RRU-BBU interconnection link  508  may similarly operate with substantially the same functionality as RRU-BBU interconnection link  308  except for potential minor modifications related to differing data throughput support. BBU  510  may include additional channel estimation hardware and may retain substantially the same functionality of BBU  310 . 
     The operation of base station  500  according to the second configuration may be summarized as follows:
         a. Perform channel estimation at BBU  510  on previous received symbol vector y (previously provided by RRU  506 ) to obtain estimated channel response matrix Ĥ SRS   H      b. (Optional: Perform compression on compression filter at BBU  510 )   c. Transmit compression filter (based on estimated channel response matrix Ĥ SRS   H  and optionally Ĥ DMRS ) from BBU  510  to RRU  506  over RRU-BBU interconnection link  508     d. Compress current received symbol vector y at RRU  506  using Ĥ SRS   H  to generate compressed received symbol vector y compressed      e. Transmit y compressed  (including received SRS and DMRS symbols) from RRU  506  to BBU  510  over RRU-BBU interconnection link  508     f. Determine compressed estimated channel response matrix Ĥ compressed  at BBU  510  and perform symbol detection using y compressed  and Ĥ compressed  to generate detected symbol vector {circumflex over (x)}       

     As BBU  510  is responsible for computing estimated channel response matrix Ĥ SRS   H  (applied as the compression filter by RRU  506 ) in base station  500 , there may exist a slight delay in computation of the compression filter at BBU  510  and the application time of the compression filter by RRU  506 . Accordingly, BBU  510  may utilize SRS symbols instead of DMRS symbols in order to determine compression filter Ĥ SRS   H , as UE 1 -UE K  may only transmit DMRS during uplink subframes scheduled for user data transmission (i.e. PUSCH data for LTE network configurations). SRS symbols may in contrast be available during each uplink subframe, regardless of scheduled user data transmission. 
     BBU  510  may determine estimated channel response matrix Ĥ SRS   H  based on SRS symbols, which may be initially received by RRU  506  and subsequently transmitted to BBU  508 . BBU  510  may therefore extend the use of SRS data symbols past the conventional application of frequency dependent scheduling (channel quality measurement) in order to apply SRS symbols for channel response estimation and compression filter calculation. 
     As denoted in  FIG. 5 , BBU  510  may provide RRU  506  with estimated channel response matrix Ĥ SRS   H  over RRU-BBU interconnection link  508 , which RRU  506  may apply to received symbol vector y as a compression filter to generate compressed received symbol vector y compressed . 
     RRU  506  may provide BBU  510  with SRS symbols, DMRS symbols (compressed or uncompressed, as will be detailed), and y compressed . BBU  510  may then utilize the DMRS symbols in addition to Ĥ SRS   H  (as previously calculated at BBU  510 ) to perform symbol detection on compressed received symbol vector y compressed  received from RRU  506  to obtain detected symbol vector x. BBU  510  may also apply the SRS symbols (and optionally DMRS symbols) to update compression filter Ĥ SRS   H  for future use by RRU  506  to compress subsequent received symbol vector y. BBU  510  may continuously calculate the compression filter (Ĥ SRS   H  or Ĥ comb ) and provide the compression filter to RRU  506  for application in compression. 
     Base station  500  may utilize an initialization period, as the initially received SRS (and/or DMRS) symbols and symbol vector(s) y may need to first be provided to BBU  510  for compression filter calculation before RRU  506  may begin effectively compressing further received symbol vectors y using the compression filter. 
     Accordingly, RRU  506  may receive initial SRS symbols from UE 1 -UE K  using the N RX  data streams corresponding to antenna array  502  and analog combiner  504 . RRU  506  may provide the SRS symbols to BBU  510  over RRU-BBU interconnection link  508 . 
     BBU  510  may then calculate compression filter Ĥ SRS   H  (i.e. estimated channel response matrix based on SRS) to be utilized for data compression at RRU  506  using the received SRS symbols. It is appreciated that alternative procedures may be implemented in order to calculate such a compression filter, which may depend on e.g. reference symbols utilized in a particular mobile communication protocol. 
     BBU  510  may calculate Ĥ SRS   H  in a similar manner as detailed regarding base station  300 . BBU  510  may obtain the estimated channel response vector ĥ k,SRS  for each UE k  of UE 1 -UE K , where ĥ k,SRS =[ĥ 1,k,SRS ,ĥ 2,k,SRS , . . . ĥ N     RX     ,k,SRS ] T  (where each element ĥ j,k,SRS  denotes the estimated channel response based on SRS between UE k  and Ant j ). 
     BBU  510  may then obtain Ĥ SRS   H  as follows:
 
 Ĥ   SRS[N     RX×K     ]   H =[ ĥ   1,SRS   ,ĥ   2,SRS   , . . . ,ĥ   K,SRS ] H   (8).
 
     BBU  510  may then transmit Ĥ SRS   H  to RRU  506  over RRU-BBU interconnection link  508 . Upon receiving Ĥ SRS   H , RRU  506  may then apply Ĥ SRS   H  to received symbol vector y received from UE 1 -UE K  (i.e. at compression hardware  506   c ) in order to compress y to y compressed . It is appreciated that the procedure detailed above may be implemented continuously, where BBU  510  constantly computes and transmits compression filter Ĥ SRS   H  to RRU  506 . This procedure may be thus be utilized to update compression filter Ĥ SRS   H  at RRU  506  over time. 
     RRU  506  may apply compression filter Ĥ SRS   H  to compress y as follows:
 
 y   compressed   =Ĥ   SRS   H   ×y   (9).
 
     Resulting compressed received symbol vector y compressed  may thus be of dimension K×1, thereby substantially compressing user data (e.g. PUSCH data) from antenna number-proportional to user number-proportional, which may be particular advantages in MIMO schemes where N RX &gt;&gt;K. 
     RRU  506  may then transmit y compressed  to BBU  510  over RRU-BBU interconnection link  508 . In order to perform symbol detection directly on y compressed , BBU  510  may derive compressed estimated channel response matrix Ĥ compressed  (where y compressed =Ĥ compressed x). BBU  510  may obtain an accurate compressed estimated channel response matrix Ĥ compressed  based on DMRS symbols, i.e. where the DMRS symbols directly correspond to the data symbols of x and y (i.e. in time). As previously indicated, RRU  506  may supply BBU  510  with DMRS symbols in addition to SRS symbols and y compressed . 
     RRU  506  may either transmit the DMRS symbols in compressed or uncompressed form over RRU-BBU interconnection link  508 , thereby offering two alternatives for the second configuration. Uncompressed DMRS transmission may offer performance advantages over compressed DMRS transition while inherently resulting in greater link burden onto RRU-BBU interconnection link  508 . Conversely, compressed DMRS transmission may require increased data transmission rates while introducing performance loss. 
     In the uncompressed DMRS transmission scheme of the second configuration, RRU  506  may transmit DMRS symbols to BBU  510  over RRU-BBU interconnection link  508  without compression. RRU  506  may extract the DMRS symbols (and SRS symbols) from the received data stream using time selection, i.e. by de-multiplexing the reference symbols from the other uplink data contained. 
     BBU  510  may then estimate the channel response information in the form of DMRS estimated channel response matrix Ĥ DMRS  of dimension N RX ×K. BBU  510  may then determine compressed estimated channel response matrix Ĥ compressed  from {right arrow over (H)} DMRS  and Ĥ SRS   H  (already available at BBU  510 ) as follows:
 
 Ĥ   compressed   =Ĥ   SRS   H   ×Ĥ   DMRS   (10).
 
     BBU  510  may then apply resulting compressed estimated channel response matrix Ĥ compressed  to perform symbol detection directly on y compressed , i.e. as previously detailed regarding Equation 4. BBU  510  may thus obtain detected symbol vector {circumflex over (x)} corresponding to x. 
     An additional potential feature of uncompressed DMRS transmission in the second configuration is the ability to “refine” the compression matrix utilized by RRU  506  for compression of y. As previously detailed, BBU  510  may calculate and provide SRS estimated channel response matrix Ĥ SRS   H  to RRU  506  for compression, thereby relying on the constant availability of SRS symbols compared to the intermittent availability of DMRS symbols. 
     However, BBU  510  may additionally perform refinements to the compression filter provided to RRU  506 , such as by refining Ĥ SRS   H  according to subsequently obtained DMRS symbols. BBU  510  may provide combined compression filter Ĥ comb   H  to RRU  506 , where Ĥ comb  is given as follows:
 
 Ĥ   comb   =f   0 ( Ĥ   SRS )+ f   1 ( Ĥ   DMRS )  (11),
 
where f 0 ( ) and f 1 ( ) are mapping functions.
 
     BBU  510  may therefore perform real-time refinement of the compression filter, thereby refining Ĥ comb  to closely match the ideal compression filter due to the increased accuracy offered by DMRS channel response estimation. BBU  510  may continuously transmit Ĥ comb  to RRU  506 , such as by updating Ĥ comb  as newly obtained SRS and DMRS symbols are obtained. System performance may thus be further improved. 
     The uncompressed DMRS transmission scheme of the second configuration may therefore produce a compression ratio of 
                 11   14     ⁢     K     N   RX         +     3   14           
in an LTE network configuration, corresponding to the distribution of DMRS, SRS, and PUSCH symbols in uplink subframes (11 compressed PUSCH symbols with 3 uncompressed SRS and DMRS symbols per uplink sub frame).
 
     In the compressed DMRS transmission scheme of the second configuration, RRU  506  may compress received DMRS symbols before transmission to BBU  510  over RRU-BBU interconnection link  508 . RRU  506  may apply the same compression filter Ĥ SRS   H  supplied by BBU  510  for compression of DMRS symbols, thereby compressing DMRS symbols from N RX  dimension to K dimension. 
     BBU  510  thus requires compressed estimated channel response matrix Ĥ compressed  of dimension K×K to perform symbol detection directly on y compressed  to yield {circumflex over (x)}. BBU  510  may derive Ĥ compressed  directly from the compressed DMRS symbols. 
     The compressed DMRS transmission scheme of the second configuration thus yields a compression ratio of 
                 13   14     ⁢     K     N   RX         +     1   14           
(corresponding to 1 compressed SRS symbol and 13 compressed DMRS/PUSCH symbols per uplink subframe).
 
     In addition to compressing data transmitted on RRU-BBU interconnection link  508  from RRU  506  to BBU  510 , base station  500  may additionally compress data transmitted from BBU  510  to RRU  506  on RRU-BBU interconnection link  508 . Specifically, BBU  510  may perform compression on the compression matrix. As transmission of uncompressed compression filters may impose significant link burden on RRU-BBU interconnection link  508 , transmission of compressed compression filters from BBU  510  to RRU  506  may reduce the requisite data throughput level. As detailed above, such may be particularly advantageous in scenarios where large numbers of receive antennas (corresponding to large N RX ) are employed. 
     BBU  508  may represent the compression matrix by determining pre-filtering (i.e. compression) elements for each subcarrier between UE k  of UE 1 -UE K  and Ant i  of N RX  receive antennas Ant i -Ant NRX  as follows:
 
ω k,i =[ω 1,k,i ,ω 2,k,i , . . . ,ω N     SC     ,k,i ] T   (12),
 
where N SC  gives the total number of uplink subcarriers utilized by UE k .
 
     BBU  510  may calculate pre-filtering vectors ω k,i , k={1, . . . , K} and i={1, . . . , N RX } to provide to RRU  506  over RRU-BBU interconnection link  508  to apply as the compression filter for compression of y. Uplink MIMO schemes employing large numbers of antennas must therefore support high link burden on RRU-BBU interconnection link  508  in the RRU to BBU direction, which may similarly not be practically realizable in many base station configurations. 
     BBU  510  may therefore compress each ω k,i  based on the correlation between adjacent subcarriers. BBU  510  may thus compress each ω k,i  from dimension N SC  to dimension N compressed , where the value of N compressed  depends on the particular compression scheme applied by BBU  510 . BBU  510  may therefore include additional compression hardware configured to implement any number of a variety of compression schemes. The various compression schemes may provide tradeoffs between performance (i.e. loss) and link burden. 
     In particular, BBU  510  may apply a delta encoding compression scheme or linear interpolation encoding scheme in order to compress each ω k,i  for transmission over RRU-BBU interconnection link  508 . The delta encoding compression scheme may provide better performance (i.e. reduced loss) than the linear interpolation scheme with a lower relative compression ratio. Both compression schemes may thus be advantageous over uncompressed transmission schemes, particularly when a large number of receive antennas are employed (i.e. massive uplink MIMO scheme with high N RX ). 
     In the delta encoding scheme, BBU  510  may transmit an absolute pre-filtering element as a reference among every N consecutive subcarriers of each ω k,i . BBU  510  may select the reference element position as being in the middle of every N subcarriers, and may transmit the remaining N pre-filtering elements as increment values (i.e. delta values) relative to the adjacent subcarrier. In order to avoid cumulative error, BBU  510  may use the formula d n =x n −{circumflex over (x)} n-1  as opposed to d n =x n −{circumflex over (x)} n-1  for the increment elements, where {circumflex over (x)} n-1  is the recovered information of x n-1 . 
     Assuming N=N SC =12, the original pre-filtering vector ω k,i  can be expressed as follows:
 
ω k,i =[ω 1,k,i ,ω 2,k,i , . . . ,ω 6,k,i , . . . ,ω 11,k,i ,ω 12,k,i ] T   (13).
 
     As BBU  510  has knowledge of the compression scheme, BBU  510  can additionally calculate the elements of each pre-filtering vector ω k,i  as will be recovered at RRU  506 . The recovered pre-filtering vector {circumflex over (ω)} k,i  may be expressed as follows:
 
{circumflex over (ω)} k,i =[{circumflex over (ω)} 1,k,i ,{circumflex over (ω)} 2,k,i , . . . {circumflex over (ω)} 6,k,i , . . . ,{circumflex over (ω)} 11,k,i ,{circumflex over (ω)} 12,k,i ] T   (14).
 
     In order to prevent error spread, BBU  510  may calculate the increment adjacent pre-filtering elements of ω k,i  according to the recovered pre-filtering elements as opposed to the ideal elements. BBU  510  may thus calculate pre-filtering vector to ω k,i,delta  as the follows:
 
ω k,i,delta =[ d   l1,k,i   , . . . ,d   l5,k,i ,ω 6,k,i   ,d   r7,k,i   , . . . ,d   r12,k,i ] T   (15),
 
where d lj,k,i =ω j,k,i −{circumflex over (ω)} j+1,k,i  and d rj,k,i =ω j,k,i −ω j−1,k,i .
 
     BBU  510  may then quantize each increment variable d lj,k,i  and d rj,k,i  of ω k,i,delta  using Huffman compression, thereby reducing the number of requisite transmission bits for each d lj,k,i  and d rj,k,i . For example, each element d lj,k,i  and d rj,k,i  may be reduced by 2.89 bits in an implementation utilizing 16 bits for each element of ω k,i,delta . The compression ratio on the pre-filtering matrix may thus be 
     
       
         
           
             
               1 
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                 2.89 
                 16 
               
               * 
               
                 
                   
                     N 
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                 . 
               
             
           
         
       
     
     BBU  510  may implement further compression on each pre-filtering vector ω k,i  by utilizing a linear interpolation compression scheme. In the linear interpolation compression scheme, BBU  510  may transmit one pre-filtering element of each pre-filtering vector ω k,i  every N subcarriers. The resulting compressed pre-filtering vector ω k,i,interp  may thus be given as follows:
 
ω k,i,interp =[ω 1,k,i ,ω N+1,k,i , . . . ,ω jN+1,k,i , . . . ] T   (16)
 
     BBU  510  may then transmit to ω k,i,interp  to RRU  506  over RRU-BBU interconnection link  508 . RRU  506  may then recover pre-filtering vector {circumflex over (ω)} k,i  as follows:
 
{circumflex over (ω)} k,i =[{circumflex over (ω)} 1,k,i ,{circumflex over (ω)} 2,k,i , . . . ,ω N     SC     ,k,i ] T   (17),
 
where
 
     
       
         
           
             
               
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     BBU  510  may obtain a compression ratio of 
             1   N         
for pie-filtering vectors ω k,i , k={1, . . . , K} and i={1, . . . , N RX } by applying the linear interpolation compression scheme.
 
     Accordingly, there exist a number of options for applying data compression in order to reduce link burden in base stations, in particular by implementing compression at an RRU component to compress data transmitted to a BBU component over an RRU-BBU interconnection link. The data compression schemes may offer varying tradeoffs between performance (i.e. loss) and compression rate, and may be implemented in a variety of different base station architectures, in particular the first configuration and second configuration detailed herein. 
     As detailed above, in an aspect of the disclosure base station  300  and  500  may be characterized as a base station apparatus including a plurality of receive antennas (antenna array  302  or  502 ), baseband processing circuitry (BBU  310  or  510 ), radio processing circuitry (RRU  306  or  506 ), and a data link (RRU-BBU interconnection link  308  or  508 ) between the radio processing circuitry and the baseband processing circuitry. The radio processing circuitry may be configured to receive a plurality of aggregated data symbols from the plurality of receive antennas, each of the aggregated data symbols composed of transmitted data symbols from a plurality of transmit terminals and corresponding to an antenna of the plurality of antennas, apply a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive antennas and the plurality of transmit terminals, and transmit the plurality of isolated data symbols to the baseband processing circuitry over the data link. 
     As detailed above, RRU  306  or  506  may be characterized as an for processing radio signals in a base station. The apparatus may include a pre-processing circuit (AGC, ADC, &amp; FFT hardware  306   a  or  506   a  and/or RB selection hardware  306   b  or  506   b ) configured to obtain a plurality of aggregated data symbols, each of the aggregated data symbols corresponding to a receive terminal of a plurality of receive terminals of the base station and composed of transmitted data symbols from a plurality of transmit terminals; and a compression processing circuit (CE &amp; compression hardware  306   c  or compression hardware  506   c ) configured to apply a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals, and transmit the plurality of isolated data symbols to a baseband processing apparatus of the base station. 
     As detailed above, BBU  310  and  510  may be characterized as an apparatus for processing baseband signals in a base station.  FIG. 6  shows an exemplary internal architecture of baseband processing apparatus  600 , which be a BBU corresponding to either BBU  310  and/or BBU  510 . As previously indicated, BBU  310  and BBU  510  may include digital processing circuitry configured to perform various signal processing operations. Similarly, baseband processing apparatus  600  may have one or more digital processing circuits  610 . Baseband processing apparatus  600  may be configured to calculate a plurality of channel response estimates based on a plurality of reference symbols associated with a plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of a plurality of receive terminals of the base station, calculate a compression filter based on the plurality of channel response estimates, transmit the compression filter to a radio processing apparatus of the base station, receive a plurality of received data symbols from the radio processing apparatus, and perform symbol detection of the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols. 
       FIG. 7  shows a flow chart illustrating method  700  of processing signals in a radio processing apparatus of a base station. In  710 , method  700  may obtain a plurality of aggregated data symbols, each of the aggregated data symbols corresponding to a receive terminal of a plurality of receive terminals of the base station and being composed of transmitted data symbols from a plurality of transmit terminals. Method  700  may then in  720  apply a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals. In  730 , method  700  may transmit the plurality of isolated data symbols to a baseband processing apparatus of the base station. 
     The further features described above in reference to  FIGS. 1-5 , are considered equally applicable with respect to method  700 . 
       FIG. 8  shows a flow chart illustrating method  800  of transmitting data between a radio processing apparatus and a baseband processing apparatus of a base station. Method  800  may include obtaining, at the radio processing apparatus a plurality of aggregated data symbols, each of the aggregated data symbols corresponding to a receive terminal of a plurality of receive terminals of the base station and being composed of transmitted data symbols from a plurality of transmit terminals in  810 . Method  800  may then in  820  apply, at the radio processing apparatus, a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals. In  830  method  800  may transmit, from the radio processing apparatus to the baseband processing apparatus, the plurality of isolated data symbols. 
     The further features described above in reference to  FIGS. 1-5 , are considered equally applicable with respect to method  800 . 
       FIG. 9  shows a flow chart illustrating method  900  of processing signals in a baseband processing apparatus configured to be implemented in a base station. In  910 , method  900  may calculate a plurality of channel response estimates based on a plurality of reference symbols associated with a plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of a plurality of receive terminals of the base station. Method  900  may then calculate a compression filter based on the plurality of channel response estimates in  920 . In  930 , method  900  may transmit the compression filter to a radio processing apparatus of the base station. In  940 , method  900  may receive a plurality of received data symbols from the radio processing apparatus. In  950 , method  900  may perform symbol detection on the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols. 
     The further features described above in reference to  FIGS. 1-2 and 4-5  are considered equally applicable with respect to method  900 . 
     It is appreciated that many of the compression schemes may be readily combined and/or aggregated for application in a single base station structure. While all such combinations may not necessarily be explicitly detailed herein, it is understood that all such potential combinations are embraced by the scope of this disclosure. 
     As previously detailed, such compression schemes may be particularly advantageous in realizing thin base station architectures for massive uplink MIMO schemes, such as for LTE network configurations. However it is appreciated that the implementations detailed herein are considered demonstrative in nature, and may thus be readily applied in any number of scenarios, such as involving alternative communication protocols to LTE and/or conventional MIMO schemes. 
     Furthermore, while the compression filters detailed herein have exhibited a focus on derivation from channel estimates based on DMRS and/or SRS, it is appreciated that any such channel estimation procedure may be applicable, and is thus not limited to the use of DMRS and/or SRS. For example, it is understood that any such MIMO channel estimation procedure related to symbol recovery may be similarly applied in the derivation of compression filters for compressing data at a remote unit. 
     It is appreciated that implementations of methods detailed herein are demonstrative in nature, and are thus understood as capable of being implemented in a corresponding device. Likewise, it is appreciated that implementations of devices detailed herein are understood as capable of being implemented as a corresponding method. It is thus understood that a device corresponding to a method detailed herein may include a one or more components configured to perform each aspect of the related method. 
     The following examples pertain to further aspects of the disclosure: 
     Example 1 is a method of processing signals in a radio processing apparatus of a base station. The method includes obtaining a plurality of aggregated data symbols, wherein each of the plurality of aggregated data symbols corresponds to a receive terminal of a plurality of receive terminals of the base station and is composed of transmitted data symbols from a plurality of transmit terminals, applying a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals, and transmitting the plurality of isolated data symbols to a baseband processing apparatus of the base station. 
     In Example 2, the subject matter of Example 1 can optionally include receiving the compression filter at the radio processing apparatus from the baseband processing apparatus. 
     In Example 3, the subject matter of Example 2 can optionally include wherein the receiving the compression filter at the radio processing apparatus from the baseband processing apparatus includes receiving the compression filter in a compressed form at the radio processing apparatus. 
     In Example 4, the subject matter of Example 2 can optionally include receiving a plurality of reference symbols corresponding to the plurality of receive terminals, and transmitting the plurality of reference symbols to the baseband processing apparatus. 
     In Example 5, the subject matter of Example 4 can optionally include applying the compression filter to the plurality of reference symbols to generate a plurality of compressed reference symbols, and wherein the transmitting the plurality of reference symbols to the baseband processing apparatus includes transmitting the plurality of compressed reference symbols to the baseband processing apparatus. 
     In Example 6, the subject matter of Example 6 can optionally include wherein the plurality of reference symbols are demodulation reference symbols (DMRS). 
     In Example 7, the subject matter of Example 1 can optionally include determining the compression filter at the radio processing apparatus based on wireless channel estimates between the plurality of receive terminals of the base station and one or more of the plurality of transmit terminals. 
     In Example 8, the subject matter of Example 1 can optionally include calculating the compression filter at the radio processing apparatus. 
     In Example 9, the subject matter of Example 8 can optionally include calculating the compression filter at the radio processing apparatus by calculating a plurality of channel response estimates based on a plurality of reference symbols corresponding to the plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals, and calculating the compression filter based on the plurality of channel response estimates. 
     In Example 10, the subject matter of Example 9 can optionally include wherein the plurality of reference symbols includes demodulation reference symbols (DMRS). 
     In Example 11, the subject matter of Example 9 can optionally include receiving the plurality of reference symbols from the plurality of transmit terminals. 
     In Example 12, the subject matter of Example 11 can optionally include wherein the receiving the plurality of reference symbols from the plurality of transmit terminals includes receiving the plurality of reference symbols from the plurality of transmit terminals using shared time-frequency resources. 
     In Example 13, the subject matter of Example 12 can optionally include wherein the plurality of transmit terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 14, the subject matter of Example 8 can optionally include compressing the compression filter at the radio processing apparatus to generate a compressed compression filter, and transmitting the compressed compression filter to the baseband processing apparatus. 
     In Example 15, the subject matter of Example 8 can optionally include wherein the calculating the compression filter includes calculating channel response estimates between the plurality of receive terminals and the plurality of transmit terminals based on a plurality of reference symbols received from the plurality of transmit terminals. 
     In Example 16, the subject matter of any one of Examples 1 to 15 can optionally include wherein the compression filter includes a plurality of filter values, and wherein the applying a compression filter to the plurality of aggregated data symbols includes multiplying the plurality of aggregated symbols with the plurality of filter values to obtain the plurality of isolated data symbols. 
     In Example 17, the subject matter of any one of Examples 1 to 15 can optionally include wherein the compression filter includes a filter matrix, and wherein the applying a compression filter to the plurality of aggregated data symbols includes performing matrix multiplication between the filter matrix and a vector composed of the plurality of aggregated data symbols to obtain the plurality of isolated data symbols. 
     In Example 18, the subject matter of any one of Examples 1 to 15 can optionally include wherein the number of aggregated data symbols of the plurality of data symbols is greater than the number of isolated data symbols of the plurality of isolated data symbols. 
     In Example 19, the subject matter of Example 18 can optionally include wherein the number of aggregated data symbols of the plurality of data symbols is correlated with the number of receive terminals of the plurality of receive terminals, and wherein the number of isolated data symbols of the plurality of isolated data symbols is correlated with the number of transmit terminals of the plurality of transmit terminals. 
     In Example 20, the subject matter of any one of Examples 1 to 15 can optionally include wherein the total amount of data associated with the plurality of isolated data symbols is less than the total amount of data associated with the aggregated data symbols. 
     In Example 21, the subject matter of any one of Examples 1 to 15 can optionally include wherein the plurality of transmit terminals are mobile terminal devices. 
     In Example 22, the subject matter of any one of Examples 1 to 15 can optionally include wherein the plurality of receive terminals are receive antennas of the base station. 
     In Example 23, the subject matter of any one of Examples 1 to 15 can optionally include wherein the plurality of transmit terminals are mobile terminal devices and the plurality of receive terminals are receive antennas of the base station. 
     In Example 24, the subject matter of Example 23 can optionally include wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 25, the subject matter of Example 1 can optionally include compressing the compression filter to generate a compressed compression filter at the radio processing apparatus, and transmitting the compressed compression filter to the baseband processing apparatus. 
     In Example 26, the subject matter of Example 25 can optionally include wherein the compression filter includes a plurality of elements, and wherein the compressing the compression filter to generate a compressed compression filter at the radio processing apparatus includes selecting one or more repeated elements of the compression filter, and generating the compressed compression filter using the one or more repeated elements. 
     In Example 27, the subject matter of Example 25 can optionally include wherein the compressing the compression filter to generate a compressed compression filter at the radio processing apparatus includes generating the compressed compression filter by applying a discrete cosine transform to the compression filter. 
     In Example 28, the subject matter of any one of Examples 1 to 15 can optionally include wherein the radio processing apparatus is a remote radio unit (RRU) and the baseband processing apparatus is a baseband unit (BBU). 
     In Example 29, the subject matter of any one of Examples 1 to 15 can optionally include wherein the radio processing apparatus and the baseband processing apparatus are connected by an interconnection data link, and wherein the transmitting the plurality of isolated data symbols to the baseband processing apparatus includes transmitting the plurality of isolated data symbols over the interconnection data link. 
     In Example 30, the subject matter of Example 29 can optionally include wherein the interconnection data link includes an optical fiber link. 
     Example 31 is a method of transmitting data between a radio processing apparatus and a baseband processing apparatus of a base station. The method includes obtaining, at the radio processing apparatus a plurality of aggregated data symbols, wherein each of the plurality of aggregated data symbols corresponds to a receive terminal of a plurality of receive terminals of the base station and is composed of transmitted data symbols from a plurality of transmit terminals, applying, at the radio processing apparatus, a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals, and transmitting, from the radio processing apparatus to the baseband processing apparatus, the plurality of isolated data symbols. 
     In Example 32, the subject matter of Example 31 can optionally include performing, at the baseband processing apparatus, symbol detection on the plurality of isolated data symbols in order to generate a plurality of detected data symbols. 
     In Example 33, the subject matter of Example 32 can optionally include wherein the plurality of detected data symbols approximate the transmitted data symbols from the plurality of transmit terminals. 
     In Example 34, the subject matter of Example 31 can optionally include calculating, at the radio processing apparatus, the compression filter. 
     In Example 35, the subject matter of Example 34 can optionally include calculating, at the radio processing apparatus, the compression filter by calculating a plurality of channel response estimates based on a plurality of reference symbols corresponding to the plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals, and calculating the compression filter based on the plurality of channel response estimates. 
     In Example 36, the subject matter of Example 35 can optionally include wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 37, the subject matter of Example 31 can optionally include wherein the compression filter includes a plurality of filter values, and wherein the applying a compression filter to the plurality of aggregated data symbols includes multiplying, at the radio processing apparatus, the plurality of aggregated data symbols with the plurality of filter values to obtain the plurality of isolated data symbols. 
     In Example 38, the subject matter of Example 31 can optionally include wherein the compression filter includes a filter matrix, and wherein the applying a compression filter to the plurality of aggregated data symbols includes performing, at the radio processing apparatus, matrix multiplication between the filter matrix and a vector composed of the plurality of aggregated data symbols to obtain the plurality of isolated data symbols. 
     In Example 39, the subject matter of Example 34 can optionally include transmitting, from the radio processing apparatus to the baseband processing apparatus, the compression filter. 
     In Example 40, the subject matter of Example 39 can optionally include performing, at the baseband processing apparatus, symbol detection on the plurality of isolated data symbols in order to generate a plurality of detected data symbols by applying the compression filter to the plurality of isolated data symbols in order to generate the plurality of detected data symbols. 
     In Example 41, the subject matter of Example 40 can optionally include wherein the applying the compression filter to the plurality of isolated data symbols in order to generate the plurality of detected data symbols includes applying the compression filter as part of minimum mean squares (MMSE) estimation to generate the plurality of detected data symbols. 
     In Example 42, the subject matter of Example 39 can optionally include wherein the transmitting the compression filter includes compressing the compression filter at the radio processing apparatus to generate a compressed compression filter, and transmitting the compressed compression filter from the radio processing apparatus to the baseband processing apparatus over the data link. 
     In Example 43, the subject matter of Example 42 can optionally include wherein the compression filter includes a plurality of elements, and wherein the compressing the compression filter to generate a compressed compression filter, includes identifying a plurality of redundant elements of the compression filter, and generating the compressed compression filter as the plurality of redundant elements. 
     In Example 44, the subject matter of Example 42 can optionally include wherein the compressing the compression filter to generate a compressed compression filter include applying a discrete cosine transform to the compression filter to generate the compressed compression filter. 
     In Example 45, the subject matter of Example 31 can optionally include calculating, at the baseband processing apparatus, the compression filter, and transmitting, from the baseband processing apparatus to the radio processing apparatus, the compression filter. 
     In Example 46, the subject matter of Example 31 can optionally include calculating, at the baseband processing apparatus, an uncompressed compression filter, compressing, at the baseband processing apparatus, the uncompressed compression filter to generate the compression filter, and transmitting, from the baseband processing apparatus to the radio processing apparatus, the compression filter. 
     In Example 47, the subject matter of Example 46 can optionally include wherein the compressing the uncompressed compression filter to generate the compression filter includes compressing the uncompressed compression filter using a delta or linear interpolation compression scheme to generate the compression filter. 
     In Example 48, the subject matter of Example 45 can optionally include wherein the calculating the compression filter includes calculating the compression filter based on a plurality of reference symbols corresponding to the plurality of transmit terminals. 
     In Example 49, the subject matter of Example 48 can optionally include wherein the calculating the compression filter based on a plurality of reference symbols corresponding to the plurality of transmit terminals includes calculating a plurality of channel response estimates based on the plurality of reference symbols, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals. 
     In Example 50, the subject matter of Example 48 can optionally include receiving, at the radio processing apparatus, the plurality of reference symbols from the plurality of receive antennas, each of the plurality of reference symbols corresponding to a respective transmit terminal of the plurality of transmit terminals, and transmitting, from the radio processing apparatus to the baseband processing apparatus, the plurality of reference symbols over the data link. 
     In Example 51, the subject matter of Example 50 can optionally include wherein the plurality of reference symbols are sounding reference symbols (SRSs). 
     In Example 52, the subject matter of Example 45 can optionally include receiving, at the radio processing apparatus, a plurality of reference symbols corresponding to the plurality of aggregated data symbols, and transmitting, from the radio processing apparatus to the baseband processing apparatus, the plurality of reference symbols over the data link. 
     In Example 53, the subject matter of Example 52 can optionally include wherein the plurality of reference symbols are demodulation reference symbols (DMRSs). 
     In Example 54, the subject matter of Example 52 can optionally include applying, at the radio processing apparatus, the compression filter to the plurality of reference symbols to generate a plurality of compressed reference symbols, and wherein the transmitting the plurality of reference symbols includes transmitting, from the radio processing apparatus to the baseband processing apparatus, the plurality of compressed reference symbols. 
     In Example 55, the subject matter of Example 52 can optionally include applying, at the baseband processing apparatus, the compression filter and the plurality of reference symbols in order to perform symbol detection on the plurality of isolated data symbols to generate a plurality of detected data symbols. 
     In Example 56, the subject matter of Example 55 can optionally include wherein the plurality of detected data symbols approximate the plurality of transmitted data symbols. 
     In Example 57, the subject matter of Example 55 can optionally include wherein the applying the compression filter and the plurality of reference symbols in order to perform symbol detection on the plurality of isolated data symbols to generate a plurality of detected data symbols includes performing symbol detection on the plurality of isolated data symbols using minimum mean squares estimation (MMSE) based on the compression filter and the plurality of reference symbols. 
     In Example 58, the subject matter of Example 57 can optionally include calculating, at the baseband processing apparatus, a plurality of channel response estimates based on the plurality of reference symbols, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals, and wherein the performing symbol detection on the plurality of isolated data symbols includes performing symbol detection on the plurality of isolated data symbols using minimum mean squares estimation (MMSE) based on the compression filter and the plurality of channel response estimates. 
     In Example 59, the subject matter of Example 45 can optionally include updating, at the baseband processing apparatus, the compression filter, and transmitting the updated compression filter to the radio processing apparatus over the data link. 
     In Example 60, the subject matter of Example 59 can optionally include wherein the baseband processing apparatus is further configured to receive a plurality of first reference symbols and a plurality of second reference symbols from the radio processing apparatus, and wherein the baseband processing apparatus is configured to update the compression filter based on the plurality of first reference symbols and the plurality of second reference symbols. 
     In Example 61, the subject matter of Example 60 can optionally include wherein the radio processing apparatus is configured to receive the plurality of first reference symbols and the plurality of second reference symbols, and transmit the plurality of first reference symbols and the plurality of second reference symbols to the baseband processing apparatus over the data link. 
     In Example 62, the subject matter of Example 60 can optionally include wherein the plurality of first reference symbols are sounding reference symbols (SRSs) and the plurality of second reference symbols are demodulation reference symbols (DMRSs). 
     In Example 63, the subject matter of any one of Examples 31 to 62 can optionally include wherein the baseband processing apparatus is a baseband unit (BBU) and the radio processing apparatus is a remote radio unit (RRU). 
     Example 64 is an apparatus for processing radio frequency signals in a base station. The radio processing apparatus includes a pre-processing circuit configured to obtain a plurality of aggregated data symbols, wherein each of the plurality of aggregated data symbols corresponds to a receive terminal of a plurality of receive terminals of the base station and is composed of transmitted data symbols from a plurality of transmit terminals, and a compression processing circuit configured to apply a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive terminals and the plurality of transmit terminals, and transmit the plurality of isolated data symbols to a baseband processing apparatus of the base station. 
     In Example 65, the subject matter of Example 64 can optionally include wherein the compression processing circuit is configured to receive the compression filter from the baseband processing apparatus. 
     In Example 66, the subject matter of Example 65 can optionally include wherein the compression processing circuit is further configured to receive the compression filter from the baseband processing apparatus in a compressed form. 
     In Example 67, the subject matter of Example 65 can optionally include wherein the compression processing circuit is further configured to receive a plurality of reference symbols corresponding to the plurality of receive terminals, and transmit the plurality of reference symbols to the baseband processing apparatus. 
     In Example 68, the subject matter of Example 65 can optionally include wherein the processing compression circuit is further configured to apply the compression filter to the plurality of reference symbols to generate a plurality of compressed reference symbols, and wherein the compression processing circuit is configured to transmit the plurality of reference symbols to the baseband processing apparatus by transmitting the plurality of compressed reference symbols to the baseband processing apparatus. 
     In Example 69, the subject matter of Example 68 can optionally include wherein the plurality of reference symbols are demodulation reference symbols (DMRS). 
     In Example 70, the subject matter of Example 64 can optionally include wherein the compression processing circuit is further configured to determine the compression filter based on wireless channel estimates between the plurality of receive terminals of the base station and one or more of the plurality of transmit terminals. 
     In Example 71, the subject matter of Example 64 can optionally include wherein the compression processing circuit is further configured to calculate the wireless channel estimates based on reference signals received from the plurality of transmit terminals. 
     In Example 72, the subject matter of Example 64 can optionally include wherein the compression processing circuit is configured to calculate the compression filter. 
     In Example 73, the subject matter of Example 72 can optionally include wherein the compression processing circuit is configured to calculate the compression filter by calculating a plurality of channel response estimates based on a plurality of reference symbols corresponding to the plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals, and calculating the compression filter based on the plurality of channel response estimates. 
     In Example 74, the subject matter of Example 73 can optionally include wherein the plurality of reference symbols include demodulation reference symbols (DMRS). 
     In Example 75, the subject matter of Example 73 can optionally include wherein the pre-processing circuit is configured to receive the plurality of reference symbols from the plurality of transmit terminals and provide the plurality of reference symbols to the compression processing circuit. 
     In Example 76, the subject matter of Example 75 can optionally include wherein the pre-processing circuit is configured to receive the plurality of reference symbols from the plurality of transmit terminals using shared time-frequency resources. 
     In Example 77, the subject matter of Example 76 can optionally include wherein the plurality of transmit terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 78, the subject matter of Example 73 can optionally include wherein the compression processing circuit is configured to compress the compression filter to generate a compressed compression filter and transmit the compressed compression filter to the baseband processing apparatus. 
     In Example 79, the subject matter of Example 72 can optionally include wherein the compression processing circuit is configured to calculate the compression filter by calculating channel response estimates between the plurality of receive terminals based on a plurality of reference symbols corresponding to the plurality of transmit terminals. 
     In Example 80, the subject matter of Example 73 can optionally include wherein the compression filter includes a plurality of filter values, and wherein the compression processing circuit is configured to apply a compression filter to the plurality of aggregated data symbols by multiplying the plurality of aggregated data symbols with the plurality of filter values to obtain the plurality of isolated data symbols. 
     In Example 81, the subject matter of Example 72 can optionally include wherein the compression filter includes a filter matrix, and wherein the compression processing circuit is configured to apply the compression filter to the plurality of aggregated data symbols by performing matrix multiplication between the filter matrix and a vector composed of the plurality of aggregated data symbols to obtain the plurality of isolated data symbols. 
     In Example 82, the subject matter of any one of Examples 64 to 81 can optionally include wherein the number of aggregated data symbols of the plurality of data symbols is greater than the number of isolated data symbols of the plurality of isolated data symbols. 
     In Example 83, the subject matter of Example 82 can optionally include wherein the number of aggregated data symbols of the plurality of data symbols is correlated with the number of receive terminals of the plurality of receive terminals, and wherein the number of isolated data symbols of the plurality of isolated data symbols is correlated with the number of transmit terminals of the plurality of transmit terminals. 
     In Example 84, the subject matter of any one of Examples 64 to 81 can optionally include wherein the total amount of data associated with the plurality of isolated data symbols is less than the total amount of data associated with the aggregated data symbols. 
     In Example 85, the subject matter of any one of Examples 64 to 81 can optionally include wherein the plurality of transmit terminals are mobile terminal devices. 
     In Example 86, the subject matter of any one of Examples 64 to 81 can optionally include wherein the plurality of transmit terminals are mobile terminal devices involved in an uplink multiple input multiple output (MIMO) scheme. 
     In Example 87, the subject matter of any one of Examples 64 to 81 can optionally include wherein the plurality of receive terminals are receive antennas of the base station. 
     In Example 88, the subject matter of any one of Examples 64 to 81 can optionally include wherein the plurality of transmit terminals are mobile terminal devices and the plurality of receive terminals are receive antennas of the base station. 
     In Example 89, the subject matter of any one of Examples 64 to 81 can optionally include wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 90, the subject matter of any one of Examples 64 to 81 can optionally include wherein the apparatus is a remote radio unit (RRU) and the baseband processing apparatus is a baseband unit (BBU). 
     In Example 91, the subject matter of any one of Examples 64 to 81 can optionally include wherein the apparatus and the baseband processing apparatus are connected by an interconnection data link, and wherein the transmitting the plurality of isolated data symbols to the baseband processing apparatus includes transmitting the plurality of isolated data symbols over the interconnection data link. 
     In Example 92, the subject matter of Example 91 can optionally include wherein the interconnection data link includes an optical fiber link. 
     In Example 93, the subject matter of Example 64 can optionally include wherein the compression processing circuit is configured to compress the compression filter to generate a compressed compression filter, and transmit the compressed compression filter to the baseband processing apparatus. 
     In Example 94, the subject matter of Example 93 can optionally include wherein the compression filter includes a plurality of elements, and wherein the compression processing circuit is configured to generate the compressed compression filter by selecting one or more repeated elements of the compression filter, and generating the compressed compression filter using the one or more repeated elements. 
     In Example 95, the subject matter of Example 93 can optionally include wherein the compression processing circuit is configured to compress the compression filter to generate a compressed compression filter at the apparatus by generating the compressed compression filter by applying a discrete cosine transform the compression filter. 
     Example 96 is a base station. The base station includes a plurality of receive antennas, baseband processing circuitry, radio processing circuitry, and a data link between the radio processing circuitry and the baseband processing circuitry, the radio processing circuitry configured to receive a plurality of aggregated data symbols from the plurality of receive antennas, wherein each of the plurality of aggregated data symbols is composed of transmitted data symbols from a plurality of transmit terminals and corresponds to an antenna of the plurality of antennas, apply a compression filter to the plurality of aggregated data symbols in order to reduce the plurality of aggregated data symbols into a plurality of isolated data symbols, the compression filter being based on channel estimates between the plurality of receive antennas and the plurality of transmit terminals, and transmit the plurality of isolated data symbols to the baseband processing circuitry over the data link. 
     In Example 97, the subject matter of Example 96 can optionally include wherein the baseband processing circuitry is configured to perform symbol detection on the plurality of isolated data symbols in order to generate plurality of detected data symbols. 
     In Example 98, the subject matter of Example 97 can optionally include wherein the plurality of detected data symbols approximate the transmitted data symbols from the plurality of transmit terminals. 
     In Example 99, the subject matter of Example 96 can optionally include wherein the radio processing circuitry is configured to calculate the compression filter. 
     In Example 100, the subject matter of Example 96 can optionally include wherein the radio processing circuitry is configured to calculate the compression filter by calculating a plurality of channel response estimates based on a plurality of reference symbols corresponding to the plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals, and calculating the compression filter based on the plurality of channel response estimates. 
     In Example 101, the subject matter of Example 100 can optionally include wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 102, the subject matter of Example 96 can optionally include wherein the compression filter includes a plurality of filter values, and wherein the radio processing circuitry is configured to apply the compression filter to the plurality of aggregated data symbols by multiplying the plurality of aggregated data symbols with the plurality of filter values to obtain the plurality of isolated data symbols. 
     In Example 103, the subject matter of Example 96 can optionally include wherein the compression filter includes a filter matrix, and wherein the radio processing circuitry is configured to apply a compression filter to the plurality of aggregated data symbols by performing matrix multiplication between the filter matrix and a vector composed of the plurality of aggregated data symbols to obtain the plurality of isolated data symbols. 
     In Example 104, the subject matter of Example 96 can optionally include wherein the radio processing circuitry is further configured to transmit the compression filter to the baseband processing circuitry over the data link. 
     In Example 105, the subject matter of Example 104 can optionally include wherein the baseband processing circuitry is configured to receive the compression filter and the plurality of isolated data symbols over the data link. 
     In Example 106, the subject matter of Example 104 can optionally include wherein the baseband processing circuitry is configured to receive the compression filter and the plurality of isolated data symbols over the data link, and perform symbol detection on the plurality of isolated data symbols using the compression filter to generate a plurality of detected data symbols, the detected data symbols approximating the plurality of transmitted data symbols. 
     In Example 107, the subject matter of Example 106 can optionally include wherein the baseband processing circuitry is configured to perform symbol detection on the plurality of isolated data symbols using the compression filter to generate the plurality of detected data symbols using minimum mean squares estimation (MMSE). 
     In Example 108, the subject matter of Example 104 can optionally include wherein the radio processing circuitry is configured to transmit the compression filter to the baseband processing circuitry over the data link by compressing the compression filter to generate a compressed compression filter, and transmitting the compressed compression filter to the baseband processing circuitry over the data link. 
     In Example 109, the subject matter of Example 108 can optionally include wherein the radio processing circuitry is configured to compress the compression filter to generate a compressed compression filter by applying a discrete cosine transform to the compression filter to generate the compressed compression filter. 
     In Example 110, the subject matter of Example 96 can optionally include wherein the compression filter includes a plurality of filter elements, and wherein the radio processing circuitry is configured to transmit the compression filter to the baseband processing circuitry over the data link by identifying a plurality of redundant filter elements of the compression filter, generating a compressed compression filter as the plurality of redundant filter elements of the compression filter, and transmitting the compressed compression filter to the baseband processing circuitry over the data link. 
     In Example 111, the subject matter of Example 110 can optionally include wherein the compression filter includes a filter matrix composed of the plurality of filter elements, and wherein the identifying a plurality of redundant filter elements includes identifying the filter elements forming an upper or lower triangle of the filter matrix as the plurality of redundant filter elements. 
     In Example 112, the subject matter of Example 96 can optionally include wherein the baseband processing circuitry is configured to calculate the compression filter, and transmit the compression filter to the radio processing circuitry over the data link. 
     In Example 113, the subject matter of Example 96 can optionally include wherein the baseband processing circuitry is configured to calculate an uncompressed compression filter, compress the uncompressed compression filter to generate the compression filter, and transmit the compression filter to the radio processing circuitry over the data link. 
     In Example 114, the subject matter of Example 113 can optionally include wherein the baseband processing circuitry is configured to compress the uncompressed compression filter to generate the compression filter by compressing the uncompressed compression filter using a delta or linear interpolation compression scheme to generate the compression filter. 
     In Example 115, the subject matter of Example 112 can optionally include wherein the baseband processing circuitry is configured to calculate the compression filter based on a plurality of reference symbols corresponding to the plurality of transmit terminals. 
     In Example 116, the subject matter of Example 115 can optionally include wherein the baseband processing circuitry is configured to calculate the compression filter by calculating a plurality of channel response estimates based on the plurality of reference symbols, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals. 
     In Example 117, the subject matter of Example 115 can optionally include wherein the radio processing circuitry is further configured to receive a plurality of reference symbols from the plurality of receive antennas, each of the plurality of reference symbols corresponding to a respective transmit terminal of the plurality of transmit terminals, and transmit the plurality of reference symbols to the baseband processing circuitry over the data link. 
     In Example 118, the subject matter of Example 117 can optionally include wherein the plurality of reference symbols are sounding reference symbols (SRSs). 
     In Example 119, the subject matter of Example 112 can optionally include wherein the radio processing circuitry is further configured to receive a plurality of reference symbols corresponding to the plurality of aggregated data symbols, and transmit the plurality of reference symbols to the baseband processing circuitry over the data link. 
     In Example 120, the subject matter of Example 119 can optionally include wherein the plurality of reference symbols are demodulation reference symbols (DMRSs). 
     In Example 121, the subject matter of Example 119 can optionally include wherein the radio processing circuitry is further configured to apply the compression filter to the plurality of reference symbols to generate a plurality of compressed reference symbols, and wherein the radio processing circuitry is configured to transmit the plurality of reference symbols to the baseband processing circuitry over the data link by transmitting the plurality of compressed reference symbols to the baseband processing circuitry. 
     In Example 122, the subject matter of Example 119 can optionally include wherein the baseband processing circuitry is further configured to apply the compression filter and the plurality of reference symbols in order to perform symbol detection on the plurality of isolated data symbols to generate a plurality of detected data symbols. 
     In Example 123, the subject matter of Example 122 can optionally include wherein the plurality of detected data symbols approximate the plurality of transmitted data symbols. 
     In Example 124, the subject matter of Example 122 can optionally include wherein the baseband processing circuitry is configured to apply the compression filter and the plurality of reference symbols in order to perform symbol detection on the plurality of isolated data symbols to generate a plurality of detected data symbols by performing symbol detection on the plurality of isolated data symbols using minimum mean squares estimation (MMSE) based on the compression filter and the plurality of reference symbols. 
     In Example 125, the subject matter of Example 124 can optionally include wherein the baseband processing circuitry is further configured to calculate a plurality of channel response estimates based on the plurality of reference symbols, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of the plurality of receive terminals, and wherein the baseband processing circuitry is configured to perform symbol detection on plurality of isolated data symbols by performing symbol detection on the plurality of isolated data symbols using minimum mean squares estimation (MMSE) based on the compression filter and the plurality of channel response estimates. 
     In Example 126, the subject matter of Example 112 can optionally include wherein the baseband processing circuitry is further configured to update the compression filter and transmit the updated compression filter to the radio processing circuitry over the data link. 
     In Example 127, the subject matter of Example 126 can optionally include wherein the baseband processing circuitry is configured to receive a plurality of first reference symbols and a plurality of second reference symbols from the radio processing circuitry, and wherein the baseband processing circuitry is configured to update the compression filter based on the plurality of first reference symbols and the plurality of second reference symbols. 
     In Example 128, the subject matter of Example 127 can optionally include wherein the radio processing circuitry is configured to receive the plurality of first reference symbols and the plurality of second reference symbols, and transmit the plurality of first reference symbols and the plurality of second reference symbol to the baseband processing circuitry over the data link. 
     In Example 129, the subject matter of Example 127 can optionally include wherein the plurality of first reference symbols are sounding reference symbols (SRSs) and the plurality of second reference symbols are demodulation reference symbols (DMRSs). 
     In Example 130, the subject matter of any one of Examples 96 to 129 can optionally include wherein the baseband processing circuitry is a baseband unit (BBU) of the base station and the radio processing circuitry is a remote radio unit (RRU) of the base station. 
     Example 131 is an apparatus for processing baseband frequency signals in a base station. The apparatus includes one or more digital processing circuits and is configured to calculate a plurality of channel response estimates based on a plurality of reference symbols associated with a plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of a plurality of receive terminals of the base station, calculate a compression filter based on the plurality of channel response estimates, transmit the compression filter to a radio processing apparatus of the base station, receive a plurality of received data symbols from the radio processing apparatus, and perform symbol detection of the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols. 
     In Example 132, the subject matter of Example 131 can optionally include configured to receive the plurality of reference symbols from the radio processing apparatus. 
     In Example 133, the subject matter of Example 132 can optionally include further configured to receive a plurality of additional reference symbols from the radio processing apparatus. 
     In Example 134, the subject matter of Example 133 can optionally include further configured to receive the plurality of additional reference symbols in a compressed form. 
     In Example 135, the subject matter of Example 133 can optionally include wherein the plurality of additional reference symbols include demodulation reference symbols (DMRS). 
     In Example 136, the subject matter of Example 133 can optionally include further configured to calculate a plurality of additional channel response estimates based on the plurality of additional reference symbols. 
     In Example 137, the subject matter of Example 136 can optionally include configured to calculate the compression filter based on the plurality of channel response estimates by calculating the compression filter based on the plurality of channel response estimates and the plurality of additional channel response estimates. 
     In Example 138, the subject matter of Example 136 can optionally include further configured to calculate a symbol detection filter based on the plurality of channel response estimates and the plurality of additional channel response estimates, and the apparatus is configured to perform symbol detection on the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols by applying the symbol detection filter to the plurality of received data symbols to generate the plurality of detected data symbols. 
     In Example 139, the subject matter of Example 133 can optionally include further configured to calculate a symbol detection filter based on the compression filter and the plurality of additional reference symbols, and wherein the apparatus is configured to perform symbol detection of the plurality of received data symbols by applying the symbol detection filter to generate a plurality of detected data symbols. 
     In Example 140, the subject matter of Example 138 or 139 can optionally include wherein the apparatus is configured to perform symbol detection of the plurality of received data symbols by applying minimum mean squares estimation (MMSE) to the plurality of received data symbols using the symbol detection filter to generate the plurality of detected data symbols. 
     In Example 141, the subject matter of Example 131 can optionally include wherein the plurality of received data symbols contain a plurality of transmitted data symbols corresponding to the plurality of transmit terminals, and wherein the plurality of detected data symbols approximate the plurality of transmitted data symbols. 
     In Example 142, the subject matter of Example 131 can optionally include wherein the plurality of reference symbols include sounding reference symbols (SRS). 
     In Example 143, the subject matter of Example 131 can optionally include wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 144, the subject matter of Example 131 can optionally include wherein the apparatus is further configured to calculate an updated compression filter, and transmit the updated compression filter to the radio processing apparatus. 
     In Example 145, the subject matter of Example 131 can optionally include configured to calculate a compression filter based on the plurality of channel response estimates by calculating an initial compression filter based on the plurality of channel response estimates, and compressing the initial compression filter to generate the compression filter. 
     In Example 146, the subject matter of Example 145 can optionally include configured to compress the initial compression filter to generate the compression filter by compressing the initial compression filter using a delta interpolation scheme or a linear interpolation scheme to generate the compression filter. 
     In Example 147, the subject matter of any one of Examples 131 to 146 can optionally include configured as a baseband unit (BBU). 
     In Example 148, the subject matter of Example 147 can optionally include wherein the radio processing unit is a remote radio unit (RRU). 
     In Example 149, the subject matter of any one of Examples 131 to 146 can optionally include wherein the plurality of transmit terminals are a plurality of user terminals and the plurality of receive terminals are a plurality of receive antennas. 
     In Example 150, the subject matter of any one of Examples 131 to 146 can optionally include wherein the plurality of detected data symbols approximate a plurality of transmitted data symbols each associated with a respective one of the plurality of transmit terminals. 
     In Example 151, the subject matter of Example 150 can optionally include wherein the plurality of transmitted data symbols correspond to a shared wireless resource as part of a multiple input multiple output (MIMO) scheme. 
     Example 152 is a method of processing signals in a baseband processing apparatus configured to be implemented in a base station, the method including calculating a plurality of channel response estimates based on a plurality of reference symbols associated with a plurality of transmit terminals, each of the plurality of channel response estimates approximating the wireless channel between a respective transmit terminal of the plurality of transmit terminals and a respective receive terminal of a plurality of receive terminals of the base station, calculating a compression filter based on the plurality of channel response estimates, transmitting the compression filter to a radio processing apparatus of the base station, receiving a plurality of received data symbols from the radio processing apparatus, and performing symbol detection on the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols. 
     In Example 153, the subject matter of Example 152 can optionally include receiving the plurality of reference symbols from the radio processing apparatus. 
     In Example 154, the subject matter of Example 152 can optionally include receiving a plurality of additional reference symbols from the radio processing apparatus. 
     In Example 155, the subject matter of Example 154 can optionally include wherein the receiving the plurality of additional reference symbols from the radio processing apparatus includes receiving the plurality of additional reference symbols in a compressed form. 
     In Example 156, the subject matter of Example 154 can optionally include wherein the plurality of reference additional symbols include demodulation reference symbols (DMRS). 
     In Example 157, the subject matter of Example 154 can optionally include calculating a plurality of additional channel response estimates based on the plurality of additional reference symbols. 
     In Example 158, the subject matter of Example 157 can optionally include wherein the calculating a compression filter based on the plurality of channel response estimates includes calculating the compression filter based on the plurality of channel response estimates and the plurality of additional channel response estimates. 
     In Example 159, the subject matter of Example 157 can optionally include calculating a symbol detection filter based on the plurality of channel response estimates and the plurality of additional channel response estimates, and wherein the performing symbol detection on the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols includes applying the symbol detection filter to the plurality of received data symbols to generate the plurality of detected data symbols. 
     In Example 160, the subject matter of Example 154 can optionally include calculating a symbol detection filter based on the plurality of channel response estimates and the plurality of additional reference symbols, and wherein the performing symbol detection on the plurality of received data symbols using the compression filter to generate a plurality of detected data symbols includes applying the symbol detection filter to the plurality of received data symbols to generate the plurality of detected data symbols. 
     In Example 161, the subject matter of Example 159 or 160 can optionally include wherein the applying the symbol detection filter to the plurality of received data symbols to generate the plurality of detected data symbols includes applying minimum mean squares estimation (MMSE) to the plurality of received data symbols using the symbol detection filter to generate the plurality of detected data symbols. 
     In Example 162, the subject matter of Example 152 can optionally include wherein the plurality of received data symbols contain a plurality of transmitted data symbols corresponding to the plurality of transmit terminals, and wherein the plurality of detected data symbols approximate the plurality of transmitted data symbols. 
     In Example 163, the subject matter of Example 152 can optionally include wherein the plurality of reference symbols include sounding reference symbols (SRS). 
     In Example 164, the subject matter of Example 152 can optionally include wherein the plurality of transmit terminals and the plurality of receive terminals are part of a multiple input multiple output (MIMO) scheme. 
     In Example 165, the subject matter of Example 152 can optionally include calculating an updated compression filter, and transmit the updated compression filter to the radio processing apparatus. 
     In Example 166, the subject matter of Example 152 can optionally include wherein the calculating a compression filter based on the plurality of channel response estimates includes calculating an initial compression filter based on the plurality of channel response estimates, and compressing the initial compression filter to generate the compression filter. 
     In Example 167, the subject matter of Example 166 can optionally include wherein the compressing the initial compression filter to generate the compression filter includes compressing the initial compression filter using a delta interpolation scheme or a linear interpolation scheme to generate the compression filter. 
     In Example 168, the subject matter of any one of Examples 152 to 167 can optionally include wherein the baseband processing apparatus is a baseband unit (BBU) and the radio processing apparatus is a remote radio unit (RRU). 
     In Example 169, the subject matter of any one of Examples 152 to 167 can optionally include wherein the plurality of transmit terminals are a plurality of user terminals and the plurality of receive terminals are a plurality of receive antennas. 
     In Example 170, the subject matter of any one of Examples 152 to 167 can optionally include wherein the plurality of detected data symbols approximate a plurality of transmitted data symbols each associated with a respective one of the plurality of transmit terminals. 
     In Example 171, the subject matter of Example 170 can optionally include wherein the plurality of transmitted data symbols correspond to a shared wireless resource as part of a multiple input multiple output (MIMO) scheme. 
     While the invention has been particularly shown and described with reference to specific embodiments, it should be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. The scope of the invention is thus indicated by the appended claims and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced.

Metadata:
Filing Date: 20150910
Publication Date: 20200707
Grant Date: 20200707
Priority Date: 20150910
Inventors: CHANG, Wenting
ZHANG, XU
CHEN, Yujun
TIAN, Jiansong
LI, GUANGJIE
WU, YE
ZHOU, FENG
Assignee: APPLE INC
CPC Classifications: [{"code": "H04B7/0413", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04B7/0842", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L69/04", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W8/00", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04B7/0413", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L27/2639", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W88/085", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04B7/0452", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04W28/06", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L69/04", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04B7/0842", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W8/00", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L25/0224", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04B7/0413", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04W28/06", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04B7/0842", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04B7/0452", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04L25/0224", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L27/2639", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W88/085", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04W8/00", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04L69/04", "inventive": true, "first": false, "tree": "[]"}]
Family ID: 58239075