The teachings in accordance with the exemplary embodiments of this invention relate generally to Radio Standards including physical layer (PHY), Medium access control (MAC), Radio Link Control (RLC), Radio Resource Control (RRC), etc., and particularly, to radio physical layer design. More specifically, teachings in accordance with the exemplary embodiments relate to signalling formats between the user equipment (UE) and base stations.
In FDD systems (or some TDD systems, for example, those without proper calibration), the UE has to send back the DL channel information to the gNB due to the absence of channel reciprocity. The gNB may use this information to build DL precoding matrices. In LTE and NR phase I, the UE sends back one or more indices called Precoding Matrix Indicator(s) known as PMI, which point to one or more codeword(s) in a predetermined codebook known at UE and gNB sides. The predetermined codebook is based on DFT precoding. For NR phase II, a more accurate description of the channel at the gNB is required for improved multi user (MU)-MIMO performance and more advanced schemes such as non-linear precoding, coordinated multi-point transmission (CoMP) or Interference Alignment (IFA).
In one proposal, as described by Samsung, CATT (Center for Advanced Technology in Communication), ZTE Corporation, Nokia, RP−172767 titled “Motivation for new WI: Enhancements on MIMO for NR” in the GPP TSG RAN Meeting #78, the UE uses singular value decomposition (SVD) precoding to compress the channel frequency response (CFR) available at the UE. This approach may exploit the spatial and frequency correlation properties. For one receive antenna index, the CFR can be determined as a function of CFR complex coefficient between transmit antenna port (beam), receive antenna and frequency band index.
Certain abbreviations that may be found in the description and/or in the Figures are herewith defined as follows:
CFR channel frequency response
CIR channel impulse response
COMP Coordinated multi-point
CSI Channel State Information
DL Down link
DMRS Demodulation Reference Signal
FDD frequency division duplex
gNB 5G Enhanced Node B (Base station)
GoB grid of beams
IFA Interference alignment
LOS Line of sight
LTE long term evolution
MAC Medium access control
MEC multi-access edge computing
MIMO multiple input multiple output
mMIMO Massive MIMO
MME mobility management entity
MSE mean square error
Mu-MIMO Multi-user, multiple-input, multiple-output
Multi-TRP multi-transmit receive point
NCE network control element
NLOS Non line of sight
NR New radio
N/W Network
PCA Principal Component Analysis
PMI precoder matrix indicator
SVD Singular Value Decomposition
TDD time division duplex
UE User Equipment
5G Fifth generation mobile communication system
The following summary includes examples and is merely intended to be exemplary. The summary is not intended to limit the scope of the claims.
In accordance with one aspect, an example method comprises determining a number of polarizations, determining a number of receive antennas that have a same polarization, determining a total number of receive antennas based on the number of polarizations and the number of receive antennas that have the same polarization; and applying singular value decomposition precoding on all the receive antennas with the same polarization.
In accordance with another aspect, an example apparatus comprises means for determining a number of polarizations, means for determining a number of receive antennas that have a same polarization, means for determining a total number of receive antennas based on the number of polarizations and the number of receive antennas that have the same polarization; and means for applying singular value decomposition precoding on all the receive antennas with the same polarization.
In accordance with another aspect, an example apparatus comprises at least one processor; and at least one non-transitory memory including computer program code, the at least one memory and the computer program code may be configured to, with the at least one processor, cause the apparatus to: determine a number of polarizations, determine a number of receive antennas that have a same polarization, determine a total number of receive antennas based on the number of polarizations and the number of receive antennas that have the same polarization; and apply singular value decomposition precoding on all the receive antennas with the same polarization.
In accordance with another aspect, an example apparatus comprises a non-transitory program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine for performing operations, the operations comprising: determining a number of polarizations, determining a number of receive antennas that have a same polarization, determining a total number of receive antennas based on the number of polarizations and the number of receive antennas that have the same polarization; and applying singular value decomposition precoding on all the receive antennas with the same polarization.
The foregoing and other aspects of embodiments of this invention are made more evident in the following Detailed Description, when read in conjunction with the attached Drawing Figures, wherein:
In the example embodiments as described herein a method and apparatus that provides multi-beam downlink channel control procedures.
Turning to
The gNB (NR/5G Node B but possibly an evolved NodeB) 170 is a base station (e.g., for LTE, long term evolution, or for NR, New Radio) that provides access by wireless devices such as the UE 110 to the wireless network 100. The gNB 170 includes one or more processors 152, one or more memories 155, one or more network interfaces (N/W I/F(s)) 161, and one or more transceivers 160 interconnected through one or more buses 157. Each of the one or more transceivers 160 includes a receiver, Rx, 162 and a transmitter, Tx, 163. The one or more transceivers 160 are connected to one or more antennas 158. The one or more memories 155 include computer program code 153. The gNB 170 includes a signaling module 150, comprising one of or both parts 150-1 and/or 150-2, which may be implemented in a number of ways. The signaling module 150 may be implemented in hardware as signaling module 150-1, such as being implemented as part of the one or more processors 152. The signaling module 150-1 may be implemented also as an integrated circuit or through other hardware such as a programmable gate array. In another example, the signaling module 150 may be implemented as signaling module 150-2, which is implemented as computer program code 153 and is executed by the one or more processors 152. For instance, the one or more memories 155 and the computer program code 153 are configured to, with the one or more processors 152, cause the gNB 170 to perform one or more of the operations as described herein. The one or more network interfaces 161 communicate over a network such as via the links 176 and 131. Two or more gNBs 170 communicate using, e.g., link 176. The link 176 may be wired or wireless or both and may implement, e.g., an X2 interface.
The one or more buses 157 may be address, data, or control buses, and may include any interconnection mechanism, such as a series of lines on a motherboard or integrated circuit, fiber optics or other optical communication equipment, wireless channels, and the like. For example, the one or more transceivers 160 may be implemented as a remote radio head (RRH) 195, with the other elements of the gNB 170 being physically in a different location from the RRH, and the one or more buses 157 could be implemented in part as fiber optic cable to connect the other elements of the gNB 170 to the RRH 195.
It is noted that description herein indicates that “cells” perform functions, but it should be clear that the gNB that forms the cell will perform the functions. The cell makes up part of a gNB. That is, there can be multiple cells per gNB. Each cell may contain one or multiple transmission and receiving points (TRPs).
The wireless network 100 may include a network control element (NCE) 190 that may include MME (Mobility Management Entity)/SGW (Serving Gateway) functionality, and which provides connectivity with a further network, such as a telephone network and/or a data communications network (e.g., the Internet). The gNB 170 is coupled via a link 131 to the NCE 190. The link 131 may be implemented as, for example, an S1 interface. The NCE 190 includes one or more processors 175, one or more memories 171, and one or more network interfaces (N/W I/F(s)) 180, interconnected through one or more buses 185. The one or more memories 171 include computer program code 173. The one or more memories 171 and the computer program code 173 are configured to, with the one or more processors 175, cause the NCE 190 to perform one or more operations.
The wireless network 100 may implement network virtualization, which is the process of combining hardware and software network resources and network functionality into a single, software-based administrative entity, a virtual network. Network virtualization involves platform virtualization, often combined with resource virtualization. Network virtualization is categorized as either external, combining many networks, or parts of networks, into a virtual unit, or internal, providing network-like functionality to software containers on a single system. Note that the virtualized entities that result from the network virtualization are still implemented, at some level, using hardware such as processors 152 or 175 and memories 155 and 171, and also such virtualized entities create technical effects.
The computer readable memories 125, 155, and 171 may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The computer readable memories 125, 155, and 171 may be means for performing storage functions. The processors 120, 152, and 175 may be of any type suitable to the local technical environment, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on a multi-core processor architecture, as non-limiting examples. The processors 120, 152, and 175 may be means for performing functions, such as controlling the UE 110, gNB 170, and other functions as described herein.
In general, the various embodiments of the user equipment 110 can include, but are not limited to, cellular telephones such as smart phones, tablets, personal digital assistants (PDAs) having wireless communication capabilities, portable computers having wireless communication capabilities, image capture devices such as digital cameras having wireless communication capabilities, gaming devices having wireless communication capabilities, music storage and playback appliances having wireless communication capabilities, Internet appliances permitting wireless Internet access and browsing, tablets with wireless communication capabilities, as well as portable units or terminals that incorporate combinations of such functions.
Embodiments herein may be implemented in software (executed by one or more processors), hardware (e.g., an application specific integrated circuit), or a combination of software and hardware. In an example of an embodiment, the software (e.g., application logic, an instruction set) is maintained on any one of various conventional computer-readable media. In the context of this document, a “computer-readable medium” may be any media or means that can contain, store, communicate, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer, with one example of a computer described and depicted, e.g., in
The current architecture in LTE networks is fully distributed in the radio and fully centralized in the core network. The low latency requires bringing the content close to the radio which leads to local break out and multi-access edge computing (MEC). 5G may use edge cloud and local cloud architecture. Edge computing covers a wide range of technologies such as wireless sensor networks, mobile data acquisition, mobile signature analysis, cooperative distributed peer-to-peer ad hoc networking and processing also classifiable as local cloud/fog computing and grid/mesh computing, dew computing, mobile edge computing, cloudlet, distributed data storage and retrieval, autonomic self-healing networks, remote cloud services and augmented reality. In radio communications, using edge cloud may mean node operations to be carried out, at least partly, in a server, host or node operationally coupled to a remote radio head or base station comprising radio parts. It is also possible that node operations will be distributed among a plurality of servers, nodes or hosts. It should also be understood that the distribution of labor between core network operations and base station operations may differ from that of the LTE or even be non-existent. Some other technology advancements probably to be used are Software-Defined Networking (SDN), Big Data, and all-IP, which may change the way networks are being constructed and managed.
Having thus introduced one suitable but non-limiting technical context for the practice of the example embodiments of this invention, the example embodiments will now be described with greater specificity.
According to a baseline implementation, the UE 110 may use singular value decomposition (SVD) precoding to compress the channel frequency response (CFR) available at the UE 110, for one receive antenna index n, the CFR may be written as:
Where cn(m,bs) is the CFR complex coefficient between transmit antenna port (beam) m, receive antenna n and frequency band index bs. M is the number of transmit antenna ports and Bs is the number of subbands. U is the matrix containing the spatial singular vectors, V is the matrix containing the frequency singular vectors and Σ is the diagonal matrix containing the singular values. Owing to the compression behavior (for example, the UE 110 using SVD precoding to compress the CFR available at the UE), mentioned earlier, the CFR may be compressed as:
HM×B
Every short term update, the UE 110 may feedback the d most significant singular vectors back to the base station (for example gNB 170). Therefore instead of sending back M.Bs complex coefficients, the UE 110 may be required to feedback (M+Bs)×d complex coefficients. For a UE 110 with N receive antennas, the feedback overhead is equal to:
N×d×(M+Bs)×(Namp+Nphase) Eqn (3).
Where each of Namp and Nphase is a number of bits assigned for encoding the amplitude and phase components, respectively, of every coefficient.
As shown in Eqn (3), the feedback overhead increases linearly with the product of the number of receive antennas and number of antenna ports. In some systems, one UE 110 may have multiple antennas (for example, in NR, one UE 110 may have up to 8 receive antennas) which in such case of SVD precoding feedback scheme may lead to a huge feedback overhead which cannot be supported (or accepted/tolerated).
The example embodiments exploit (for example, may be based on) the correlation between the channels observed with receiver antennas having the same polarization.
Referring now to
The signal received at m=1 is x1(t)=x0(t−τ) (Eqn. 4). Where τ=cd sin(θ). Wherein c is the speed of light. Tau (τ) is the time delay by which the signal arrives between two neighboring antennas.
Therefore, the signal received at m=1: x1(t)=α(t−τ)cos(ω(t−τ)+s(t−τ)+β) (Eqn. 5)
For the case of not so large bandwidth, for example,
Hence, the complex envelope may be determined as:
According to an example embodiment in which signal 220 is x_1, Eqn (4) describes the complex envelope of signal 220.
Therefore, if the angular spread at the UE 110 side is not very high, there will be strong correlation on the amplitude of the received signals on receive antennas 205 which have the same polarization. The angular spread may be determined based on the UE 110 position, etc. A predetermined threshold may be used to determine instances in which the angular spread corresponds to a strong correlation. In frequency domain, this may lead to a correlation between the received signals on receive antennas 205 which have the same polarization.
Equation 7.3-22 of the 3GPP channel model description as described by 3GPP, “3GPP TR 36.873 V12.4.0 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Study on 3D channel model for LTE (Release 12)”, states the following:
In instances in which the UE 110 has omni directional antennas, the field patterns Frx,u,θ and Frx,u,ϕ is equal to 1. This means the only part dependent on the receive antenna index is the exponential term exp(j2πλ−1({circumflex over (r)}rx,n,mT
For a LOS user, the channel coefficient, H, may be computed as equation 7.3-27 of the 3GPP channel model description.
In this instance, it is clear that there is one dominant path (for example, for high values of KR). Two receive antennas 205 sharing the same polarization may therefore see very close amplitude for that path and at the same time instant t. In instances of LOS users, a strong correlation may be determined. Further, the example embodiments may also detect some degree of amplitude correlation for NLOS users.
Referring to
As shown in
As shown in
The example embodiments may exploit the correlation on the same polarization receive antennas 205 as follows.
The example embodiments may use an assumption that N=p×Nr, where P is the number of polarizations, in this case P=2, and Nr is the number of receive antennas with the same polarization.
The example embodiments may, instead of applying SVD precoding on each receive antenna separately, as in the baseline method described with respect to the background and
The example embodiments may exploit the correlation among receive antennas with the same polarization (for example, as shown in Eqn 5) to provide a better compression of the CSI and consequently save UL feedback overhead. The example embodiments may apply the following equation for each polarization p=0 . . . P−1
For each polarization, this finds the channel matrix for all the Nr receive antennas at the same time. With this scheme, in an example embodiment, SVD precoding is used to exploit the spatial, frequency and same-polarization correlation simultaneously. The feedback overhead required is P×d×(M+Nr×Bs)×(Namp+Nphase).
The ratio between the newly required feedback overhead using the example embodiments and the baseline is.
Simulation results on a system with M=16 antenna ports, Bs=10 frequency bands, UMi channel [2], each UE 110 has NR=2 cross polarized (Xpol) Antennas (for example, N=4), the example embodiments assume a bandwidth of 10 MHz with 50 physical resource blocks (PRBs), at a carrier frequency of 2 GHz. The example embodiments assume a channel frequency oversampling factor of 12, for example, assuming one pilot subcarrier per PRB. MU-MIMO scheme is carried out, where all UEs 110 are spatially multiplexed on the same time-frequency resources. Up to 2 layers may be transmitted per UE 110. The example embodiments assume a feedback periodicity of 10 ms and for SVD precoding may use d=2 singular vectors.
As shown in
As shown in
UE 110 (1) (first step of UE 110 procedure) performs CSI-RS reception and CSI computation and builds CFR matrix HM×R
For p=0, . . . , P−1, at (2), UE 110 may build {tilde over (H)}pM×B
At (3), UE 110 may apply SVD precoding as in Eqn (2) to obtain M×B
At (4) UE 110 may quantize elements in M×d,d×d,d×B
At (5) UE 110 may send (M×d,d×d,d×B
gNB 170, at (2), may use (UM×dn, Σd×dn, Vn
At block 610, UE 110 may determine that a number of receive antennas Nr have a same polarization.
At block 620, UE 110 may assume that N=p×Nr, where p is the number of polarizations, in this case p=2, and Nr is the number of receive antennas with the same polarization. N, P and Nr are related to the UE antenna structure. This is independent of the used feedback scheme. Nr is the number of receive antennas per polarization. In other words, no of receive antennas per polarization is the same for all polarizations.
At block 630, UE 110 may apply SVD precoding on all Nr receive antennas with the same polarization. This may be defined as a batch precoding process (or some other group precoding) as distinguished from precoding on each receive antenna separately.
At block 640, UE 110 may, for each polarization p−0 . . . P−1, determine a modified channel coefficient, {tilde over (H)}pN×B
At block 650, UE 110 may determine a feedback overhead with a ratio of
to a feedback overhead in an instance that uses singular value decomposition (SVD) precoding to compress the channel frequency response (CFR) available at the UE 110 (such as described with respect to Eqn. 3, herein above).
Without in any way limiting the scope, interpretation, or application of the claims appearing below, a technical effect of one or more of the example embodiments disclosed herein is that CSI compression is implemented before CSI feedback so as not to waste unnecessary overhead on the UL. Another technical effect, as shown by simulation results, is that a very small loss ˜3.3% in performance at the expense of saving (a relatively large amount of) ˜30% of the feedback overhead. Another technical effect is that the performance gap even decreases as the quantization resolution increases. A further technical effect is that the example embodiments may be implemented at the base station (for example, gNB 170) for improving spectral efficiency of the system for a given feedback rate and/or reducing the overall feedback overhead for NR MIMO and mMIMO systems.
An example embodiment may provide a method comprising determining a number of polarizations, determining a number of receive antennas that have a same polarization, determining a total number of receive antennas based on the number of polarizations and the number of receive antennas that have the same polarization; and applying singular value decomposition precoding on all the receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, receiving data via the receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, determining, for each polarization p=0 . . . P−1, a modified channel coefficient, {tilde over (H)}pM×B
In accordance with the example embodiments as described in the paragraphs above, determining N=p×Nr, where p is the number of polarizations, and Nr is the number of receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, determining if an angular spread at a user equipment is below a predetermined threshold; and determining that there is a strong correlation of at least one amplitude of at least one received signal on the receive antennas which have the same polarization.
In accordance with the example embodiments as described in the paragraphs above, wherein a user equipment has omni directional antennas and at least one field pattern is equal to 1.
In accordance with the example embodiments as described in the paragraphs above, finding at least one channel matrix for all the receive antennas at the same time by applying
In accordance with the example embodiments as described in the paragraphs above, assuming one pilot subcarrier per physical resource block.
In accordance with the example embodiments as described in the paragraphs above, implementing a Multi-user, multiple-input, multiple-output scheme, where all user equipment's are spatially multiplexed on a same time-frequency resources.
An example embodiment may be provided in an apparatus comprising at least one processor; and at least one non-transitory memory including computer program code, the at least one memory and the computer program code may be configured to, with the at least one processor, cause the apparatus to: determine a number of polarizations; determine a number of receive antennas that have a same polarization; determine a total number of receive antennas based on the number of polarizations and the number of receive antennas that have the same polarization; and apply singular value decomposition precoding on all the receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, receive data via the receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, determine for each polarization p=0 . . . P−1, a modified channel coefficient, {tilde over (H)}pM×B
In accordance with the example embodiments as described in the paragraphs above, determine N=p×Nr, where p is the number of polarizations, and Nr is the number of receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, determine if an angular spread at a user equipment is below a predetermined threshold; and determine that there is a strong correlation of at least one amplitude of at least one received signal on the receive antennas which have the same polarization.
In accordance with the example embodiments as described in the paragraphs above, wherein the apparatus has omni directional antennas and at least one field pattern is equal to 1.
In accordance with the example embodiments as described in the paragraphs above, find at least one channel matrix for all the receive antennas at the same time by applying
In accordance with the example embodiments as described in the paragraphs above, assume one pilot subcarrier per physical resource block.
In accordance with the example embodiments as described in the paragraphs above, implement a Multi-user, multiple-input, multiple-output scheme, where all user equipment's are spatially multiplexed on a same time-frequency resources.
An example embodiment may be provided in an apparatus comprising means for determining a number of polarizations, means for determining a number of receive antennas that have a same polarization, means for determining a total number of receive antennas based on the number of polarizations and the number of receive antennas that have the same polarization; and means for applying singular value decomposition precoding on all the receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, means for receiving data via the receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, determining for each polarization p=0 . . . P−1, a modified channel coefficient, {tilde over (H)}pM×B
In accordance with the example embodiments as described in the paragraphs above, determining N=p×Nr, where p is the number of polarizations, and Nr is the number of receive antennas with the same polarization.
In accordance with the example embodiments as described in the paragraphs above, determining if an angular spread at a user equipment is below a predetermined threshold; and determine that there is a strong correlation of at least one amplitude of at least one received signal on the receive antennas which have the same polarization.
Embodiments herein may be implemented in software (executed by one or more processors), hardware (e.g., an application specific integrated circuit), or a combination of software and hardware. In an example embodiment, the software (e.g., application logic, an instruction set) is maintained on any one of various conventional computer-readable media. In the context of this document, a “computer-readable medium” may be any media or means that can contain, store, communicate, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer, with one example of a computer described and depicted, e.g., in
If desired, the different functions discussed herein may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the above-described functions may be optional or may be combined.
Although various aspects are set out above, other aspects comprise other combinations of features from the described embodiments, and not solely the combinations described above.
It is also noted herein that while the above describes example embodiments, these descriptions should not be viewed in a limiting sense. Rather, there are several variations and modifications which may be made without departing from the scope of the present invention.
Although various aspects of the invention are set out in the independent claims, other aspects of the invention comprise other combinations of features from the described embodiments and/or the dependent claims with the features of the independent claims, and not solely the combinations explicitly set out in the claims.
It is also noted herein that while the above describes example embodiments, these descriptions should not be viewed in a limiting sense. Rather, there are several variations and modifications which may be made without departing from the scope of the present invention as defined in the appended claims.
In general, the various embodiments may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the invention is not limited thereto. While various aspects of the invention may be illustrated and described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that these blocks, apparatus, systems, techniques or methods described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.
Embodiments may be practiced in various components such as integrated circuit modules. The design of integrated circuits is by and large a highly automated process. Complex and powerful software tools are available for converting a logic level design into a semiconductor circuit design ready to be etched and formed on a semiconductor substrate.
The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. All of the embodiments described in this Detailed Description are exemplary embodiments provided to enable persons skilled in the art to make or use the invention and not to limit the scope of the invention which is defined by the claims.
The foregoing description has provided by way of example and non-limiting examples a full and informative description of the best method and apparatus presently contemplated by the inventors for carrying out the invention. However, various modifications and adaptations may become apparent to those skilled in the relevant arts in view of the foregoing description, when read in conjunction with the accompanying drawings and the appended claims. However, all such and similar modifications of the teachings of this invention will still fall within the scope of this invention.
It should be noted that the terms “connected,” “coupled,” or any variant thereof, mean any connection or coupling, either direct or indirect, between two or more elements, and may encompass the presence of one or more intermediate elements between two elements that are “connected” or “coupled” together. The coupling or connection between the elements can be physical, logical, or a combination thereof. As employed herein two elements may be considered to be “connected” or “coupled” together by the use of one or more wires, cables and/or printed electrical connections, as well as by the use of electromagnetic energy, such as electromagnetic energy having wavelengths in the radio frequency region, the microwave region and the optical (both visible and invisible) region, as several non-limiting and non-exhaustive examples.
Furthermore, some of the features of the preferred embodiments of this invention could be used to advantage without the corresponding use of other features. As such, the foregoing description should be considered as merely illustrative of the principles of the invention, and not in limitation thereof.