US 20080108310 A1 Abstract Systems and methods for closed loop MIMO (multiple input and multiple output) wireless communication are provided. Various transmit formats including spatial multiplexing and STTD are defined in which vector or matrix weighting is employed using information fed back from receivers. The feedback information may include channel matrix or SVD-based feedback.
Claims(24) 1. A MIMO system comprising:
a transmitter having multiple transmit antennas; at least one receiver, each receiver having at least one receive antenna; each receiver being adapted to transmit at least one type of feedback information selected from a group consisting of: information for use in performing beam-forming; antenna selection/grouping information. 2. The system of spatial multiplexing; vector weighted spatial multiplexing; matrix weighted spatial multiplexing; K-stream spatial multiplexing employing more than K transmit antennas; single stream STTD; single stream STTD with proportional weighting and antenna selection; multi-stream STTD; multi-stream STTD with layer weighting; multi-stream STTD with a combination of layer weighting and proportional weighting; and hybrid beam-forming and spatial multiplexing. 3. The system of 4. The system of each receiver performs respective channel measurements and feeds back information for use in performing beam-forming based on the respective channel measurements. 5. The system of a) elements of a measured channel matrix; b) elements of a V matrix of a SVD decomposed channel matrix; c) parameters of a Givens decomposition of a V matrix of a SVD decomposed channel matrix; d) parameters of a truncated Givens decomposition of a V matrix of a SVD decomposed channel matrix, where one or more eigen-vectors are discarded; e) differentially encoded elements of a measured channel matrix; f) differentially encoded elements of a V matrix of a SVD decomposed channel matrix; g) differentially encoded parameters of a Givens decomposition or truncated Givens decomposition of a V matrix of a SVD decomposed channel matrix; h) Householder decomposition; i) full scalar quantization of any of the information types of a) through h); j) partial scalar quantization of any of the information types a) through g); k) scalar quantization of any one of the information types a) through h) where varying resolution is used to quantize parameters; l) vector quantization of any of the information types of a) through h); m) a combination of scalar quantization and differential quantization for any of the information types a) through h); n) using a Delta Sigma quantizer for any of the information types a) through h). o) binary beam-forming weights; p) a differential index into a set of vector quantizations; and q) pre-defined codebook. 6. The system of 7. The system of b) Max SNR; b) Max Shannon capacity; and c) True receiver operational process. 8. The system of a) selection between SM (spatial multiplexing) and STTD (space time transmit diversity) transmission format; b) selection of particular antennas for SM transmission; c) selection and grouping of particular antennas for STTD transmission; and d) eigen-mode selection information. 9. The system of performing SVD decomposition and discarding weak eigen-modes; selecting antennas using determinants of sub-MIMO channel matrices. 10. The system of a) for every sub-carrier individually; b) for groups of consecutive sub-carriers; c) for an entire set of sub-carriers; d) for sets of groups of sub-carriers. 11. The system of 11 to 14. 12. The system of the transmitter transmits pilots on each transmit antenna for use in performing channel estimation. 13. The system of 14. The system of 15. The system of 16. The system of 17. The system of 18. The system of 19. The system of 46 to 48 with generalizations as described. 20. The system of 21. The system of 22. The system of AMC sub-channels, where respective adaptive modulation and coding is defined for each AMC sub-channel; PUSC sub-channels. 23. A receiver adapted to implement receiver functionality of 24. A transmitter adapted to implement transmitter functionality of Description This application claims the benefit of U.S. Provisional Patent Application No. 60/581,356 filed on Jun. 22, 2004, U.S. Provisional patent Application No. 60/582,298 filed on Jun. 24, 2004, U.S. Provisional Patent Application No. 60/601,178 filed on Aug. 13, 2004, Provisional Patent Application No. 60/514,621 filed on Sep. 30, 2004, Provisional Patent Application No. 60/619,461 filed on Oct. 15, 2004 and Provisional Patent Application No. 60/642,697 filed on Jan. 10, 2005, all of which are hereby incorporated by reference in their entirety. The invention relates to MIMO (multiple input, multiple output) systems and methods. In MIMO (multiple input multiple output) OFDM (orthogonal frequency division multiplexing) systems, there are multiple transmit antennas and multiple receive antennas and a plurality of sub-carriers that are available for transmission between the transmit antennas and the receive antennas for either one or multiple users. New advances in MIMO OFDM systems are taught in Applicant's co-pending application <attorney docket 71493-1320> entitled “Pilot Design For OFDM Systems With Four transmit Antennas” filed Mar. 15, 2005, and in Applicant's co-pending application <attorney docket 71493-1330) entitled “Wireless Communication Methods, Systems, And Signal Structures” filed Apr. 4, 2005, both hereby incorporated by reference in their entirety. With open loop implementations, the transmitter transmits on the multiple transmitter antennas and sub-carriers without the benefit of channel information fed back from the receivers. Efforts have been made to facilitate wireless closed-loop MIMO communications including broadband closed-loop MIMO, which might for example be based on OFDM modulation schemes, and narrowband closed-loop MIMO. Broadband closed-loop MIMO includes many sub-bands. Each of these sub-bands requires MTMO channel feedback for a closed-loop implementation. As a result the feedback resources required for broadband closed-loop MIMO can become quite large. Narrowband closed-loop MIMO, by comparison, includes one or a few sub-bands and requires a relatively smaller amount of feedback resources. Broadband and narrowband MIMO, therefore, have different applications. According to one broad aspect, the invention provides a MIMO system comprising: a transmitter having multiple transmit antennas; at least one receiver, each receiver having at least one receive antenna; each receiver being adapted to transmit at least one type of feedback information selected from a group consisting of: information for use in performing beam-forming; antenna selection/grouping information. In some embodiments, a transmission format to each receiver is selected from a group of transmission formats consisting of: spatial multiplexing; vector weighted spatial multiplexing; matrix weighted spatial multiplexing; K-stream spatial multiplexing employing more than K transmit antennas; single stream STTD; single stream STTD with proportional weighting and antenna selection; multi-stream STTD; multi-stream STUD with layer weighting; multi-stream STTD with a combination of layer weighting and proportional weighting; and hybrid beam-forming and spatial multiplexing. In some embodiments, a defined sub-set of available formats is made available for a given receiver, and wherein the given receiver feeds back a selection of one of the defined sub-set of available formats. In some embodiments, each receiver performs respective channel measurements and feeds back information for use in performing beam-forming based on the respective channel measurements. In some embodiments, the information for use in performing beam-forming is selected from a group consisting of: a) elements of a measured channel matrix; b) elements of a V matrix of a SVD decomposed channel matrix; c) parameters of a Givens decomposition of a V matrix of a SVD decomposed channel matrix; d) parameters of a truncated Givens decomposition of a V matrix of a SVD decomposed channel matrix, where one or more eigen-vectors are discarded; e) differentially encoded elements of a measured channel matrix; f) differentially encoded elements of a V matrix of a SVD decomposed channel matrix; g) differentially encoded parameters of a Givens decomposition or truncated Givens decomposition of a V matrix of a SVD decomposed channel matrix; h) Householder decomposition; i) full scalar quantization of any of the information types of a) through h); j) partial scalar quantization of any of the information types a) through g); k) scalar quantization of any one of the information types a) through h) where varying resolution is used to quantize parameters; l) vector quantization of any of the information types of a) through h); m) a combination of scalar quantization and differential quantization for any of the information types a) through h); n) using a Delta Sigma quantizer for any of the information types a) through h); o) binary beam-forming weights; p) a differential index into a set of vector quantizations; and q) pre-defined codebook. In some embodiments beam-forming feedback is performed by each receiver as a function of receiver specific criteria. In some embodiments, the receiver specific criteria is selected from a group consisting of: Max SNR; b) Max Shannon capacity; and c) True receiver operational process. In some embodiments, antenna selection/grouping information is at least one information type selected from a group consisting of: a) selection between SM (spatial multiplexing) and STTD (space time transmit diversity) transmission format; b) selection of particular antennas for SM transmission; c) selection and grouping of particular antennas for STTD transmission; and d) eigen-mode selection information. In some embodiments, the system further comprises the receiver determining the antenna selection/grouping information by performing a step selected from a group of steps consisting of: performing SVD decomposition and discarding weak eigen-modes; selecting antennas using determinants of sub-MIMO channel matrices. In some embodiments, feed back and beam-forming and/or antenna selection/grouping is performed for sub-carriers of a multi-carrier system to a resolution selected from a group consisting of: a) for every sub-carrier individually; b) for groups of consecutive sub-carriers; c) for an entire set of sub-carriers; d) for sets of groups of sub-carriers. In some embodiments, transmission matrices and feedback are in accordance with one of FIGS. In some embodiments, the transmitter transmits pilots on each transmit antenna for use in performing channel estimation. In some embodiments, at least some of the pilots are punctured pilots. In some embodiments, at least some of the pilots comprise un-coded pilots for use by multiple receivers. In some embodiments, the pilots comprise user specific pre-coded pilots for use by particular receivers receivers. In some embodiments, the pilots comprise user specific pre-coded pilots for use by particular receivers receivers and un-coded pilots for use by multiple receivers. In some embodiments, the pilot patterns are as shown in any one of In some embodiments, the pilot patterns are as shown in one of In some embodiments, feedback information is transmitted using a feedback channel having the structure of one of FIGS. In some embodiments, at least one receiver has a plurality of receive antennas. In some embodiments, the at least one receiver comprises a plurality of receivers. In some embodiments, sub-channels are defined using at least one of; AMC sub-channels, where respective adaptive modulation and coding is defined for each AMC sub-channel; PUSC sub-channels. In another embodiment, a receiver is provided that is adapted to implement receiver functionality as summarized above. In another embodiment, a transmitter is provided that is adapted to implement transmitter functionality as summarized above. Other aspects and features of the present invention will become apparent to those ordinarily skilled in the art upon review of the following description of specific embodiments of the invention in conjunction with the accompanying figures. Preferred embodiments of the invention will now be described with reference to the attached drawings in which: General Background and Example System Overview The following provides a glossary of some of the terms used in this application: AMC—Adaptive Coding and Modulation BS or BTS—Base Station CL_MIMO—Closed Loop MIMO CQI—Channel Quality Indicator CQICF—CQI channel DFT—Discrete Fourier Transform FB—Feedback FDD—Frequency Duplex FFT—Fast Fourier Transform MIMO—Multiple Input Multiple Output MLD—Maximum Likelihood Detector MSE—Minimum square error MSS—Mobile Subscriber Station PUSC—Partially Utilized Sub-Channel QoS—Quality of service SISO—Single Input Single Output SVD—Singular Value Decomposition STTD—Space Time Transmit Diversity SM—Spatial Multiplexing SQ—Scalar Quantize TDD—Time Duplex VQ—Vector Quantize For purposes of providing context for the embodiments described below, an example OFDM system will now be described with reference to FIGS. An example of a high level overview of the mobile terminals The baseband processor On the transmit side, the baseband processor With reference to The baseband processor For transmissions the baseband processor In OFDM modulation, the transmission band is divided into multiple, orthogonal carrier waves. Each carrier wave is modulated according to the digital data to be transmitted. Because OFDM divides the transmission band into multiple carriers, the bandwidth per carrier decreases and the modulation time per carrier increases. Since the multiple carriers are transmitted in parallel, the transmission rate for the digital data, or symbols, on any given carrier is lower than when a single carrier is used. OFDM modulation typically employs the performance of an Inverse Fast Fourier Transform (IFFT) on the information to be transmitted. For demodulations a Fast Fourier Transform (FFlT) is typically performed on the received signal to recover the transmitted information. In practice, the IFFT and FFT are provided by digital signal processing carrying out an Inverse Discrete Fourier Transform (IDFT) and Discrete Fourier Transform (DFT), respectively. Accordingly, the characterizing feature of OFDM modulation is that orthogonal carrier wave are generated for multiple bands within a transmission channel. The modulated signals are digital signals having a relatively low transmission rate and capable of staying within their respective bands. The individual carrier waves are not modulated directly by the digital signals. Instead, all carrier waves are modulated at once by IFFT processing. In the preferred embodiment, OFDM is used for at least the downlink transmission from the base stations With reference to The scheduled data Bit interleaver logic At this point, groups of bits have been mapped into symbols representing locations in an amplitude and phase constellation. Then spatial diversity is desired, blocks of symbols are then processed by space-time block code (STC) encoder logic For the present example, assume the base station Reference is now made to Initially, the digitized signal is provided to synchronization logic At this point, the OFDM symbols in the time domain are ready for conversion to the frequency domain using FFT processing logic The frequency domain symbols and channel reconstruction information, which are derived from the channel responses for each receive path are provided to an STC decoder The recovered symbols are placed back in order using symbol de-interleaver logic In parallel to recovering the data It is to be understood that the The embodiments set forth below represent the necessary information to enable those skilled in the art to practice the invention and illustrate the best mode of practicing the invention. Upon reading the following description in light of the accompanying drawing figures, those skilled in the art will understand the concepts of the invention and will recognize applications of these concepts not particularly addressed herein. It should be understood that these concepts and applications fall within the scope of the disclosure and the accompanying claims. While the embodiments can be applied in a system such as exemplified in FIGS. Transmission Formats for Closed Loop MIMO Various Transmission formats are provided for closed loop MIMO air-interface designs. MIMO transmission formats and signalling apparatus are generalized to allow a variety MIMO schemes to operate using the same air-interface design. According to one aspect of the invention, basic transmission formats include: (1) spatial multiplexing (SM) and (2) space-time transmit diversity (STTD), with vector or matrix weighted full MIMO or sub-MIMO transmission based on various transmit antennas configurations. These formats can be used in single or multi-carrier configurations. The schemes can also be generalized to cover multiple base station transmission. Some embodiments feature a receiver selecting between various available transmit formats. The particular formats to include in a given system are implementation specific. Spatial Multiplexing (BLAST) BLAST is also called spatial multiplexing (SM). This transmission format allows maximum parallel transmission of data streams and can achieve a theoretical capacity limit. For an open loop M×N MIMO SM transmission (M transmit antennas and N receive antennas), basic transmission matrices are presented below in Table 1 for up to four transmit antennas. It is readily apparent how similar transmission matrices can be constructed for numbers of transmit antennas larger than four.
For M transmit antenna SM, there can be N receiver antennas with N≧M. Where N<M for a given receiver, antenna selection can be performed to identify a subset of the M transmit antennas for use in BLAST transmission to the receiver. Mechanisms for performing antenna selection are described below. Vector Weighted Closed Loop SM Transmission For M×N MIMO vector weighted SM transmission according to an embodiment of the invention, the transmission matrices are presented below in Table 2 for up to four transmit antennas. It is readily apparent how vector weighted SM matrices can be extended to handle more than four transmit antennas. With vector weighted closed loop transmission, each symbol is transmitted on a single transmit antenna and a single weight is applied to each such symbol. Other users can then be supported using the remaining antenna(s).
Vector weighted SM allows, for example, per antenna power allocation and balancing, SINR optimization from the receiver, and joint transmit-receive closed loop optimization as a Weiner solution. For M transmit antenna vector weighted SM, there can be N receiver antennas with N≧M, Where N<M for a given receiver, antenna selection can be performed to identify a subset of the M transmit antennas for use in BLAST transmission to the receiver. Mechanisms for performing antenna selection are described below. Other users can then be supported using the remaining antenna(s) Matrix Weighted Closed Loop SM Transmission M×N MIMO matrix weighted SM transmission according to an embodiment of the invention has associated transmission matrices as shown in Table 3, where 2, 3 and 4 transmit antenna matrices are shown. As in the previous examples, it is readily apparent how matrix weighted SM transmission matrices can be extended to handle more than four transmit antennas. With matrix weighted spatial multiplexing, each symbol is represented on multiple transmit antennas with a respective weight. However, depending upon the weight selected, a given symbol may not necessarily be represented on all transmit antennas. Different examples of this are presented below.
The matrix weighted M×N SM transmission can be applied to a single user reception application where N≧M or to the multi-user concurrent transmission cases, such as 2×2×1, 4×4×1, 4×2×2, for example. In the above examples, 2×2×1 for example, means two transmit antennas, two users, and each user having one receive antenna. Where N<M for a given receiver, antenna selection can be performed to identify a subset of the M transmit antennas for use in BLAST transmission to the receiver. Mechanisms for performing antenna selection are described below. Other users can then be supported using the remaining antenna(s). Tables 4 to 6 and
The first configuration For the second configuration, generally indicated at Table 5 below provides similar information to that described in Table 4 above, but for a three transmit antenna case. In other words, this is elaborating the details of transmit formats available for the matrix weighted SM matrix-B described above in Table 3. The options available with a three transmit case are to use all three streams for a single user as indicated at format-1 in the first row, to use one of the three symbol streams for a first user and the remaining two symbol streams for a second user as shown in format-2 in the second row, and to assign a different user to each of the three streams as shown in format-3 in the third row. In all cases, the transmit beam-forming matrix has the same structure. The feedback options are again listed in the right hand three columns of Table 5.
Similarly, the configurations available for a four transmit antenna configuration with matrix weighting are shown in Table 6 below. A single user format is shown in the first row; two user formats are shown in the second and fourth rows, a three user format is shown in the third row, and a four user format is shown in the fifth row. It is to be understood that not all of the potential formats have been exhaustively shown in Table 6. In all cases, the transmit beam-forming matrix has the same structure, and the feedback options for the different formats are shown in the right hand three columns of Table 6.
The second configuration shown in The above described BLAST vector and weighted transmission configurations are generally applicable for closed loop MIMO systems with 2, 3 and 4 antennas. It should be readily apparent how these can be extended to handle a larger number of antennas. In a multi-carrier environment, these transmission configurations can be applied either on a per-carrier basis, for blocks of contiguous carriers, sets of non- or partially-contiguous carriers, or for an entire transmit bandwidth. Thus, for the OFDM particular implementations, in some implementations, a different beam-forming matrix/user assignment can be applied on a per-carrier basis; in other implementations, the available OFDM bandwidth is divided into sub-bands, and the same beam-forming matrix/user assignment is used on each sub-band; and yet a further available option, the entire OFDM bandwidth is used to transmit with the same beam-forming configuration. In yet another option, the entire available OFDM bandwidth divided into small sub-channels, with each user being assigned a respective set of such sub-channels. Spatial Multiplexing when there are More Transmit Antennas than Receive Antennas When there are extra transmit antennas, antenna selection and signal pre-processing can be used to significantly enhance link level performances. The SNR relation is: where γ Antenna Selection for Spatial Multiplexing With antenna selection, the receiver analyzes conditions on the channel and selects antennas that are best for that receiver. This antenna selection information is then fed back to the transmitter for use in performing the actual transmissions. Antenna Selection for a Single User With Single Antenna A single stream selective transmit diversity technique is represented in Table 7 below. This example assumes that there are four transmit antennas available to be selected for a single receive antenna user. The four different transmit options are shown in the table to include: the user's symbol s Once again for a multi-carrier implementation, antenna selection can take place to any appropriate sub-carrier resolution. The particular feedback signalling is one particular example of how to signal back an identity of one of four antennas. An appropriate signalling mechanism can be employed. Furthermore, the antenna selection mechanism can be extended to differing numbers of transmit antennas.
2-Stream Spatial Multiplexing for Single User An embodiment of the intention proposes closed loop sub-MIMO selection for SM. The term “sub-MIMO” is used to describe the case where there are multiple transmit antennas and a fewer number of receive antennas, and antenna selection is used to select a subset of the transmit antennas for use by the given receiver with the remaining antennas being available for other receivers. This will be described in the context of a 4×2 sub-MIMO system, in which the channel matrix to a given receiver has the following format:
More generally, in a K receive antenna system, K columns from channel matrix II can be selected, where K is the size of the subset antenna group. There are a total of C As in previous discussions, for multi-carrier applications, antenna selection can be used at whatever frequency resolution may be determined for a given application. The best antenna group may differ for different sub-carriers. If no other users are simultaneously being transmitted to, null sub-carriers are preferably fed into non-selected antennas. This antenna selection process is typically performed at the receiver. Once the best two transmit antennas have been selected at the receiver, the selection is fed back to the transmitter. An example of how this feedback can be performed is shown in Table 8 below. The transmit contents that are possible are shown for each of the four transmit antennas. It can be seen that there are six different permutations depending upon which two transmit antennas are selected. The first column is used to show how three bits can be used to transmit a selection of two of the six antennas. Other feedback formats are possible. In some implementations feed back is for every sub-carrier. If three bits are fed back on a per sub-carrier basis, then for L sub-carriers, L×3 bits would be required, in some implementations, feed back is for a sub-channel of contiguous sub-carriers. If three bits are fed back for a contiguous block of sub-carriers, under the assumption that channel conditions are substantially constant across the block, obviously fewer feedback bits are required.
In this case, the sub-MIMO channel selection is based on the sub-MIMO channel condition and the antenna power allocation for the SM data can be adjusted by the feedback information pertaining to the weights. Antenna group index (illustratively 3 bits), and proportional weighting vector (illustratively 2 real elements (or alternatively complex elements), each element being of 4-bits, 6-bits, or 8-bits) are preferably provided as feedback, signals. It should be appreciated, however, that weights may be derived from feedback information and need not necessarily be directly provided in feedback information. Closed Loop Sub-MIMO Selection with Beam-Forming For a DL 4×2 MIMO system, consider six sub-MIMO systems H Table 9 is an illustrative example of this. A single antenna is used to transmit a stream without any weighting; another antenna is used to transmit the same stream with weighting; and the remaining two antennas are used to transmit the other second stream, both with weighting. The particular antenna used to transmit either the un-weighted symbol or the weighted symbols is information that is preferably fed back to the transmitter. The weighting vector or information from which the weights can be derived is also preferably fed back from the receiver to the transmitter. Thus, the illustrated example, this would require the equivalent of three bits to identify one of the six permutations, and additional feedback for the three weights w
STTD Transmission Formats The transmission formats described thus far have all been based on the BLAST approach in which there is a single transmitted symbol for each information symbol, or on the BLAST variant described by way of example with reference to Table 9 above in which each K-stream blast is employed on more than K antennas, so at least some of the symbols are transmitted twice. Additional transmission formats are based on STTD (space time transmit diversity) in which there are at least two transmitted symbols based on each information symbol, and typically sets of two information symbols are transmitted using 2×2 Alamouti block. However, other STTD formats are also contemplated. Single Stream Weighted STTD (SSTD) for a Single User with Antenna Selection and Proportional Weighting In another transmission format, for a single data steam, transmit diversity is “proportionally weighted” STTD. This is a middle approach between conventional STTD (no weighting) and antenna switching. One advantage of this scheme is to safeguard against possible feedback error, feedback delay, and possible channel change between feedback updates for the antenna selection. The channel matrix condition (CMC) does not affect STTD when orthogonal codes are used. For quasi-orthogonal codes, CMC does affect signal quality. In the case of single stream transmit diversity, we also have the two options of beam-forming and antenna selection that can be performed similarly to that described above for the BLAST transmission formats. Beam-forming involves applying weights to the elements of the STTD groups, and antenna selection involves selecting a sub-set of a set of available transmit antennas for transmitting the stream. For an SSTD system with four transmit antennas, a hybrid proportionally weighted STTD approach can be used. In one embodiment, the two antennas with the strongest combined SNR are selected, and proportional weighting on these two selected antennas is then applied. The advantages of this scheme include; diversity and SNR gain due to antenna selection, increased robustness provided by proportional weighting, and the employment of efficient Alamouti codes. An example of SSTD with antenna selection and proportional weighting is given in Table 10, where two antennas out of four are selected and weighted,
In this case, feedback signals preferably include antenna group index (illustratively 3 bits), proportional weighting vector or other information allowing the determination of the weighting vector (illustratively 2 real elements, each element might for example be of 4-bits, 6-bits, or 8-bits). It should be readily apparent how the single stream case can be extended to larger numbers of transmit antennas. Double Stream Transmit Diversity (D-STTD) for a Single User With double stream transmit diversity, two streams are transmitted to a single user with each stream being sent using a respective weighted Alamouti code structure (or some other STTD structure). More generally, with an M transmit antenna system, M/2 STTD sub-groups can be formed and transmitted to a different receiver, although multiple or all of the sub-groups might be sent to one receiver. This is a hybrid case of STTD and space-multiplexing (SM). Because of inter-code interference, antenna grouping becomes more important. Preferably, layer based water-filling is employed to provide additional gain to the system. With layer-based water-filling, more power is transmitted to the layer having the better channel. Thus, with a double STTD system, a respective pair of antennas is assigned to each stream, and the respective “layer” is transmitted on that pair of antennas. Preferably, more power is given to the layer having the better channel conditions. An example of a set of possible layer weighting permutations is shown in Table 11 for the four transmit antenna case. In the first row, transmit antennas
The feedback signals in this case are used to select one of the three different permutations, and this can take the form of an antenna group index (2 bits in the example shown), and weights or information relating to weights. In this implementation, there are two STTD water-filling weights and each can be fed back to an implementation specific resolution, for example, 4-bits, 6-bits, or 8-bits. The water-filling weights determine the relative amount of power used on the two STTD groups. In summary, the options for STTD transmissions for a single user include a pair of antennas to transmit a single layer, or multiple pairs of transmit antennas each used to transmit a respective layer, in each of these cases each layer being transmitted using STTD. Preferably, for multi-carrier applications, antenna selection/grouping is performed on a per sub-carrier basis. Alternatively, it can be performed for some other sub-carrier breakdown. In the event an entire OFDM band, this would be referred to as “fixed” STTD, while in the event of antenna grouping on a per sub-carrier basis, this is referred to as antenna grouping D-STTD, In addition to antenna grouping, antenna selection can also be used to eliminate some of the antennas and only use a single antenna per STTD block. This will make a 4×2 double STTD system degenerate to a 2×2 BLAST system. In fact, this can be viewed as applying antenna selection to each STTD sub-code—after the rule of antenna grouping has been applied. For example, if antenna selection is also used with the W-STTD format in the second row of Table 11 to eliminate the first and fourth transmit antennas, the result is something that is effectively equivalent to a 2×2 BLAST system as shown in Table 12 below.
In another embodiment, proportional weighting is applied to each constituent STTD code after antenna grouping, rather than or in addition to for the STTD codes as a whole as was the case in Table 11 above. An example of weighted double STTD with antenna grouping and proportional weighting is given in Table 13 below. There are two levels of weighting in this design: water-filling is applied across layers (i.e. across constituent STTD codes), and proportional weighting is applied within each constituent STTD code. In other words, weighting is sued to get the best allocation of the Alamouti pairs among the antennas, and weighting is used to weight the antennas of a given pair differently. In the table below, both of these weights are included within the single weight w
Referring now to Only a subset of antennas/sub-channels are selected for transmitting signals to a given receiver. Receivers only need to feedback antennas/sub-channels group indexes to the transmitter. In the event weighting is also employed, then this case, weighting information might be fed back for each sub-carrier, or for groups of six sub-carriers. In multi-user applications, antenna/sub-channel selection is based on multi-user diversity; different users may select different antenna groups. Quasi-water-filling over is preferably employed in selecting antennas/sub-channels: transmitting power on good channels and antennas, while avoiding poor channels. Power balancing can be achieved through multi-user diversity. Since different receivers experience different channel environments, their antenna group selection will not necessarily the same. When different receivers select different antenna groups, the average power transmitted by each transmit antenna can be somewhat balanced. Antenna Selection for STTD Formats and SM Formats The above STTD and SM options have all featured weighting, either in the form of water-filling across different STTD groups/SM antennas and/or proportional weighting within STTD groups. Antenna selection/antenna grouping can be combined with these weighting options. In another embodiment, antenna selection/antenna grouping alone is employed. Several examples of pure antenna selection will now be described. Antenna Selection/Grouping for three Transmit Antennas Example STTD formats for three transmit antenna applications will now be described. In the example of Another antenna grouping example is shown in Also shown is a two stream example where the receiver must select two of the three possible antennas, and feedback to the transmitter which two of the three antennas it would like to receive its data on. In this case, a power boosting factor of 1/√{square root over (2)} such that the total amount of power is divided across the two antennas for the given user. Antenna Selection/Grouping for Four Transmit Antennas With the two stream example, the matrices B For two streams, two of the four antennas are selected, and there are six different options as set out in the table. A power boosting factor of 1/√{square root over (2)} is applied for this case. For a three stream example, there are four different ways to select three of the four antennas as set out in the table. A power boosting factor of 1/√{square root over (3)} is applied. Also shown in the table is an example set of bits that can used to feedback on the channel quality indicator channel selection of an appropriate one of the potential transmission matrices depending upon whether there are 1, 2 or 3 streams. Binary Beam-Forming It is noted that while the above examples show antenna selection feedback, binary beam-forming can be used to similar effect. With binary beam-forming, the beam-forming weights are binary, meaning that a given antenna is either on or off. This is analogous to selection. Two specific examples of using beam-forming to perform antenna selection are provided in MIMO Downlink Pilot Designs Referring now to Referring first to Referring now to While a particular staggering arrangement has been shown in Referring now to Referring now to Referring now to Referring now to Referring now to As indicated above, for the example pilot patterns of Pilot Transmission Schemes with Pilot Pre-Coding Systems and methods employing pre-coding of MIMO pilots in accordance with an embodiment of the invention will now be described. In the above described embodiments, it has been assumed that pilot channel information is transmitted without any weights being applied. In this manner, any receiver can look at the transmitted pilot information and recover a respective channel for the particular receiver. In some embodiments, a pre-coding of the pilot is performed. For a pre-coded pilot, the equivalent channel measured at the receiver becomes G=HW, where H is the actual channel, and W are the weights applied to the pilots. The feedback beam-former W, or information from which it can be derived, may be computed from the channel H for a particular user, Many examples of how this feedback can be performed are detailed below. In the event pre-coding of the pilot is performed, the channel can be recovered according to:
1. current H analysis and future feedback; and 2. multiple users (possibly including non-MIMO) to assist in channel interpolation. The non-pre-coded channel H can be re-encoded to coherently demodulate current data for each user. In contrast, with the example of Advantageously, by using pre-coded pilots, a smaller number of pilots can be used. The number of pilots can be reduced in either the time or frequency dimension. Preferably, for cases in which the receiver is mobile, the density in time is kept the same and the density is reduced in the frequency domain. Furthermore, for band adaptive modulation and coding, it is preferable to select the most flat part of the band or use larger FFT size, and/or to use an interlaced antenna pilot mapping. For the case where a receiver is nomadic, i.e., it is not highly mobile, but does move periodically, it is advantageous to keep the frequency density the same, and to reduce the density in the time domain. In this case, preferably a block antenna pilot mapping is employed. The location of the receiver-specific pilots is an implementation specific decision. For the purpose of completeness, several examples are presented below. The example of Referring now to The example of In accordance with another embodiment of the invention a pre-coded pilot design for the PUSC (partial use sub-carrier applications) is provided. For PUSC the symbol is first divided into basic clusters of consecutive sub-carriers. Pilots and data carriers are allocated within each cluster of sub-carriers. According to IEEE 802.16-2004, a permutation is used when allocating the data carriers to a sub-channel, a permutation consisting of a remapping of the a cluster sub-carriers into other allocations (that can be almost random). The data carriers in each cluster may be assigned to different MSSs, and therefore, pilots may be used by multiple MSSs. To support the dedicated pilots to closed-loop MSSs operating in PUSC mode, the permutation procedure to partition the sub-carriers into sub-channels is disabled or is allowed to apply to the PUSC sub-channel within a single user. Each sub-channel includes 48 data carriers from two clusters. Referring now to Closed Loop Feedback Options for MIMO Applications The transmission formats discussed above rely on antenna selection/grouping feed back and/or beam-forming weights. The first option indicated at The next option indicated at The next option indicated at In another embodiment, indicated at Finally, the next option indicated at In summary, the options are to apply feedback for MIMO/STC set up and/or applying feedback to the beam-former The beam-former feedback information may be for a unitary beam-former structure, or some other beam-former. Detailed examples have been given previously as to how MIMO/STC set up information can be fed back, Many options for beam-former feedback are given in the details below. In accordance with various embodiments of the invention there is provided methods of facilitating closed loop MIMO pre-coding and feedback in a communications network that might, for example be operating in accordance with the IEEE 802.16(e) and IEEE 802.11(n) standards. As will be apparent to one of skill in the art the various embodiments can be implemented in software, firmware or an ASIC (application specific integrated circuit) or any suitable combination of these or other components. Feedback for Antenna Selection/Grouping and Eigen-mode Selection SVD Approach SVD (singular value decomposition) is theoretically optimal in terms of the best channel matching transmission and achieving the link level Shannon capacity. However, SVD typically requires a large amount of computing and a large amount of CSI (channel state information) feedback in the FDD (frequency division duplexing) case. With SVD, the Channel matrix H is decomposed according to
H can be further expressed as follows:
Thus, the matrix V Antenna Selection/Grouping Antenna selection/grouping is based on the selection of sub-set of antennae from a larger set of available antennas by the terminal based on a simple criterion. The terminal generally needs to feedback very little information to the base station, Mechanisms for transmitting this feedback information from the receiver to the transmitter have been presented above. Antenna grouping criterion can be based on determinant as described previously, Antenna grouping can also be based on an eigenvalue approach. This approach may avoid selection being dominated by weak layers. Typically degradation due to antenna selection is smaller when the group size is larger. For a MIMO system, the eigenvalues of the channel matrix are often unevenly distributed. Removing the layers associated with small eigenvalues will have little effects on channel capacity. With a reduced number of layers, more sophisticated MEMO decoders can be used to improve link performance. The power saved from layers that are not used for this a particular receiver can be used by other users on other sub-bands.
The V matrix of an SVD decomposed channel matrix consists of a set of horizontal vectors each of which are multiplied by a respective eigenvalue in the product UDV. In the transmitter, through the use of a beamforming matrix V These two approaches are summarized in SVD generally provides optimal performance when adaptive modulation and coding (AMC) can be performed on each individual layer. When AMC is not layer based, the performance difference is generally smaller due to imbalanced layer SNR distribution. Preferably, therefore, AMC is implemented on per layer basis. In some embodiments, when SVD is used the 4-th layer can generally be eliminated meaning only 3 columns of the V-matrix generally need to be fed back to the transmitter. In systems with larger numbers of antennas, it may be possible to eliminate more layers. Antenna Grouping Algorithms Various antenna grouping algorithms will now be described. Any of these can be employed on a per sub-carrier, per block of sub-carriers, per group of blocks of sub-carriers or for an entire OFDM band. They can be applied for a single or multiple user system. Selection Between STTD and SM An antenna grouping algorithm in accordance with an embodiment of the invention will now be described. With channel estimates from the pilots: the receiver computes criterion for use in selecting between STTD and SM transmission modes as follows, where if the STTD criteria is greater than the SM criteria, then STTD transmission is employed and alternatively, SM is employed. Other criteria can be used.
According to another embodiment one may exploit the benefits of both. For example, when a channel changes slowly, beam-forming provides a SNR gain, while STTD provides diversity gain (on the symbol level) which improves FEC performance (especially for higher code rates). Then, when a channel changes quickly one can degenerate to an STTD system which will preserve protection against fading. Antenna Selection for STTD An antenna grouping algorithm in accordance with an embodiment of the invention will now be described for an STTD mode. The antenna group selection can be based on criterion including the following:
For the SM mode, the antenna group selection can be based on criterion including the following:
An antenna grouping algorithm in accordance with an embodiment of the invention will now be described. For the STTD mode, in accordance with an embodiment of the invention, define
The following is a particular example of an antenna grouping procedure: Step 1: Decide antenna group size for STTD and SM mode; Step 2: Select-transmit antenna sub-sets based on selected size; Step 3: Decide transmit rode: STTD vs. SM; Step 4: If SM is selected and the antenna group size is larger than SM layers, then use Matrix B, otherwise, use Matrix C. Multi-User Pre-Coding A multi-user pre-coding algorithm in accordance with an embodiment of the invention will now be described. Consider a MIMO broadcast channel transmit antennas to transmit to K users each with N receive antennas. The base band model of this system is defined by:
In the proposed methods the transmitted vector a carries information for M users, defined as follows.
For demodulation, the user π(j) multiplies the received vector to a normal vector u′ Determination of the Active Users, Modulation, and Demodulation Vectors In this part, it is assumed that the channel state information is available at the transmitter. Later, this algorithm is modified such that only partial channel state information is required. Each stage of the algorithm includes two optimizing operations. First, for each user, finding a direction in which that user has maximum gain. Second, selecting the best user in terms of the larger gain. This optimization is performed in the null space of the former selected coordinates. In the following, the proposed algorithm is presented. 1) Set j=1 and the condition matrix G 2) Find σ As it has been mentioned before, in this algorithm, a major part of the processing can be accomplished at the receivers. Therefore the perfect channel state information is not required at the transmitter which results a significant decreasing in the rate of feedback. 1) Set j=1 and G 2) each user calculates σ Referring now to At the transmitter, there is a transmit beam-former At For the channel information, preferably the difference between the new channel matrix H and the previous channel matrix E is measured and a differential is determined between the two most recent channel matrices. This amount is encoded at At the transmitter, the channel matrix H is reconstructed at The embodiment of Feedback MIMO Channel and CQI Jointly Referring now to Differential Scalar Quantizer—Element by Element Quantization The two above-described embodiments employ the feedback of differentials in either the channel matrix H or the unitary matrix V. While the illustrated example uses +1, −1 quantization, this requiring one bit per element to be transmitted on the feedback channel ΔΣ Modulation 1-bit Quantizer In accordance with another referred embodiment of the invention a ΔΣ modulator 1-bit quantizer is employed to determine the information to be fed back. An example of a 1 Multi-User Differential Feedback The differential encoder output may be grouped together to map to the existing CQI feedback channel or MIMO feedback channel. Givens Feedback In another embodiment of the invention, the V matrix determined through singular value decomposition is fed back from the receiver to the transmitter using Givens feedback. Unitary matrices have the property that they can be decomposed into a product of Givens matrices. In particular, an n×n V matrix can be decomposed into Givens matrices containing n An example of a system employing Givens feedback is shown Then, the quantized parameters θ and C are fed back over the MIMO feedback channel Preferably, at the same time AMC/eigen assignment is performed on the basis of eigenvalues of the channel matrix of the SVD composition performed at Advantageously, for V matrix feedback, the base station is able to verify the integrity of the received matrix V by exploiting the orthogonality of the matrix. By decomposing the SVD-based unitary V matrix into Givens matrices, the V matrix can be represented by n In accordance with an embodiment of the invention, 2(n In accordance with this embodiment an n stream CQI channel may also be used, preferably 4 bits each. Combining the Given's feedback and the CQI yields the total amount for the unitary matrix feedback of 2n 2-Antenna Givens Transform The following is an SVD based Givens transform algorithm in accordance with an embodiment of the invention suitable for 2-Transmit Antennas. With 2-antenna Givens transformation, 2 An alternative format is the following Givens rotation for 2 transmit antenna (Format-B) that takes the form:
The parameter space includes π={−π+π} and η={−π+π} 3-Antenna Givens Transform An SVD based Givens transform algorithm in accordance with an embodiment of the invention will now be described for 3-Transmit Antennas. With 3-antenna Givens transforms, n The parameter space includes
It can be seen in the above example, the quantization performed for the parameter θ is more precise than that performed for the parameter C. It is generally the case that different quantization accuracies may be performed for the different parameters being fed back using given speed back. Through experimentation, it has been found that acceptable performance can be achieved with a less accurate C parameter. In some embodiments described below, certain C parameters can be ignored. 4-Antenna Givens Transform An SVD based Givens transform SQ algorithm in accordance with an embodiment of the invention will now be described for 4-Transmit Antennas. 4-antenna Givens transformation requires 4 An SVD based Givens transform algorithm in accordance with an embodiment of the invention will now be described for n-Transmit Antennas. The Givens rotation for n transmit antennas (Format-A) includes:
An SVD based Givens transform algorithm in accordance with an embodiment of the invention will now be described that employs truncation of the Givens expansion. Preferably, weak eigen-modes may be discarded with application of water filling in the eigen domain. Each Given matrix is associated with one or more eigen-modes and respective eigenvalue. As such, if a given weak eigenvalue is to be discarded, then the associated Givens matrices can be discarded. In the receiver, the V matrix is re-generated, and then only the selected eigen-modes used to transmit streams as in the above example for eigen-modes selection. For example, where the full Givens expansion for the 3×3 case is as follows:
The following is another example of truncation of Givens expansion for a 4-antenna case. The Givens expansion for eigenvector #1 of a 4×4 channel matrix is as follows:
It can be seen that discarding two eigen-modes reduces the Givens expansion by one of the six matrices while discarding three of the four eigen-modes will reduce the Givens expansion by three of the six matrices. Given that each matrix requires two parameters to be fed back, a corresponding reduction in the quantity of feedback information that needs to be transmitted is realized. Generally, it can be seen that in an arbitrary n×n case, a Givens expansion can be employed, and the amount of feedback can be optionally reduced by discarding one or more eigen-modes. Bit Allocation for Givens Feedback—Full Scalar Quantization An SVD based Givens transform algorithm in accordance with an embodiment of the invention will now be described in which full scalar quantization is performed. As discussed above, it can be advantageous to use different quantizations for the various parameters being fed back using Givens feedback. Based on the pre-coding QoS requirement, the bit allocation may provide a tradeoff between performance and feedback penalty. For the Givens parameter in Format-A, θ is uniformly distributed resulting in more bits being needed for accurate feedback, whereas C is non-uniformly distributed resulting in less bits being needed. In some implementations, some C have only minimum impact on performance and can be treated as constant without a substantial performance penalty. Using a Lloyd-MAX quantizer the following bit allocations can be employed to realize a full scalar quantizer.
An SVD based Givens transform algorithm in accordance with an embodiment of the invention will now be described in which partial scalar quantization is performed. With partial scalar quantization, a differential is not fed back for each and every parameter. In an example solution, a 1 bit or 0 bit is used for each parameter c and a differential 1-bit is used for each parameter theta. Another approach includes using less bits or zero bits for the non-significant Givens parameters. The following is an example of bit allocation with partial scalar quantization for 2, 3 and 4 antennas. It can be seen that in a particular example, for the 3-antenna case for example, the C parameter is only fed back for the first of three Givens matrices, and a three bit value is sent back for theta for the first of the three matrices, and a one bit differential is used for theta for the other two matrices. This has the potential of reducing the number of feedback bits required from nine bits from the full quantization example given above to five bits for the example in the table.
The following table shows an example set of feedback allocations for different MIMO configurations using Givens feedback with full scalar quantization versus partial scalar quantization with a 1-bit differential for theta and 1-bit for c. It can be seen that the savings in the number of bits required for feedback increase as the complexity of the MIMO configuration increases. Also shown in the table are the number of bits required for a Hausholder based feedback mechanism.
The table below shows examples of the feedback allocations for various MIMO configurations comparing full scalar feedback to partial feedback in which a 1-bit differential for theta is employed, and 1-bit or zero bits are used for each c parameter. Again, the requirements for Hausholder feedback are also shown for the sake of comparison.
Grassman Subspace Packing—Vector Quantization With scalar quantization, be it full scalar or partial scalar, each feedback element pertains to one parameter of interest. This parameter can be a Givens parameter, or a channel matrix parameter from H or V for example, or some other value. In another embodiment, vector quantization is performed, in which each element fed back represents a vector, either in absolute terms or differential terms, and in respect of a set of parameters of interest. Each potential state for the output of the vector quantization operation is represented by a code word identifier/index which is fed back, and used by the transmitter to look up the vector. The vectors thus looked up are then used to generate the beam former in the transmitter. The vector might be a vector of a channel matrix, a vector of a V matrix (this would be a unitary vector), or a set of Givens parameters for example. In one embodiment, an SVD based Givens transform vector quantization algorithm is provided that employs Grassmann Subspace Packing. However, other forms of vector quantization may alternatively be employed. Each individual Givens matrix is a unitary matrix. The product of Givens matrices is a unitary matrix. The partial product of two or more Givens matrices is a unitary matrix. After determining a truncated or full Givens expansion, the resulting of unitary matrix may be quantized by using Grassmann sub-space packing (see for example D. J. Love, R. W. Heath Jr., and T. Strohmer, “Grassmannian Beamforming for Multiple-Input Multiple-Output Wireless Systems,” IEEE Transactions on Information Theory, vol. 49, pp. 2735-2747, October 2003). In this case, the code book for quantization of a unitary matrix may be considered as sub-space packing in a Grassmann manifold. Two codebooks that might be used include the uniform distributed Grassmann space, and Block circulant DFT, but other codebooks may alternatively be employed. An example of encoding using shape and gain quantizer according to an embodiment of the invention is shown in Spherical Codebook Quantizer An SVD based Givens transform vector quantization algorithm in accordance with an embodiment of the invention will now be described that employs a Spherical Code Based Quantizer. This method begins with putting the Givens parameters into a vector and then encoding the vector using a spherical code based quantizer. The following steps are performed: - 1. Given k element vector form the vector X←R
^{k } - 2. Compute g=|X| and S=X/g
- 3. Use the gain codebook to quantize g as
__g__ - 4. Find i such that α
_{i}=<sin−^{1}x_{k}<α_{i+1 }and compute
*h*_{i}(*s*)=*X/∥X∥(∥**X*_{L}^{j}*∥−∥X*_{L}*−X*∥) - 5. Find the nearest neighborhood
__h___{i}(S) to h_{i}(S) - 6. Compute h
_{i}^{−1}(h_{i}(S)) to identify the quantized shape S - 7. Compute the index
__gS__and transmit In accordance with an embodiment, Leech Lattice is used as a codebook. Alternatively, a trellis-coded quantizer can also be employed. Feedback Setup Using Receiver Criteria
A receiver based Givens transform in accordance with an embodiment of the invention will now be described in which search criteria axe established in the receiver. -
- In accordance with this embodiment of the invention channel filling is based on criteria including the receiver criteria. Based on the QoS requirements, the receiver determines the minimum feedback needed adaptively. The process may include the following:
determining the Givens truncation level; based on the Scalar quantizer structure assigning parameter values; and/or performing combinatorial searches of combinations.
Based on the receiver criterion, exhaustive search the code book and maximize the given received based criterion to determine the best pre-code matrix. These equations represent exhaustively computing beam-forming weights to see which one is the best for a given criteria.
Referring now to In any of the examples above, the Givens decomposition can be computed using any appropriate method. Iterative approaches may for example be employed such as Cholsky factorization and reverse order multiplication. These methods are known in the art and will not be described further here. It is noted that Givens decomposition is about 10% of the complexity of SVD computing complexity. This can be seen from the following table comparing the complexity of SVD versus Givens as a function of the number of transmit antennas, and the complexity is measured in terms of multiply and add operations.
The following table shows a comparison of the complexity of Givens based feedback as opposed to Hausholder based feedback as a function of the number of the transmit antennas. It can be see that the Hausholder approach is significantly more complex.
Example of Codebook Construction for Vector Pre-Coding An example of Vector Pre-coding (code-book construction) for purposes of context and comparison will now be described. The cross-correlation of the codeword in this example has a block circulant structure. The diagonal rotation matrix Q is defined as:
The codebook can be optimized by choosing rotation matrix Q indexes
An overview of Matrix Pre-coding (column by column vector quantize channel- The codebook is constructed such that the codeword vectors distribute on the n-dimension complex unit sphere uniformly. Additionally, the firs: element of each codeword is set to be real for the next step. The Hausholder matrix can be computed and stored beforehand for small codebooks. Even in the case that there is no quantization error, the reconstructed matrix could be different from the original V by a global phase on each column and this is fine with closed loop MIMO. Example of 2-Transmit Antenna Codebook for Givens Feedback Pre-design the rotation matrix for 2 transmit antennas, and then the rotation matrix is parameterized. A set of parameterized rotation matrixes serves as codebook.
According to an embodiment of the invention a differential index feedback is provided as illustrated pictorially in Avoiding the Impact of Ageing A MIMO feedback channel ageing algorithm in accordance with an embodiment of the invention will now be described, in which receiver ageing beam-former correction is utilized. For a mobile MIMO channel the channel matrix may be time-varying:
A CQICH Support of Differential Encoding Algorithm in accordance with an embodiment of the invention will now be described. For OFDM systems, preferably differential encoding is used to cross multiple sub-carriers to feedback the vector index or other feedback information. The following is an example of a mini-tile modulation scheme for sending back a vector index of zero or one. Preferably this would be transmitted on two sub-carriers. In this case, two different phases are transmitted for vector index zero, and a different arrangement of the same phases is sent for vector index one.
Another example is shown in Another example is shown in In yet another example, shown in Each embodiment is generalizable to an arbitrary number of sub-carriers and/or an arbitrary number of transmit antennas/receive antennas as will be apparent to one skilled in the art. Embodiments provide transmitters adapted to generate signals containing the disclosed transmit code-sets/sub-carrier allocations methods of transmitting such signals, receivers adapted to receive such transmissions, and methods of receiving and decoding such signals. Numerous modifications and variations of the present invention are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims, the invention may be practised otherwise than as specifically described herein. Patent Citations
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