WO2008143973A1 - Structures adaptatives d'un récepteur d'algorithme m de sortie d'un logiciel - Google Patents

Structures adaptatives d'un récepteur d'algorithme m de sortie d'un logiciel Download PDF

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Publication number
WO2008143973A1
WO2008143973A1 PCT/US2008/006286 US2008006286W WO2008143973A1 WO 2008143973 A1 WO2008143973 A1 WO 2008143973A1 US 2008006286 W US2008006286 W US 2008006286W WO 2008143973 A1 WO2008143973 A1 WO 2008143973A1
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Prior art keywords
soma
mimo
ofdm
receiver
paths
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PCT/US2008/006286
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English (en)
Inventor
Carl-Erik W. Sundberg
Haralabos Papadopoulos
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Ntt Docomo, Inc.
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Priority claimed from US12/121,649 external-priority patent/US20090285323A1/en
Application filed by Ntt Docomo, Inc. filed Critical Ntt Docomo, Inc.
Priority to EP08767750A priority Critical patent/EP2149241A1/fr
Priority to JP2010508440A priority patent/JP2010528503A/ja
Publication of WO2008143973A1 publication Critical patent/WO2008143973A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03203—Trellis search techniques
    • H04L25/03216—Trellis search techniques using the M-algorithm
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03305—Joint sequence estimation and interference removal
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03312—Arrangements specific to the provision of output signals
    • H04L25/03318—Provision of soft decisions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
    • H04L2025/03426—Arrangements for removing intersymbol interference characterised by the type of transmission transmission using multiple-input and multiple-output channels

Definitions

  • the present invention relates to the field of wireless communication; more particularly, the present invention relates to adaptive soft output M-algorithm receivers.
  • Future wireless systems require a more effective utilization of the radio frequency spectrum in order to increase the data rate achievable within a given transmission bandwidth. This can be accomplished by employing multiple transmit and receive antennas combined with signal processing.
  • a number of recently developed techniques and emerging standards are based on employing multiple antennas at a base station to improve the reliability of data communication over wireless media without compromising the effective data rate of the wireless systems. So called space-time block-codes (STBCs) are used to this end.
  • STBCs space-time block-codes
  • coded modulation systems can easily be designed by means of an outer binary code, e.g., a convolutional code, and an interleaver in a so called bit-interleaved coded modulation (BICM) system.
  • BICM bit-interleaved coded modulation
  • each of the base stations with data for a particular user as an element (or a group of elements in the case that multiple transmit antennas are present at each base station) of a virtual antenna array suggests using cooperative signal encoding schemes across these base stations to provide diversity benefits to the desired user.
  • the encoded signals are transmitted by spatially dispersed base-stations, they arrive at the receiver with distinct relative delays with one another, i.e., asynchronous Iy. Although these relative delays can, in principle, be estimated at the receiver, they are not known (and thus cannot be adjusted for) at the transmitting base stations, unless there is relative-delay information feedback from the receiver to the transmitting base stations.
  • orthogonal space-time codes can provide full diversity while their optimal decoding decouples to (linear processing followed by) symbol-by-symbol decoding.
  • Full rate OSTBCs exist only for a two transmit-antenna system. For three or more antennas, the rate cannot exceed 3 A symbols/per channel use.
  • the imposed orthogonality constraint yields simple decoding structures, it places restrictions in the multiplexing gains (and thus the spectral efficiencies and throughput) that can be provided by such schemes. [0008]
  • Many MIMO/OFDM systems exploit large-size QAM constellations and
  • a scheme with an inner modified orthogonal STBC can be viewed as a method that provides the OFDM based benefits of a single frequency network while at the same time allowing the full transmit base- station diversity and frequency diversity to be harvested from the system by using distinct coordinated transmissions from distinct base stations together with bit- interleaved coded modulation.
  • a class of schemes that can provide large spectral-efficiencies and reliable transmission includes space-time bit-interleaved coded modulation systems with OFDM. These systems can provide spatial (transmit and receive antenna) diversity, frequency diversity and can cope with asynchronous transmission. Furthermore, by modifying the binary convolutional code to a block with rate compatible punctured convolutional codes, a flexible UEP system can be achieved.
  • One drawback associated with such systems is that the near-optimum receiver can be quite complex (computation intensive).
  • the necessary joint demapper unit inner MAP or MaxLogMAP decoder grows in complexity exponentially with the product of the number of transmit antennas and the number of bits per modem constellation point.
  • a device for use in a wireless communication system includes a transmitter, and comprises of a receiver to receive information-bearing signals from the transmitter wirelessly transmitted using OFDM and bit interleaved coded modulation, where the receiver comprises an inner decoder structure having a soft output M-algorithm (SOMA) based multiple-in multiple-out (MIMO) joint demapper that uses a SOMA-based MIMO detection process to perform joint inner demapping over each subtone.
  • SOMA soft output M-algorithm
  • MIMO multiple-in multiple-out
  • the SOMA-based MIMO joint demapper is operable to identify a best candidate among a number of candidates by searching a detection tree under control of a parameter representing a total number of paths that are extended from each level, such that only a number of best alternatives from every level of the tree are expanded, wherein the SOMA-based MIMO detection process adapts one or more of the parameters based on tone quality.
  • Figure 1 is a flow diagram of one embodiment of a decoding process.
  • FIG. 2 is a block diagram of one embodiment of a transmitter for space-time coding with bit-interleaved coded modulation (BICM) with OFDM modulation for wideband frequency selective channels.
  • BICM bit-interleaved coded modulation
  • Figure 3 is a block diagram of one embodiment of a receiver having an iterative decoder for the space-time code for the OFDM system.
  • FIG. 4 is a block diagram of one embodiment of MIMO demapper
  • Figure 5 illustrates one embodiment of a set partition type mapper.
  • Figure 6 illustrates application of the H matrix and weights to two signals.
  • Figure 7 illustrates another representation of the receiver of Figure 3 in which each MIMO demapper for each subtone is shown.
  • Figure 8 illustrates the decision tree that allows a recursive computation of metrics on a tree in the case that there are three transmit antennas.
  • Figure 9 illustrates an example of a decision tree.
  • Figure 10 is a flow diagram of one embodiment of a process for setting up the SOMA inner decoding operation on a tone.
  • Figure 11 is a flow diagram of the SOMA detection process at a particular depth.
  • Figure 12 illustrates a QR decomposition
  • Embodiments of the present invention relate, in general, to adaptive receiver structures for receiving digital information over wireless systems, with multiple transmit antennas and multiple receive antennas.
  • Embodiments of the present invention deal with flexible and efficient MIMO joint demappers based on improved versions of the soft output M-algorithm.
  • Such adaptive receiver structures may be used in wireless communication environments in which a mobile receives (by use of one or several antennas) a signal that is sent over multiple transmit antennas, and where the transmit antennas may be distributed over multiple base stations (i.e., they are not collocated). In one such system, the transmit antennas are collocated at the same base station.
  • Embodiments of the present invention include reduced complexity receivers for systems that, for example, exploit intelligent wideband transmission of the information bearing signal over the multiple independently fading paths from each transmitting base station to a receiver, in such a way that it provides transmit base station diversity, the frequency diversity available in the transmission bandwidth, receive antenna diversity if multiple receive antennas are employed, and extended coverage.
  • Embodiments of the invention are applicable to systems, where the information-bearing signal is available at multiple base stations, and settings involving a single active base station with multiple transmit antennas.
  • a single base station with multiple transmit antennas is employed for transmission as well as OFDM-based BICM systems.
  • Embodiments of the present invention apply to MIMO/OFDM based systems using bit interleaved coded modulation (BICM) with iterative decoding (ID). These systems can provide full space diversity if another (outer) code with a low enough coding rate is used. If a high-rate code is used, there is a reduction in the degree of space diversity.
  • BICM bit interleaved coded modulation
  • ID iterative decoding
  • wideband transmission based on OFDM and bit-interleaved coded modulation with an outer binary code is used.
  • OFDM Orthogonal frequency division multiplexing
  • BICM Bit interleaved coded modulation
  • ID iterative decoding
  • the inner joint demapper is employed adaptively based on the quality of the OFDM tones.
  • the system can be used with or without an inner orthogonal space-time block code.
  • the present invention is applicable to space time coding schemes for both systems with collocated base stations and non collocated base stations. [0031] In the following description, numerous details are set forth to provide a more thorough explanation of the present invention.
  • these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. [0033] It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities.
  • the present invention also relates to apparatus for performing the operations herein.
  • This apparatus may be specially constructed for the required purposes, or it may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer.
  • a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any type of media suitable for storing electronic instructions, and each coupled to a computer system bus.
  • ROMs read-only memories
  • RAMs random access memories
  • EPROMs electrically erasable programmable read-only memories
  • EEPROMs electrically erasable programmable read-only memory
  • magnetic or optical cards or any type of media suitable for storing electronic instructions, and each coupled to a computer system bus.
  • a machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer).
  • a machine-readable medium includes read only memory (“ROM”); random access memory (“RAM”); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other form of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.); etc.
  • ROM read only memory
  • RAM random access memory
  • magnetic disk storage media includes magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other form of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.); etc.
  • a wireless communication system a first device (e.g., a base station) having a transmitter and a second device having a receiver (e.g., a mobile terminal) to receive information-bearing signals from the transmitter wirelessly transmitted using OFDM and bit interleaved coded modulation is described.
  • the communication system described herein is a coded modulation system that includes transmitters that apply space-time coding with bit-interleaved coded modulation that is combined with a multi-carrier OFDM modulation and receivers that apply OFDM demodulation with iterative demapping and decoding.
  • the systems described herein have N t transmit antennas and N r receive antennas.
  • Each of the N r receive antennas receives signals that are the sum of channel-distorted versions of the signals transmitted from the N t transmit antennas.
  • Such coded modulation systems in accordance with the present invention may be advantageously employed in wireless local/wide area network (LAN/WAN) applications.
  • LAN/WAN wireless local/wide area network
  • the exemplary embodiment is described for space-time coding with bit-interleaved coded modulation, other types of coded modulation for space-time coding may be used.
  • the exemplary embodiments are described for a mapping of the bit-interleaved coded data into symbols using QAM; however, other modulation schemes may be used, such as, for example, but not limited to phase-shift keying (PSK).
  • PSK phase-shift keying
  • the receiver includes circuitry that estimates the values for the elements in channel response matrix H[k], and such estimates may be generated using periodic test (pilot) signals transmitted by the transmitter to the receiver Such a priori information of the channel impulse response may also be generated via simulations.
  • the matrix H[k] denotes the channel response over the kth OFDM tone and is a matrix of dimensions N r by N t .
  • multiple transmit and receive antennas can yield communication links with increased bandwidth efficiency (data rate), extended power efficiency (range), or both.
  • Embodiments of the invention deals primarily with the forward link, i.e., the base-to-mobile transmission direction of transmission. Methods and apparatuses are disclosed for adaptive soft output M- algorithm based receiver structures.
  • a reduced complexity soft output MIMO detector in the receiver makes adaptive use of a modified soft output M-algorithm (SOMA).
  • the soft output MIMO detector is applied for every tone or subchannel in the OFDM system, as well as at every iteration in the decoding process.
  • SOMA modified soft output M-algorithm
  • the soft output MIMO detector is applied for every tone or subchannel in the OFDM system, as well as at every iteration in the decoding process.
  • MAP maximum a posteriori probability
  • the MAP performs a joint demapping function over all the transmit antennas and over all the involved QAM constellation symbols and bits. Often the asymptotically optimum but much simpler exhaustive MaxLogMAP detection algorithm is used.
  • the SOMA detector only uses a fraction of the total number of candidates in its MIMO detection process, thus the considerable complexity reduction. There is of course a tradeoff between the performance and the degree of complexity reduction.
  • the SOMA is used adaptively, in that the amount of computation allocated to each SOMA module (one per OFDM tone) is adapted to the channel conditions (on the given OFDM tone) in order to optimize the overall complexity-performance trade-offs of the receiver.
  • a SOMA detector performs a
  • the number of candidates explored in the SOMA detection process is controlled by the parameter (M) that indicates the number of paths that are extended from each node or level in the detection tree.
  • M the number of paths that are extended from each node or level in the detection tree.
  • M the number of paths that are extended from each node or level in the detection tree.
  • M the number of paths that are extended from each node or level in the detection tree.
  • this value is denoted T and is used in the soft output value calculation by the algorithm.
  • the number of inner/outer decoder iterations, I also affects the total decoding complexity and the associated performance.
  • the parameters M and T and/or I are selected adaptively for the best overall performance for a given total complexity level, with the quantity that guides the adaptivity being the quality of the different OFDM tones. For example, a high signal level or alternatively a large signal to noise ratio (SNR) for a certain tone means a good quality level for that tone.
  • the SOMA detection process performs decoding with a lower value of M, a lower value of T and potentially a lower value of I.
  • the SOMA detection process performs decoding with higher values of M, T and I for the best use of the overall complexity.
  • the adaptivity can also be extended over time, i.e. over successive OFDM symbols.
  • the space-time coding system described herein comprises OFDM for wideband transmission, MIMO and large QAM constellations for high spectral efficiency, a bit interleaver for the bit-interleaved coded modulation scheme (BICM) and an outer binary code.
  • the overall detection is typically performed iteratively. This requires that both the inner MIMO demapper and the outer decoder perform soft in soft out (SISO) detection/decoding.
  • the outer code is less critical in terms of complexity.
  • the MEMO detector in principle works with any binary outer code.
  • This code could be a turbo code, an LDPC code, a regular convolutional code or an RCPC code.
  • the decoder for the outer code is preferably a soft in soft out (SISO) type decoder, for example a MAP decoder.
  • SISO soft in soft out
  • the outer decoder supplies soft information to the inner MEMO detector for iterative decoding.
  • Figure 1 is a flow diagram of one embodiment of a decoding process.
  • the process may be performed by processing logic that may comprise hardware (e.g., dedicated logic, circuitry, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both.
  • the decoding process is performed by a receiver in the wireless communication system.
  • the process begins by processing logic evaluating quality of individual OFDM tones received by a receiver in a wireless communication system (processing block 101). The quality of the individual OFDM tones/subchannels is evaluated/estimated at the receiver. In one embodiment, the quality of OFDM tones is based on signal level. In another embodiment, the quality of OFDM tones is based on signal-to-noise ratio (SNR).
  • SNR signal-to-noise ratio
  • processing logic After evaluating the quality of OFDM tones, processing logic performs a first decoding operation to produce a first set of output data representing most likely decision values for the transmitted bits and reliability values for these decisions, including performing a SOMA-based MIMO detection process over each subtone for disjoint inner demapping, in which a best candidate is identified among a number of candidates by searching a detection tree under control of a parameter representing a total number of paths that are extended from each level, such that only a predetermined number of best alternatives from every level of the tree are expanded (processing block 102).
  • performing decoding comprises calculating soft output values at every level by computing a metric difference between the estimated best path at that level and each of all or a subset of early-terminated paths at that level, and whereby each such metric difference is used to update bit locations for which two paths (based on which the metric difference is computed) disagree in value.
  • a soft-in soft-out (SISO) outer decoder uses the soft output values from the inner SOMA-based MIMO joint demapper to produce output data and feeds soft values back to the inner decoder structure for iterative decoding.
  • a soft-input hard-output Viterbi decoder uses the soft output values from the inner SOMA-based MIMO joint demapper to produce hard output data for non- iterative decoding. Note that in such a case, a simpler outer decoder is used to produce the hard outputs.
  • the SOMA-based MIMO detection process is adapted based on the number of early-terminated paths in the tree (T), which are used in soft-output value calculations. In another embodiment, the SOMA-based MIMO detection process is adapted based on the number of iterations for each tone based on tone quality. In yet another embodiment, the SOMA-based MIMO detection process is adapted during each iteration and for every tone based on tone quality. In another embodiment, the SOMA-based MIMO detection process adapts one or more of the parameters, a number of early-terminated paths in the tree, and a total number of iterations based on tone quality.
  • processing logic After performing the first decoding operation, processing logic performs a second decoding operation with a binary outer coder (processing block 103).
  • the outer decoder comprises a MAP decoder for the associated convolutional code used as an outer encoder in the transmission system.
  • the outer decoder may comprise a conventional optimal or suboptimal decoder for a rate- compatible punctured convolutional (RCPC) code, a turbo code and a LDPC code, when such a binary code is used as an outer encoder in the transmission system.
  • RCPC rate- compatible punctured convolutional
  • Figures 2 and 3 show the transmitter and receiver block diagrams for a
  • FIG. 2 is a block diagram of one embodiment of a transmitter for space-time coding with bit-interleaved coded modulation (BICM) with OFDM modulation for wideband frequency selective channels.
  • transmitter 200 comprises convolutional encoder 201, bit interleaver 202, serial-to-parallel converter 203, mapper modems 207!-207Nt, inverse fast Fourier transform (IFFT) modules 208 I -208 NI , and transmit antennas 209 r 209 NI -
  • IFFT modules 2081 -208Nt also include circular-prefix operations, which are performed in a manner that is well known in the art.
  • convolutional coder 201 applies a binary convolutional code to the input bits (input data) 210.
  • Bit interleaver 202 then interleaves the encoded bits from convolutional coder 201 to generate bit-interleaved encoded bits. This bit interleaving de-correlates the fading channel, maximizes diversity, removes correlation in the sequence of convolutionally encoded bits from convolutional coder 201, and conditions the data for increased performance of iterative decoding.
  • Convolutional coder 201 and bit interleaver 202 may typically operate on distinct blocks of input data, such as data packets.
  • Serial-to-parallel converter 203 receives the serial bit-interleaved encoded bit stream from bit interleaver 202. Note that serial-to-parallel converter 203 may include a framing module (not shown) to insert framing information into the bit stream, which allows a receiver to synchronize its decoding on distinct blocks of information. Serial-to-parallel converter 203 generates a word of length N t long, with each element of the word provided to a corresponding one of mapper modems 2071 -207 Nt - Elements of the word may be single bit values, or may be B bit values where B is the number of bits represented by each modem constellation symbol.
  • the output of each modem mapper 207 is a symbol.
  • Each of IFFT modules 208i-208N t collect up to F symbols, and then apply the IFFT operation of length F to the block of F symbols.
  • F is an integer whose value can typically range from as small as 64 to 4096, or larger and depends on the available transmission bandwidth, the carrier frequency, and the amount of Doppler shifts that need to be accommodated by the system.
  • each of IFFT modules 208 1 - 208 Nt generate F parallel subchannels that may be transmitted over corresponding antennas 209 !-209N t -
  • Each subchannel is a modulated subcarrier that is transmitted to the channel.
  • the binary information bearing signal hereby denoted as Uk, is encoded first at the transmitter by an outer binary code using convolutional coder 201, generating a coded sequence Q > This sequence is interleaved by a pseudorandom bit interleaver 202. Then, each of mapper modems 207!-207Nt maps groups of B interleaved bits at a time into 2 ⁇ -QAM symbols.
  • the resulting QAM symbols are multiplexed through the Ntransmit antennas 209!-209Nt in a round-robin fashion and OFDM transmission is applied over each antenna using IFFT modules 208 ! -208 NI .
  • s k [ «] the QAM symbol transmitted by antenna k on tone n, and via b f [n] thelth out of the B bits is used as input in one of mapper modems 207 I -207 NI to produce s k .
  • mapper modems 207 I -207 NI maps(b k [n]) (1)
  • map denotes the mapper operation
  • FIG. 3 is a block diagram of one embodiment of a receiver having an iterative decoder for the space-time code for the OFDM system.
  • receiver 300 comprises receive antennas 301 I -301N ⁇ , fast Fourier transform (FFT) modules 302 I -302 N ⁇ , demodulator/detector 303, parallel-to-serial converter 307, bit deinterleaver 308, maximum a posteriori (MAP) decoder 309, bit interleaver 310, and serial-to-parallel converter 311.
  • FFT fast Fourier transform
  • demodulator/detector 303 demodulator/detector 303
  • parallel-to-serial converter 307 parallel-to-serial converter 307
  • bit deinterleaver 308 maximum a posteriori (MAP) decoder 309
  • bit interleaver 310 bit interleaver
  • serial-to-parallel converter 311 serial-to-parallel converter
  • receiver 300 performs OFDM demodulation for each of receive antennas 301 ⁇ . ⁇ ⁇ , and the demodulation and demapping is performed over F parallel subchannels.
  • the ith receive antenna 301 (i) senses a signal made up of various contributions of the signals transmitted from the N t transmit antennas (i.e., contributions of the multiple F parallel, narrowband, flat fading subchannels transmitted over corresponding antennas 209!-209N t of Figure 2).
  • Each of FFT modules 302 ! -302 N ⁇ apply an F-point FFT to the corresponding signals of receive antennas 301 ! -301 N r, generating N 1 - parallel sets of F subchannels.
  • demodulator/detector 303 estimates bits in each of the F subchannels (slowly varying with flat fading) rather than in only one subchannel as in the narrowband, flat fading systems of the prior art.
  • Demodulator 304 demodulates F subchannel carriers to baseband for each of the N r parallel sets of F subchannels.
  • Multi-input multi-output (MIMO) demapper 305 based on the N r parallel sets of F subchannels from FFT modules 302 ! -302 N ⁇ produces MAP estimates of the demapped bits (i.e, bits mapped from the constellation symbol) in each of the F subchannels from the N t antennas in the transmitter.
  • MIMO demapper 305 produces the estimates of the demapped bits and reliability information about these bits using reliability information generated by soft-output decoding (followed by reinterleaving) by MAP decoder 309.
  • MIMO demapper 305 computes soft values for bits transmitted on the overlapping F subchannels, along with an estimate (approximation) of the a posteriori probability of the soft value being correct. This is performed in a manner well-known in the art. [0059]
  • FIG 4 is a block diagram of one embodiment of MIMO demapper 305 having MIMO joint demapper units for the different OFDM tones/subchannels.
  • each signal of the N r receive antennas 301 I -301 N ⁇ is divided into F subchannels (via demodulator 304, not shown in Figure 4) by applying the FFT and sent to corresponding subchannel MIMO demappers 401 I -401 F -
  • the signal outputs of the kth subchannel for all N r receive antennas are provided to the kth subchannel MIMO demapper 401(k), reliability information using extrinsic information generated from the output of MAP decoder 309 of the previous iteration.
  • the extrinsic information is exchanged between MIMO demapper 305 and MAP decoder 309 to improve the bit error rate performance for each iteration.
  • Methods for computing the extrinsic information in such inner/outer decoder settings are well-known in the art.
  • the extrinsic information is computed as follows. First, the soft-output is computed by the MAP outer decoder, and from it the input reliability information (input to the same outer decoder) is subtracted off in order to compute the extrinsic information produced by MAP decoder 309. This extrinsic information is deinterleaved and passed as input to MIMO demapper 305 in the next iteration.
  • MIMO demapper 305 together with reliability values for those bits are provided to parallel-to-serial converter 307 along with the extrinsic reliability information on each one of these bits.
  • the reliability information is computed as the difference between the output reliability values for those bits (produced by demapper 305) and the input reliability values for those bits (inputs to demapper 305).
  • the converter 307 reconstitutes the estimate of the BICM encoded bit stream generated by the transmitter, which was estimated by the receiver 300.
  • the estimated BICM encoded bit stream (and the extrinsic reliability information) is then deinterleaved by bit deinterleaver 308 and applied to MAP decoder 309 to reverse the convolutional encoding applied by the transmitter.
  • the reverse operation in this case corresponds to generating estimates of the bit values of the information bit stream that is the input to convolutional coder 201, and also producing extrinsic information that is to be passed back (after reinterleaving) to MEvIO demapper 303 as new reliability information.
  • the MAP decoding process generates soft output values for transmitted information bits in a manner that is well known in the art.
  • the extrinsic information from MAP decoder 309 is first applied to bit interleaver 310.
  • Bit interleaving aligns elements of the extrinsic information with the interleaved estimated BICM encoded bitstream from MIMO demapper 305.
  • the interleaved extrinsic information is applied to serial-to-parallel converter 311, which forms N t parallel streams of extrinsic information corresponding to the parallel bit streams formed at the transmitter.
  • the extrinsic information is exchanged between MIMO demapper 305 and MAP decoder 309 to improve the bit error rate performance for each iteration.
  • a MaxLogMAP-type approximation is used to compute bit-LLR values for each bit location.
  • an improved Max-Log approximation for calculation of LLRs can be used in both MIMO demapper 305 and in MAP decoder 309 associated with the convolutional code used as an outer encoder in the transmission scheme.
  • ) when calculating updated forward recursive, reverse recursive, and branch metrics sequences to calculate the LLR.
  • Each constituent MIMO demapper 305 or MAP decoder 309 thus calculates the max* term by separate calculation of a max term (max(x,y)) and a logarithmic correction term (log(l+e " ' x"yl )).
  • Figure 5 illustrates one embodiment of a so called set partition type mapper for 16QAM for use in iterative decoding.
  • This type of mapper is suitable for BICM with iterative decoding (ID) in contrast to the Gray mapper which is suitable for a non-iterative decoding process.
  • the samples from each receive antenna and on each tone are passed through an inner/outer soft-in soft-out decoder structure for decoding shown in Figures 3 and 4, which are described above.
  • the outer decoder is an optimal (soft-in soft-out) BCJR decoder.
  • the complexity of the near-optimal receivers associated with these types of coded OFDM/BICM/OFDM systems resides in the inner decoder of the receiver structure in Figure 3.
  • the received signal sample on the mth receive antenna and the «th tone can be expressed as where h mk [n] denotes the effective channel gain between the Ath transmit and the mth receive antenna on the nth tone, vwn[n] denotes the associated thermal noise term on the mth antenna and nth tone.
  • CSI channel state information
  • the complexity measure C indicates the number of terms needed in order to form the log-likelihood ratio (LLR) in the joint demapper (inner decoder).
  • the receiver uses a modified version of the soft output M-algorithm (SOMA).
  • SOMA soft output M-algorithm
  • the SOMA is well known in the art; see for example, Wong, "The Soft Output M-algorithm and its applications", Ph.D. Thesis, Queens University, Scientific, Canada, August 2006, incorporated herein by reference.
  • the modified soft output M-algorithm (SOMA) is used adaptively.
  • the M-algorithm is well known in the art and is described in Lin & Costello, "Error Control Coding, 2 nd Edition," Prentice Hall, New York, 2003.
  • the joint demapper uses the modified SOMA for finding the best alternative among an exponentially growing population of candidates by doing a reduced search in a detection tree. This is done by expanding only the M best alternatives from every level of the tree rather than all alternatives.
  • the M best alternatives are determined using a metric.
  • the metric is so called MaxLogMAP type metric, such as described in Lin & Costello, "Error Control Coding, 2 nd Edition," Prentice Hall, New York, 2003, which is well-known in the art.
  • the joint demapper calculates soft output values by comparing the estimated best path with the best alternative paths branching off the best path. These paths though the levels of the tree could be terminated at the end of the tree (there are M such paths) or non-terminated at every level (there are T early-terminated paths). That is, the SOMA detection process performs these soft output calculations iteratively during the tree search in the algorithm, whereby at each depth in the tree it uses early terminated paths at that depth and the best candidate at the same depth for computing reliability values for all the bit locations that is possible.
  • the soft output values from the inner SOMA-based MIMO joint demapper are then used by the soft in soft out (SISO) decoder for the outer binary code.
  • This decoder in rum feeds soft values back to the inner decoder in an iterative turbo- type iterative decoding.
  • a soft-input hard-output Viterbi decoder i.e., a simpler outer decoder uses the soft output values from the inner SOMA-based MIMO joint demapper to produce hard output data for non-iterative decoding.
  • the inner decoder is channel-adaptive.
  • Such channel-adaptive versions of SOMA inner decoders save in complexity (with respect to the base SOMA designs) without appreciable reduction in performance, as well as being optimizable for a given channel realization to a desired target BER performance.
  • the SOMA algorithm computes (estimated) symbol decision values and reliability information for the associated bit estimates by first turning the computation above into a computation on a tree and then performing approximate maximization computations by limiting the search through the tree.
  • the focus is on the SOMA operating on a fixed but arbitrary
  • F*"' denote the associated permutation matrix, i.e., the matrix yielding s (n) -P * s .
  • the full-search MaxLogMAP can be readily implemented based on the above set of measurements via a search on a tree.
  • the k first equations are considered from equation (4) to rank candidates.
  • the sets of candidates are ranked in groups whereby each group corresponds to all the N-symbol candidates that have the same symbol values in the first k symbols in the order described by ⁇ .
  • the quantities T (5,5) can be readily implemented recursively via a full tree-search on a tree of depth N and 2 B branches per node.
  • the SOMA algorithm in essence, performs a limited MaxLogMAP- metric based search on the tree. Like any M-algorithm, from all surviving candidates at any given level, all possible candidates are expanded to the next level (2 B M in this case), but only a subset M of those is kept for search at higher depths in the tree.
  • An important element of the SOMA is that it recursively generates and updates quality metric estimates for each value of each of the NB bits represented on the tree.
  • I P ⁇ r' ⁇ + l ⁇ r ⁇ M + N lerm > are still used before they are discarded for producing relative reliability updates for the bits and bit values they represent by updating the associated locations in ⁇ 0 ' and ⁇ * 1 ' .
  • the SOMA first chooses the surviving length-Npath with the best accumulated metric as the hard estimate.
  • This NxI vector of QAM symbol estimates is used to directly demap and obtain hard estimates for the NB bits
  • Reliability metrics are
  • each decoder computes extrinsic information that is passed as input (appropriately deinterleaved in the case of the MIMO demapper, and reinterleaved in the case of the outer MAP decoder) to the other decoder.
  • the extrinsic information is computed as the difference between the soft output information produced by the decoder (e.g., in the case of MIMO demapper see equation (7)), and the input intrinsic information to the decoder.
  • the metric used for SOMA decoding shown in equation (6) is modified to include an extrinsic term.
  • another term is added to the right hand side of equation (6), which is a sum of terms, one term for each bit location in the binary representation of the symbol 5 .
  • differential reliability values are employed, the term added that corresponds to any given, but fixed, bit location, equals zero if the bit- value of that bit location in 5 is O, and equal to the differential input reliability value otherwise.
  • Figures 6A and 6B illustrate the operation of the MIMO demapper for one subtone for a simple 2x2 example.
  • the yi and y 2 signals are generated from the symbols s t and S 2 from first and second antennas. This occurs in a well-known fashion according to the following:
  • the MIMO demapper receives y ⁇ and y 2 signals and returns estimates of the bits represented by the symbols S 1 and S 2 , for one subtone as shown in Figure 6B. In addition, soft-output (reliability information) is provided on the set of estimated bits.
  • FIG. 7 illustrates another representation of the receiver of Figure 3 in which each
  • This structure allows the computation of each of the metrics in (6) to be performed on a tree.
  • leafs for each possible value of s 2 are extended, and the second term (branch metric) in the sum in equation (6) is computed and added to 1 st term corresponding to the particular value of S 1 .
  • each node represents a computation of (6) for a specific vector symbol candidate. Those can thus be compared as in (5) to provide bit estimates and reliability information for all the bits represented by the QAM symbol vector.
  • the SOMA algorithm does not search the full tree, but rather a limited set of paths. The way the paths are limited is to start expanding paths from the root of the tree and at each level keeping only a subset of the paths as surviving paths (i.e., as paths that will be further extended).
  • a decision is made to expand the tree for only the M best branches. This decision can be based by calculating the parial distance metric for each candidates.
  • the complexity of the inner SOMA decoder is controlled by the values of the parameters M (the number of best paths) and T (the early-terminated paths).
  • the overall complexity is also controlled by the number of times the inner decoding algorithm is used, which, in turn, is determined by the number of OFDM tones and the number of iterations (I) used for iterative decoding.
  • Figure 10 is a flow diagram of one embodiment of a process for setting up the SOMA inner decoding operation on tone n.
  • the process is performed by processing logic that may comprise hardware (e.g., circuitry, dedicated logic, etc.), software (such as is run on a general purpose computer system or a dedicated machine), or a combination of both.
  • the process is performed on each tone.
  • first channel measurements are used (based on pilot signals) to estimate the channels between all transmit-receive antenna pairs on any given tone f (this would correspond to estimating the channel matrix H[fJ) (1001).
  • the channel estimation and SNR computation are based on pilot measurements on OFDM tone f (1031).
  • the channel estimates and lookup table (LUT) 1005 are used to set up the adaptivity (e.g., changing M, T of the I) of SOMA.
  • these measurements are used to set up the QR- decomposition of the channel matrix, set up the SOMA detection tree (1003), and select (e.g., by means of a lookup table) the parameters of the SOMA algorithm (1004). As the flow diagram reveals, the selection of these parameters depends on the channel conditions. Then, once the QR-decomposition (1002), detection tree (1003), and SOMA parameters have been set (1004), the measured data on all receive antennas on tone f (1032) are processed through a QR-decomposition (1002) to generate a set of effective channel measurements, the tree is constructed (1003) and then the SOMA inner detection algorithm is implemented. The SOMA is implemented on OFDM tone f using SOMA parameters on tone f provided by LUT 1005.
  • the output of LUT 1005 may provide one or more variable values of the SOMA parameters on tone f, namely M, T (1032), and the number of inner-outer soft-output decoder iterations, namely I (1033). That is, LUT 1005 may specify the value of M (when M is adaptive) while the values of T and I are unchanged (non-adaptable), or the value of T (where T is adaptable) while the value of M and I are unchanged (non-adaptable). The same could occur for 2 or more of the values of M, T and I. These values may be changed at different depths/levels of the tree, such that adaptation occurs over different levels. In such a case, adaptation occurs based on tone quality and on depth.
  • a LUT is not used and the values are changed in the SOMA algorithm itself.
  • certain values may change based on whether the group of the paths with the best metrics have metrics that are clustered together, such that those in the cluster (more or less than M) or having values within acertain percentage of the worst metric in the cluster (e.g., with 95% of the value of the lowest quality metric in the cluster) are permitted to continue to the next level/depth in the tree.
  • the resulting set of survivors may have cardinality more or less than M.
  • the process may keep as survivor paths, all the paths whose relative metrics are within a certain percentage (e.g., 95%) of the metric of the best path.
  • the outputs of the SOMA inner detection algorithm are bit estimates, bit relativity information and bit extrinsic information.
  • the main input is the set of survivors at depth n-1 and the metrics of these survivor paths (1101).
  • all the possible length-1 extensions of each of these length-"n-l" paths are constructed based on the survivors of the pervious depth and their metrics (1101) to generate the set of all length-n paths that will be visited by the algorithm.
  • the survivor metrics at depth n-1 (1101) and the effective measurement at depth n (1102) are used to compute the length-n metrics (1104) of these length n paths that are constructed at 1103.
  • the paths are then sorted based on their metric quality (1105).
  • the M paths with the best metrics are chosen as survivors at depth n (1112), in the same manner as the well-known SOMA process.
  • the rest of the paths are put in the list of the paths that are terminated (1107).
  • a relative metric is computed (1109) with respect to the best path at length n (which, obviously is a survivor path).
  • its relative metric is compared against a subset of entries in the bit- LLR (Least Likelihood ratio) table to decide whether or not that entry is to be updated.
  • the (k,m) entry of ⁇ (0) is updated (1108); else the (k,m) entry of ⁇ (1) is only updated (1108).
  • the entry gets updated if the relative metric provided by the new path improves the metric in the associated entry in the LLR table.
  • the output is updated bit-LLR tables (1111).
  • the different SOMA detectors are used for the different tones and are selected adaptively based on the quality of the tones.
  • the M-value can be lowered and/or the T- value can be lowered and/or the I value can be lowered.
  • a (precomputed) lookup table can be employed that lists the value of M (and T) that should be used for set of SNR (or signal level) ranges. This approach yields lower relative complexity for that particular SOMA detector.
  • M and T
  • SNR signal level
  • the allocation of complexity may be done over successive OFDM symbols, i.e., over time. For instance, resources could be jointly allocated over frequency (OFDM tone) as well as time, so that the complexity does not exceed a predetermined value over a block of OFDM symbols.
  • the value of M is changed inside one SOMA detector, i.e., search the tree with a variable number of expanded paths as well as a variable number of used early terminated paths at each level in the soft output calculations.
  • a metric correction term is applied for the soft output M-algorithm, much the same as the one used in the corrected SOVA algorithm described in S. Lin and D.J. Costello Jr., "Error Control Coding, 2 nd Edition", Prentice Hall, New York, 2003 and Kitty Wong, "The Soft Output M-algorithm and its applications", Ph.D. Thesis, Queens University, guitarist, Canada, August 2006. [0092] Note that the techniques described herein for a low complexity receiver need not be limited to a system employing OFDM modulation.
  • One advantage of embodiments of the present invention is that it provides a method for a high performing inner joint demapper with soft output, with an overall complexity that makes it implementable in an iterative decoding setting for N and B values for which the MaxLogMAP is not implementionally feasible or practical with today's technology.
  • Such embodiments include one or more of the following elements:
  • An OFDM based system with one MIMO detector for each tone where the complexity reduction in the SOMA based detector is implemented adaptively with the quality of each tone, yielding the best overall complexity for a certain performance level.
  • a SOMA detector for each tone where the M and the T values are chosen adaptively based on the tone quality, and where the number of iterations for iterative-decoding are also chosen adaptively based on the tone quality.
  • the M value may vary over the decoding tree.
  • Adaptive resource and complexity allocation may also be done over successive OFDM symbols, i.e., over time;

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Abstract

L'appareil et le procédé décrits sont destinés à des structures adaptatives d'un récepteur d'algorithme M de sortie d'un logiciel. Dans un mode de réalisation, un dispositif pour une utilisation dans un système de communication sans fil comprend un émetteur, et se compose d'un récepteur pour recevoir des signaux de support d'informations provenant de l'émetteur sans fil transmis en utilisant OFDM et une modulation codée entrelacée binaire, où le récepteur comprend une structure de décodeur interne possédant un extracteur commun d'entrée multiple sortie multiple (MIMO) basé sur un algorithme M de sortie d'un logiciel (SOMA) qui utilise un processus de détection MIMO basé sur SOMA pour réaliser une extraction interne commune sur chaque sous-ton. L'extracteur commun MIMO basé sur SOMA est exploitable pour identifier un meilleur candidat parmi un certain nombre de candidats en recherchant un arbre de détection sous le contrôle d'un paramètre représentant un nombre total de voies qui sont étendues à partir de chaque niveau, de telle sorte que seul un certain nombre de meilleures alternatives à partir de chaque niveau de l'arbre soit étendu, le processus de détection MEvIO basé sur SOMA adaptant un ou plusieurs des paramètres sur la base de la qualité de ton.
PCT/US2008/006286 2007-05-18 2008-05-16 Structures adaptatives d'un récepteur d'algorithme m de sortie d'un logiciel WO2008143973A1 (fr)

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