EP4309312A1 - Dispositif et procédé d'accès aléatoire massif - Google Patents

Dispositif et procédé d'accès aléatoire massif

Info

Publication number
EP4309312A1
EP4309312A1 EP21719118.8A EP21719118A EP4309312A1 EP 4309312 A1 EP4309312 A1 EP 4309312A1 EP 21719118 A EP21719118 A EP 21719118A EP 4309312 A1 EP4309312 A1 EP 4309312A1
Authority
EP
European Patent Office
Prior art keywords
dictionary
sequences
sections
transmitting device
transmitting
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP21719118.8A
Other languages
German (de)
English (en)
Inventor
Zoran Utkovski
Patrick AGOSTINI
Martin Kasparick
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Huawei Technologies Co Ltd
Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
Original Assignee
Huawei Technologies Co Ltd
Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Huawei Technologies Co Ltd, Fraunhofer Gesellschaft zur Forderung der Angewandten Forschung eV filed Critical Huawei Technologies Co Ltd
Publication of EP4309312A1 publication Critical patent/EP4309312A1/fr
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0041—Arrangements at the transmitter end
    • H04L1/0042—Encoding specially adapted to other signal generation operation, e.g. in order to reduce transmit distortions, jitter, or to improve signal shape
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/63—Joint error correction and other techniques
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0047—Decoding adapted to other signal detection operation
    • H04L1/0048—Decoding adapted to other signal detection operation in conjunction with detection of multiuser or interfering signals, e.g. iteration between CDMA or MIMO detector and FEC decoder
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0047—Decoding adapted to other signal detection operation
    • H04L1/005—Iterative decoding, including iteration between signal detection and decoding operation
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/47—Error detection, forward error correction or error protection, not provided for in groups H03M13/01 - H03M13/37
    • H03M13/51—Constant weight codes; n-out-of-m codes; Berger codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas

Definitions

  • the present disclosure relates generally to the field of wireless communications, particularly to random access scenarios between multiple transmitters and a receiver in a wireless communication system.
  • Wireless communications in modern society often involve a large number of users, who send messages randomly and intermittently.
  • two communication protocols for radio access are distinguished.
  • the first one is grant-based random access, where, in the first step, the active users are identified and the cellular network then performs scheduling and allocates transmission resources to the active users.
  • grant-free random access protocol on the other hand, the active users transmit their data right away without awaiting the grant approval. Grant-free random access protocols may be beneficial for massive random access for IoT where, due to the sporadic transmissions and the short messages, grant-based protocols may be inefficient.
  • Constellation design which prescribes how the information messages of the individual users are mapped to their corresponding transmit symbol vectors, is one of the major challenges for such massive random access scenarios.
  • constellation design encompasses both channel code design and modulation, and may be understood as a form of coded vector modulation.
  • random access schemes can be divided into coherent and noncoherent, depending on the assumptions regarding the availability and acquisition of channel state information at the transmitter and receiver side.
  • coherent schemes channel resources are explicitly reserved for channel estimation by dividing the symbol vector from each transmitter into a pilot part and a data part. Besides serving the purpose of channel estimation, the pilot part is also used to separate the transmitters. The data part is used to carry message information.
  • non-coherent schemes no channel estimation is performed and, as result, there is no explicit division of the transmit symbol vectors into a pilot part and a data part
  • the explicit use of pilots to enable user identification and channel estimation may come with a substantial overhead.
  • non coherent schemes are of particular relevance, as they come with reduced overhead and thus yield more efficient utilization of the valuable network resources.
  • the different constellations can be evaluated in terms of probability of a decoding error for a given number of supported users, and also reciprocally in terms of a number of supportable users for a given probability of decoding error.
  • the existing schemes are rather complex to implement, and the performance degrades rapidly when the number of users increases.
  • an objective is to provide an encoder that can be shared among multiple users.
  • Another objective is to allow a decoder with a reasonable complexity to be able to recover messages from the users with an improved performance.
  • the scheme can operate in both coherent and non-coherent fashion.
  • a first aspect of the disclosure provides a transmitting device, configured to: encode a message sequence using one or more error correction codes to obtain G encoded sequences, wherein each encoded sequence has a length of J bits, where J and G are positive integers; map the G encoded sequences using G sections of a dictionary A to obtain a transmitting signal, wherein the dictionary A is a n X JL complex matrix comprising L sections, each section comprising J columns, where n is a positive integer and L is an integer greater or equal to G; and transmit the transmitting signal on a set of time-frequency resources to a receiving device.
  • Embodiments of this disclosure propose an improved design of a transmitting device in a communication network.
  • the communication network may comprise multiple transmitting devices that transmit to the same receiving device.
  • the dictionary A of size n X JL which can be shared among users (including transmitting devices and the receiving device), is proposed in this disclosure for communicating information of the users over channels.
  • the one or more error correction codes comprise a binary constant weight code (CWC).
  • CWC binary constant weight code
  • the transmitting device may encode the message sequence using a binary CWC.
  • the weight of any coded message sequence which may be defined as the number of Is in a bit representation of a codeword, is fixed and constant.
  • the message sequence comprises B information bits, B being a positive integer
  • the transmitting device is further configured to: split the message sequence into g groups, each group comprising q information bits, where g and q are positive integers; convert each group to an integer less than 2 q ; encode g integers using a non-binary code to obtain G integers, where G > g; and encode G integers using a CWC of a length J and a weight w to obtain the G encoded sequences, wherein each encoded sequence comprises w non-zero bits and J - w zero bits, where w is an integer and 1 ⁇ w ⁇ J.
  • the constant weight code may have a size that is greater or equal to 2 q .
  • the above procedure describes in effect that the encoded message sequences may be obtained as a concatenation of two codes.
  • the first code is a CWC of the length J and the weight w.
  • the second code is a non-binary code over the Galois field GF(2 q ) of the length G.
  • the resulting encoded message sequences are themselves binary vectors of a length JG and a weight Gw, i.e., they represent codewords of another CWC of the length JG and the weight Gw.
  • the weight w of each of the G encoded sequences will be 1 (one). That is, each encoded sequence comprises one non-zero bit and the rest of the bits are zero.
  • G may be selected to be equal to g, i.e., in this case g integers are uncoded.
  • the non-binary code comprises at least one of a Reed Solomon code and a non-binary low-density parity check (LDPC) code.
  • LDPC non-binary low-density parity check
  • the transmitting device may use a Reed Solomon encoder or a LDPC encoder to obtain G integers.
  • each column of the dictionary A is a sequence from a Gabor frame.
  • the decoding complexity scales linearly with the size of the design matrix.
  • a dictionary design based on Gabor frames is proposed in this disclosure.
  • multiplications with Gabor frames (and their adjoints) can be efficiently carried out using algorithms such as fast Fourier transform (FFT).
  • FFT fast Fourier transform
  • the Gabor frame is constructed based on a seed vector.
  • the Gabor frame is constructed based on an Alltop seed vector.
  • Gabor frames may be completely specified by a total of numbers that describe the seed vector, and can be effectively generated as time-frequency translates of the seed vector.
  • an Alltop sequence may be chosen as a seed vector.
  • a Gabor frame construction based on an Alltop seed vector (Alltop window) may be particularly attractive due to its coherence properties.
  • the dictionary A may use a design other than a Gabor frame.
  • the dictionary A is one of a Gaussian design matrix, a Walsh-Hadamard matrix, a matrix constructed with Delsarte-Goethals frame sequences, and a matrix constructed with Grassmannian frame sequences.
  • the G sections of the dictionary A comprise at least one of: one or more sections dedicated to the transmitting device, and one or more sections shared among the transmitting device and one or more other transmitting devices.
  • Each section of the dictionary A may be considered either as dedicated to a particular user, i.e., to one transmitting device, or as shared among multiple or all transmitting devices. This choice may be made preliminary to the communication.
  • the transmitting devices may encode their message sequences by using the same constellation. As described in the embodiments, this code can be a binary CWC.
  • This scenario is referred to as an unsourced random access scenario.
  • the receiving device identifies the transmitted symbols, without performing association with the identity of the transmitters.
  • each transmitting device makes use of one section from the dictionary A. This scenario is here referred to as sourced random access scenario, and the receiving device can recover the identity of the transmitting device through the section identity, since each section is dedicated to one transmitting device.
  • the transmitting device is configured to select the G sections from the L sections of the dictionary A by performing a random selection or following an indication, wherein the indication is received from the receiving device and is indicative of indices of the G sections in the L sections of the dictionary A.
  • the transmitting device may select at random one or more sections of the dictionary A that are used for transmission.
  • the receiving device may inform a particular transmitting device about which section of the dictionary A is assigned to it.
  • a second aspect of the disclosure provides a receiving device, configured to: receive a plurality of signals; obtain a reconstructed signal based on the plurality of received signals; process the reconstructed signal by detecting one or more sequences from a dictionary A to obtain soft information on encoded sequences, wherein the dictionary A is a n X JL complex matrix comprising L sections, each section comprising J columns, where n, J and L are positive integers; estimate one or more message sequences based on the soft information on the encoded sequences, wherein each estimated message sequence corresponds to a particular signal of the plurality of received signals; obtain prior information based on the estimated one or more message sequences; re-process the reconstructed signal based on the prior information to obtain updated soft information on the encoded sequences; and re-estimate the one or more message sequences based on the updated soft information on the encoded sequences.
  • Embodiments of this disclosure further propose a receiving network device, which may receive data from a plurality of transmitting devices, and can operate accordingly as described in first aspect and its implementation forms.
  • the proposed dictionary A of size n x JL can be shared among all users (including all transmitting devices and the receiving device).
  • the proposed transmission schemes can be combined with receiver processing performed by two receiver modules.
  • the first receiver module aims at detecting the one or more sequences from the dictionary A.
  • the second receiver module outputs individual messages of active users (transmitting devices) by taking into account the code structure.
  • the receiver processing can be implemented by iteratively exchanging soft information between these two receiver modules.
  • each column of the dictionary A is a sequence from a Gabor frame.
  • the Gabor frame is constructed based on a seed vector.
  • the Gabor frame is constructed based on an Alltop seed vector.
  • the dictionary A is one of a Gaussian design matrix, a Walsh-Hadamard matrix, a matrix constructed with Delsarte-Goethals frame sequences, and a matrix constructed with Grassmannian frame sequences.
  • the receiving device is configured to receive the plurality of signals from a plurality of transmitting devices.
  • the plurality of signals may be received from different transmitting devices.
  • a transmitting device may comprise multiple transmitting antennas.
  • the plurality of signals may be received from different transmitting antennas of one or more transmitting devices.
  • the L sections of the dictionary A comprise at least one of: one or more sections dedicated to a particular transmitting device, and one or more sections shared among the particular transmitting device and one or more other transmitting devices.
  • a third aspect of the disclosure provides a method performed by a transmitting device, the method comprising: encoding a message sequence using one or more error correction codes to obtain G encoded sequences, wherein each encoded sequence has a length of J bits, where J and G are positive integers; mapping the G encoded sequences using G sections of a dictionary A to obtain a transmitting signal, wherein the dictionary A is a n X JL complex matrix comprising L sections, each section comprising J columns, where n is a positive integer and L is an integer greater than or equal to G; and transmitting the transmitting signal on a set of time-frequency resources to a receiving device.
  • Implementation forms of the method of the third aspect may correspond to the implementation forms of the transmitting device of the first aspect described above.
  • the method of the third aspect and its implementation forms achieve the same advantages and effects as described above for the transmitting device of the first aspect and its implementation forms.
  • a fourth aspect of the disclosure provides a method performed by a receiving device, the method comprising: receiving a plurality of signals; obtaining a reconstructed signal based on the plurality of received signals; processing the reconstructed signal by detecting one or more sequences from a dictionary A to obtain soft information on encoded sequences, wherein the dictionary A is a n X JL complex matrix comprising L sections, each section comprising J columns, where n, J and L are positive integers; estimating one or more message sequences based on the soft information on encoded sequences, wherein each estimated message sequence corresponds to a particular signal of the plurality of received signals; obtaining prior information based on the estimated one or more message sequences; re-processing the reconstructed signal based on the prior information to obtain updated soft information on the encoded sequences; and re-estimating the one or more message sequences based on the updated soft information on the encoded sequences.
  • Implementation forms of the method of the fourth aspect may correspond to the implementation forms of the receiving device of the second aspect described above.
  • the method of the fourth aspect and its implementation forms achieve the same advantages and effects as described above for the receiving device of the second aspect and its implementation forms.
  • a fifth aspect of the disclosure provides a computer program product comprising a program code for carrying out, when implemented on a processor, the method according to the third aspect and any implementation forms of the third aspect, or the fourth aspect and any implementation forms of the fourth aspect.
  • FIG. 1 shows an example of a non-coherent communication system with multiple transmitters.
  • FIG. 2 shows (a) an example of a transmitter, and (b) an example of a receiver.
  • FIG. 3 shows a time-frequency grid in an exemplary OFDM system.
  • FIG. 4 shows a transmitting device according to an embodiment of this disclosure.
  • FIG. 5 shows a transmitting device according to an embodiment of this disclosure.
  • FIG. 6 shows a dictionary A as used in an embodiment of this disclosure.
  • FIG. 7 shows a message sequence in an embodiment of this disclosure.
  • FIG. 8 shows a dictionary A as used in an embodiment of this disclosure.
  • FIG. 9 shows a message encoding procedure according to an embodiment of this disclosure.
  • FIG. 10 shows a receiving device according to an embodiment of this disclosure.
  • FIG. 11 shows a receiving device according to an embodiment of this disclosure.
  • FIG. 12 shows a method according to an embodiment of this disclosure.
  • FIG. 13 shows a method according to an embodiment of this disclosure.
  • FIG. 14 shows a performance comparison result of different communication schemes.
  • an embodiment/example in this disclosure may refer to other embodiments/examples.
  • any description including but not limited to terminology, element, process, explanation and/or technical advantage mentioned in one embodiment/example is applicative to the other embodiments/examples.
  • FIG. 1 shows a system with K single-antenna transmitters, which intend to communicate their respective sequences of bits to transmit to a receiver with M antennas over a propagation channel.
  • Each transmitter may perform a modulation and resource mapping to transmit its bit sequence, for instance, as a sequence of symbols over the channel.
  • the receiver may perform demodulation and resource demapping to recover a received matrix signal Y from the sequences of symbols received over the channel, and may estimate a sequence of bits for each transmitter (ideally, the estimated bits for one transmitter would correspond to the sequence of bits transmitted by that transmitter).
  • a channel use means that a transmitter maps a symbol to a communication resource.
  • the symbol may be mapped by the transmitter to a resource in the time-frequency grid of an orthogonal frequency-division multiplexing (OFDM) modulation, or may be mapped to a time resource for a wideband modulation.
  • OFDM orthogonal frequency-division multiplexing
  • the k-th transmitter takes as input a message mk as a sequence of B bits, and outputs a D- dimensional symbol s k , as shown in FIG. 2(a), which is then post-processed by a module for modulation and resource mapping as shown in FIG. 1.
  • Each of the D elements of s k is sent by the k-th transmitter over the channel in a so-called channel resource or channel use, which may be a slice of time and frequency, or any other orthogonal cut of the wireless channel communication medium.
  • the single receiver pre-processes the received signal as shown generally in FIG. 1 and shown in more detail in FIG. 2(b), and outputs a received matrix Y as described hereafter.
  • the receiver may use demodulators to demodulate signals received via its antennas, may use Analog-Digital converters to convert the analog signals into the digital domain, and may use a “symbol synchronization and slicing” module, which is responsible for the synchronization in time and frequency of the receiver with the sent symbols. This is needed to be able to slice the D channel uses, in order to output all elements of the signal matrix Y.
  • FIG. 3 shows an example of a time-frequency grid in an exemplary OFDM system, where D elementary resources are divided into V f V t blocks of n f n t resources.
  • each user When active, each user (transmitter) spreads its message over p ⁇ ⁇ V ⁇ such blocks in the frequency direction and p ⁇ ⁇ V ⁇ such blocks in the time dimension.
  • p ⁇ n ⁇ is related to the message duration
  • p ⁇ n ⁇ is related to the bandwidth assigned to a given transmitter. Note that the bandwidth also depends on the subcarrier spacing.
  • Each user transmits a signal spread over the D resource elements represented by a D ⁇ 1 vector s ⁇ decomposed as where each s ⁇ , ⁇ is a n ⁇ 1 vector signal mapped in v-th block.
  • the remaining V ⁇ p vectors are equal to 0.
  • the received signal outputted in the v-th block by the pre-processing module of the receiver can then be described as the sum of the contribution of K transmitters weighted by the corresponding channel coefficients and of an additive noise term.
  • a block-fading channel model is considered, meaning that the channel state is assumed to be constant during the considered n channel uses of the v-th block.
  • ⁇ W ⁇ is a matrix of size the n ⁇ M representing the thermal noise
  • ⁇ ⁇ P ⁇ , ⁇ is the transmit power coefficient of transmitter k
  • ⁇ s ⁇ , ⁇ is a vector of dimension n ⁇ 1 representing the symbol transmitted by transmitter k and carrying the information on sent sequence of bits (i.e.
  • a sent message that we denote by m ⁇ , ⁇ , and ⁇ h ⁇ , ⁇ is a vector of dimension M representing the channel between the antenna of transmitter k and the M antennas of the receiver. Since both the transmitters and receiver process each block independently, the description can be limited to one block in the following, i.e., by removing the index v for the sake of simplicity of notations. Furthermore, it is noted that operating in a random access scenario is considered, meaning that the receiver does not need to know in advance either the number of the transmitters that are transmitting over the channel or their identity. If the transmitter encoder operates differently depending on the transmitter identity, the scenario is said to be “sourced”. In this case, each transmitter will use a different encoder.
  • the transmitter encoder is independent of the transmitter identity, the scenario is said to be “unsourced”. In this case, the identity of the transmitter can be included in the message at the bit level.
  • a non-coherent regime can be considered, where the channel state is supposed to be unknown to both the receiver and the transmitters.
  • the conventional non-coherent schemes use either a tensor structure or sparsity as a main ingredient for the constellation design for a joint transmitter separation and message decoding. Considering constellations with a fixed size, the different constellations can be evaluated in terms of probability of decoding error for a given number of supported users, and reciprocally in terms of a number of supportable users for a given probability of decoding error.
  • Embodiments of this disclosure aim to provide a constellation that improves the conventional approaches with respect to these performance metrics and with respect to implementation complexity.
  • detailed transmission/encoding procedures according to embodiments of this disclosure for a single active user corresponding to the modules “Transmitter” and “Receiver” in FIG.1 will be described. Without loss of generality, the same applies to all users, possibly with different parameterization of the coding scheme, which depends in general on the reliability/latency requirements, as well as the channel conditions of the individual users.
  • FIG. 4 shows a transmitting device 400 according to an embodiment of this disclosure.
  • the transmitting device 400 may comprise processing circuitry (not shown) configured to perform, conduct or initiate the various operations of the transmitting device 400 described herein.
  • the processing circuitry may comprise hardware and software.
  • the hardware may comprise analog circuitry or digital circuitry, or both analog and digital circuitry.
  • the digital circuitry may comprise components such as application-specific integrated circuits (ASICs), field-programmable arrays (FPGAs), digital signal processors (DSPs), or multipurpose processors.
  • the transmitting device 400 may further comprise memory circuitry, which stores one or more instruction(s) that can be executed by the processor or by the processing circuitry, in particular under control of the software.
  • the memory circuitry may comprise a non-transitory storage medium storing executable software code which, when executed by the processor or the processing circuitry, causes the various operations of the transmitting device 400 to be performed.
  • the processing circuitry comprises one or more processors and a non-transitory memory connected to the one or more processors.
  • the non-transitory memory may carry executable program code which, when executed by the one or more processors, causes the transmitting device 400 to perform, conduct or initiate the operations or methods described herein.
  • the transmitting device 400 is configured to encode a message sequence 401 using one or more error correction codes to obtain G encoded sequences 402.
  • the transmitting device 400 may, to this end, include an encoder block 412.
  • the one or more error correction codes may comprise a binary CWC.
  • Each encoded sequence 402 has a length of J bits, where J and G are positive integers.
  • the transmitting device 400 is configured to map the G encoded sequences 402 using G sections of a dictionary A to obtain a transmitting signal 403.
  • the transmitting device 400 may, to this end, include a mapping block 423.
  • the dictionary A is a n X JL complex matrix comprising L sections, each section comprising J columns, where n is a positive integer and L is an integer greater or equal to G.
  • the transmitting device 400 is configured to transmit the transmitting signal 403 on a set of time-frequency resources to a receiving device 1000 (later illustrated in FIG. 10), in particular, over a channel established between the transmitting device 400 and the receiving device 1000.
  • the transmitting device 400 shown in FIG. 4 may correspond to the block “Transmitter k” shown in FIG. 1.
  • the transmitting device 400 according to an embodiment of this disclosure may be formed of two sub-blocks as shown in FIG. 5, namely the encoder block 413 that is configured to encode the message sequence 401 (message m k ) as the encoded sequence 402 (concatenated CWC p k ), and the mapping block 423, which is configured to map the encoded sequences 402 to the transmitting signal 403 (symbol m k ) to be transmitted (to the receiving device 1000).
  • the encoder block 413 that is configured to encode the message sequence 401 (message m k ) as the encoded sequence 402 (concatenated CWC p k )
  • the mapping block 423 which is configured to map the encoded sequences 402 to the transmitting signal 403 (symbol m k ) to be transmitted (to the receiving device 1000).
  • FIG. 6 shows a dictionary A, as it may be used for the transmitting device 400, wherein the dictionary A consists of L sections shared among users (transmitting devices), each of size n X J.
  • the K users to communicate information over the channel, the K users (transmitters) share the same dictionary A.
  • Each column of the dictionary A is an n-dimensional complex symbol.
  • the dictionary A is divided into L disjoint sections, each of size J, as illustrated in FIG. 6.
  • the message sequence 401 may comprise B information bits, B being a positive integer.
  • the transmitting device 400 may first split the message sequence 401 into g groups as it is shown in FIG. 7, wherein each group may comprise q information bits, where g and q are positive integers. Further, the transmitting device 400 may map q bits of each group to an integer between 0 and 2 q - 1.
  • a non-binary code over the Galois field GF(2 i? ) may be applied to encode g integers into G integers, where G > g.
  • Each of the G integers may be encoded into a binary codeword of a length J using a CWC of the length J and a weight w, where w is an integer and 1 ⁇ w ⁇ J.
  • each encoded sequence 402 may comprise w non-zero bits and J — w zero bits.
  • the transmitting device 400 may map the encoded sequence 402 (i.e., vector P k as shown in FIG. 8) using the dictionary A as shown in FIG. 8.
  • G sections from the L sections of the dictionary A may be selected for the mapping.
  • the transmitting device 400 may be configured to select the G sections from the L sections of the dictionary A by performing a random selection.
  • the transmitting device 400 may follow an indication from the receiving device 1000, wherein the indication is indicative of indices of the G sections in the L sections of the dictionary A.
  • the non-binary code may be a Reed Solomon code (L, g) over GF(2 ⁇ ).
  • FIG.9 illustrates a message encoding procedure according to this embodiment.
  • the transmitting device 400 may apply an error-correction code of a rate R that operates on the level of the J-ary symbols, resulting in a coded sequence g/R symbols.
  • the transmitting device 400 may make use of the n-dimensional complex sequences from the dictionary A, where ⁇ ⁇ is a vector size of JL ⁇ 1 corresponding to a one-hot encoding of the coded sequence of J-ary symbols, also known as pulse position modulation (PPM) in the literature. This operation is illustrated in FIG.9 decomposed into the L sections.
  • L,g Reed Solomon code
  • Each section (or block of sections) of the dictionary A of FIG. 6 or FIG. 8 can be considered either as dedicated to a particular user, e.g. to the transmitting device 400 as shown in FIG. 4, or shared among users, i.e., shared among the transmitting device 400 and other transmitting devices. This choice should be made preliminary to the communication.
  • each transmitting device may make use of the L sections of the dictionary.
  • all transmitting devices may use the same constellation.
  • the considered scenario may be referred to as an unsourced random access.
  • the consequence of this implementation is that the receiving device 1000 has to identify the transmitted symbols, without any knowledge on identities of the transmitting devices.
  • each transmitting device may make use of one section (or one block of sections) from the dictionary A (e.g., user 1 uses section 1, user 2 uses section 2 ...etc.).
  • This scenario may be referred to as sourced random access.
  • the receiving device 1000 can in this case recover the identity of the transmitting device 400 through the section identity, since each section (or block of sections) is dedicated to a particular transmitting device.
  • Another implementation may comprise dividing the L sections into a set of sections dedicated to unsourced access and another set of sections dedicated to sourced random access.
  • a set A ⁇ ci, . . . , c p ⁇ consisting of p binary vectors of length n is considered.
  • the OR superposition of these vectors is defined as the binary vector where ⁇ denotes the binary OR operation (performed component-wise on the vector elements).
  • Disjunctive code The binary code C with codeword length N and code size M is a disjunctive code of order p if each subset of size has the property that for every word c we have that but for all other words c ⁇ , ⁇ C / A we have that
  • ⁇ x,y ⁇ the correlation, i.e. the pairwise overlap (the number of positions where both x and y have 1’s)
  • wH( ⁇ ) denotes the Hamming weight.
  • the set of all disjunctive codes is denoted with parameters N, M and p as D(N, M, p).
  • a disjunctive code of order p has the property that may guarantee that any combination of p or less codewords can be uniquely decoded from their OR superposition.
  • the remaining codewords are not included in the OR superposition (in the sense of Definition 1).
  • Definition 3 Constant-weight code An (N, M, w, d) binary CWC is a set of M N-dimensional binary codewords of Hamming weight w such that the pairwise overlap (maximum number of coincident 1’s for any pair of codewords) does not exceed d.
  • the set of all CW codes is denoted with parameters N, M and w and d as CW(N, M, w, d).
  • an active transmitting device e.g. the transmitting device 400
  • the transmitting device 400 may transmits log 2 M bits of information in total.
  • the codeword c is mapped to a complex-valued transmit signal vector s of length n by the use of a n ⁇ N complex-valued dictionary matrix A (2) where ⁇ is a N ⁇ N diagonal matrix with the scaling coefficients ⁇ 1, ⁇ 2, ... , ⁇ N on the main diagonal.
  • the following channel model may be considered for the received signal vector y at the joint receiver
  • z is an additive noise vector.
  • Eq. (3) can be equivalently written in the following form where x is a sparse vector that entails information about the superposition of the corresponding transmitted binary vectors c 1 , c 2 , ... , c K (with the channel action included). Based on the structure described by eq.
  • the receiver e.g., the receiving device 1000
  • the receiver can run a procedure to estimate the support of the sparse vector x, supp(x), where the support is defined as a binary vector with 1’s on the positions of the non-zero entries of (x).
  • supp(x) represents in fact the OR superposition of the binary codewords of the K active users If the codewords c1, c2, . . . , cK are selected from a disjunctive code, as described in Definition 2, and as long as the number of active users K does not exceed the order of the disjunctive code p, K ⁇ p, it may be guaranteed that the binary codewords c1, c2, ...
  • the simulation results show that, in practice, the procedure will very often return correct detection of the ”active” codewords even if K > p.
  • the set of constant-weight codes with a length N , a size M , a weight w and a maximal correlation d, CW(N, M, w, d) is a subset of the set of disjunctive codes with length N , size M and order where ⁇ x ⁇ denotes the smallest integer greater than or equal to x.
  • an appropriately parameterized constant-weight code yields a disjunctive code, hence inheriting its properties.
  • a specific constant-weight code construction may be proposed from the concatenation of a PPM (2q) code and a Reed-Solomon code, as described in the embodiments.
  • the Reed-Solomon code may be substituted by another non-binary code over GF(2q ).
  • the use of CWC is advocated.
  • the weight of any coded message defined as the number of 1s in the bit representation of the codeword ⁇ ⁇ , may be fixed and constant. Any non-binary code could also be applied, including LDPC codes. Targeting short message transmissions where the message is spread over a few resource blocks, algebraic codes can be used.
  • Candidate codes include Reed Solomon codes, which form a special subclass of Bose Chaudhury Hocquenghem (BCH) codes.
  • BCH Bose Chaudhury Hocquenghem
  • a (4; 3) Reed Solomon code over the Galois field GF(23 ) is used, applied such that 1 redundant 8-ary symbol is added to the 4 information carrying 8-ary symbols to provide error protection.
  • other options than using a common dictionary are also possible. For instance, user-specific dictionaries may be used. In this case, the same code construction may also be applied for a scenario, in which the dictionary matrix A is divided into a certain number of sections, and each user is assigned a separate section that now acts as a user-specific dictionary.
  • the transmitted codewords also carry information about the identity of the active users.
  • a hybrid approach is also conceivable where the total number of users is divided into a number of groups (for example Ngroups), such that one group of users is configured to use one or more sections of the dictionary matrix A.
  • Ngroups groups
  • the same code construction as described above can be used to provide separation of the simultaneously active users at the receiver side.
  • the dictionary matrix A is divided into sections, and each active user selects randomly one or more sections. In this case, the proposed code construction enables the receiver to separate the active users that have selected the same section(s).
  • dictionary design An important aspect related both to the performance and the encoding/decoding complexity is the choice of the user dictionaries A (i.e. sequence design). Examples of dictionary design are thus discussed in the following.
  • One implementation includes selecting each entry of the dictionary independently drawn from a standard Gaussian distribution and storing these entries in memory. As the number of iterations is finite, the decoding complexity scales linearly with the size of the design matrix. With such a Gaussian design matrix, the memory requirement is also proportional to the dimension as the entire matrix has to be stored, which could be a major bottleneck in scaling the decoder to work with large design matrices.
  • the proposed code construction in this disclosure can be combined with any dictionary matrix design.
  • Examples include Gaussian matrices, Walsh- Hadamard matrices, Grassmannian frames, Equiangular tight frames, Delsarte-Goethals frames etc.
  • Gabor frames are attractive for the scenario in hand, including the fact that: 1) Gabor frames are completely specified by a total of n numbers that describe the seed vector, and can be effectively generated as time- frequency translates of the seed vector; 2) multiplications with Gabor frames (and their adjoints) can be efficiently carried out using algorithms such as FFT. Therefore, the dictionary design from Gabor frames as being particularly attractive/beneficial.
  • Gabor frames obtained from an Alltop seed vector have favorable properties.
  • a Gabor frame is the set of all time-frequency translates of a nonzero seed vector in Cn, and consists of n2 vectors.
  • the receiving device 1000 may comprise processing circuitry (not shown) configured to perform, conduct or initiate the various operations of the receiving device 1000 described herein.
  • the processing circuitry may comprise hardware and software.
  • the hardware may comprise analog circuitry or digital circuitry, or both analog and digital circuitry.
  • the digital circuitry may comprise components such as ASICs, FPGAs, DSPs, or multi-purpose processors.
  • the receiving device 1000 may further comprise memory circuitry, which stores one or more instruction(s) that can be executed by the processor or by the processing circuitry, in particular under control of the software.
  • the memory circuitry may comprise a non-transitory storage medium storing executable software code which, when executed by the processor or the processing circuitry, causes the various operations of the receiving device 1000 to be performed.
  • the processing circuitry comprises one or more processors and a non-transitory memory connected to the one or more processors.
  • the non-transitory memory may carry executable program code which, when executed by the one or more processors, causes the receiving device 1000 to perform, conduct or initiate the operations or methods described herein.
  • the receiving device 1000 is configured to receive a plurality of signals 1001.
  • the signals 1001 may include the signal 403 sent by the transmitting device 400 over the channel.
  • the receiving device 1000 is further configured to obtain a reconstructed signal 1002 based on the plurality of received signals 1001.
  • the receiving device 1000 may comprise a reconstruction block 1012.
  • the receiving device 1000 is configured to process the reconstructed signal 1002 by detecting one or more sequences from a dictionary A to obtain soft information 1003 on encoded sequences.
  • the dictionary A is a n X JL complex matrix comprising L sections, each section comprising J columns, where n, J and L are positive integerss.
  • the receiving device 1000 may comprise a decoding block 1023.
  • the receiving device 1000 is configured estimate one or more message sequences 1004 based on the soft information 1003 on the encoded sequences, wherein each estimated message sequence 1004 corresponds to a particular signal of the plurality of received signals 1001.
  • the receiving device 1000 may include an estimation block 1034.
  • the receiving device 1000 is configured to obtain prior information 1005 based on the estimated one or more message sequences 1004.
  • the receiving device 1000 may include a block 1045.
  • the receiving device 1000 is further configured to re-process the reconstructed signal 1002 based on the prior information 1005 to obtain updated soft information on the encoded sequences; and re-estimate the one or more message sequences 401 (see FIG. 4) based on the updated soft information on the encoded sequences.
  • the receiving device 1000 shown in FIG. 10 may correspond to the block “Receiver” in FIG. 1.
  • the receiving device 1000 shown in FIG. 10 may be the receiving device 1000 shown in FIG. 4.
  • the proposed transmission scheme of the receiving device 1000 can be combined with receiver processing performed by two receiver modules, as shown in FIG. 11.
  • the first receiver module may comprise or implement the blocks as described in FIG. 10, and aims at detecting the “active” sequences from the dictionary A.
  • the second module may outputs the individual messages of the active users (e.g., the transmitting device 400) by taking into account the code structure.
  • the first module can, for example, implement detection in the spirit of signal reconstruction in compressive sensing. As particularly appropriate are scalable inference algorithms based on message passing, such as approximate message passing (AMP) and extensions therein.
  • the plurality of signals 1001 may be received from different transmitting devices, e.g. including the transmitting device 400.
  • the plurality of signals 1001 as shown in FIG. 10 may comprise the transmitting signal 403 as shown in FIG. 4.
  • a transmitting device for example the transmitting device 400 as shown in FIG. 4
  • the plurality of signals 1001 received at the receiving device 1000 may comprise signals transmitted from different transmit antennas of the same transmitting device.
  • the output of the first receiver module effectively produces an OR multiple access channel.
  • the transmitting devices will be naturally separated over the channel.
  • the separation of the users is enabled by the applied CWC, as discussed previously.
  • the receiver processing can also be implemented by iteratively exchanging soft information between the two receiver modules: the first module would, for example, carry out standard AMP which accounts for the dictionary structure, but ignores the dependencies imposed by the code which guides the sequence selection process (i.e. prescribes how the information messages are mapped to the linear combinations of sequences from the dictionary); the second inference module refines the output of the AMP module by handling the dependencies coming from the structure of the applied code. The soft information output from the second module is then passed to the AMP module in the form of a refined prior information and the procedure is repeated.
  • the first module would, for example, carry out standard AMP which accounts for the dictionary structure, but ignores the dependencies imposed by the code which guides the sequence selection process (i.e. prescribes how the information messages are mapped to the linear combinations of sequences from the dictionary); the second inference module refines the output of the AMP module by handling the dependencies coming from the structure of the applied code.
  • the soft information output from the second module is then passed to the AMP module in
  • FIG. 12 shows a method 1200 according to an embodiment of the disclosure.
  • the method 1200 is performed by a transmitting device 400 shown in FIG. 4 or FIG. 5.
  • the method 1200 comprises: a step 1201 of encoding a message sequence 401 using one or more error correction codes to obtain G encoded sequences 402.
  • each encoded sequence 402 has a length of J bits, where J and G are positive integers.
  • the method 1200 further comprises a step 1202 of mapping the G encoded sequences 402 using G sections of a dictionary A to obtain a transmitting signal 403.
  • the dictionary A is a n x J L complex matrix comprising L sections, each section comprising J columns, where n is a positive integer and L is an integer greater than or equal to G.
  • the method 1200 further comprises a step 1203 of transmitting the transmitting signal 403 on a set of time-frequency resources to a receiving device 1000.
  • the receiving device 1000 may be the receiving device 1000 shown in FIG. 4, FIG. 10 or FIG. 11.
  • FIG. 13 shows a method 1300 according to an embodiment of the disclosure.
  • the method 1300 is performed by a receiving device 1000 shown in FIG. 4, FIG. 10 or FIG. 11.
  • the method 1300 comprises: a step 1301 of receiving a plurality of signals 1001.
  • the method 1300 further comprises a step 1302 of obtaining a reconstructed signal 1002 based on the plurality of received signals 1001.
  • the method 1300 further comprises a step 1303 of processing the reconstructed signal 1002 by detecting one or more sequences from a dictionary A to obtain soft information 1003 on encoded sequences, wherein the dictionary A is a n ⁇ J L complex matrix comprising L sections, each section comprising J columns, where n, J and L are positive integers.
  • the method 1300 comprises a step 1304 of estimating one or more message sequences 401 based on the soft information 1003 on encoded sequences, wherein each estimated message sequence 401 corresponds to a particular signal of the plurality of received signals 1001. Then, the method 1300 further comprises a step 1305 of obtaining prior information 1004 based on the estimated one or more message sequences 401, a step 1306 of re-processing the reconstructed signal 1002 based on the prior information 1004 to obtain updated soft information 1003 on the encoded sequences, and a step 1307 of re-estimating the one or more message sequences 401 based on the updated soft information 1003 on the encoded sequences.
  • the plurality of signals 1001 comprises the transmitting signal 403 that is transmitted from the transmitting device 400 shown in FIG.4 or FIG.5.
  • This disclosure proposes to define a new transmitter encoder computing a symbol from a sequence of bits at each transmitter. Such symbols are transmitted over the air and processed by the receiver.
  • This disclosure further proposes to define a multi-user receiver that is able to recover the list of the initial sequence of bits of all transmitters from the received symbols.
  • Embodiments of the disclosure describes a design of an encoder shared among all users combining an error correction code with a constant weight property with a dictionary matrix divided in blocks. In particular, the use of CWCs and the dictionary design based on Gabor frames may be preferable.
  • FIG.14 compares performances of the proposed constellation design (referred to as CWC with Gabor dictionary) with a conventional constellation design 1 and an existing constellation design 2 for the following scenarios.
  • the powers coefficient are chosen equal to
  • the elements of H are drawn from a complex Gaussian distribution of variance 1.
  • the elements of W are drawn from a complex Gaussian distribution of variance 10 1,5 .
  • the proposed constellation outperforms state-of-the-art methods for random access in terms of number of supported users and probability of error and are close to optimal for single-antenna receiver.
  • the block-fading requirement is suitable for relatively short coherence time/frequency.
  • any method according to embodiments of the disclosure may be implemented in a computer program, having code means, which when run by processing means causes the processing means to execute the steps of the method.
  • the computer program is included in a computer readable medium of a computer program product.
  • the computer readable medium may comprise essentially any memory, such as a ROM (Read-Only Memory), a PROM (Programmable Read-Only Memory), an EPROM (Erasable PROM), a Flash memory, an EEPROM (Electrically Erasable PROM), or a hard disk drive.
  • embodiments of the transmitting device 400 and the receiving device 1000 comprises the necessary communication capabilities in the form of e.g., functions, means, units, elements, etc., for performing the solution.
  • means, units, elements and functions are: processors, memory, buffers, control logic, encoders, decoders, rate matchers, de-rate matchers, mapping units, multipliers, decision units, selecting units, switches, interleavers, deinterleavers, modulators, demodulators, inputs, outputs, antennas, amplifiers, receiver units, transmitter units, DSPs, trellis-coded modulation (TCM) encoder, TCM decoder, power supply units, power feeders, communication interfaces, communication protocols, etc. which are suitably arranged together for performing the solution.
  • TCM trellis-coded modulation
  • the processor(s) of the transmitting device 400 and the receiving device 1000 may comprise, e.g., one or more instances of a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an ASIC, a microprocessor, or other processing logic that may interpret and execute instructions.
  • CPU Central Processing Unit
  • the expression “processor” may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones mentioned above.
  • the processing circuitry may further perform data processing functions for inputting, outputting, and processing of data comprising data buffering and device control functions, such as call processing control, user interface control, or the like.

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Abstract

La présente divulgation se réfère à une procédure d'accès aléatoire massif. Elle concerne un dispositif de transmission configuré pour : coder une séquence de message à l'aide d'au moins un code de correction d'erreur afin d'obtenir G séquences codées, chaque séquence codée comportant une longueur de J bits, J et G étant des nombres entiers positifs ; mapper les G séquences codées à l'aide de sections G d'un dictionnaire A afin d'obtenir un signal d'émission, le dictionnaire A étant une matrice complexe n x JL comprenant L sections, chaque section comprenant J colonnes, n étant un nombre entier positif et L étant un nombre entier supérieur ou égal à G ; et transmettre le signal d'émission sur un ensemble de ressources de temps-fréquence à un dispositif de réception. De plus, la présente divulgation concerne également un dispositif de réception configuré pour recevoir une pluralité de signaux, et récupérer des séquences de message de tous les émetteurs à partir des signaux reçus.
EP21719118.8A 2021-04-14 2021-04-14 Dispositif et procédé d'accès aléatoire massif Pending EP4309312A1 (fr)

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