Method for transmitting multiple streams with one code based on random multiplexing and joint detection decoding

Abstract

The application discloses a one-code multi-stream transmission method based on random multiplexing and joint detection decoding, wherein original signals are subjected to random multiplexing at a transmitting end, so that signal energy is uniformly distributed on all fading branches; signals transmitted by the transmitting end are received at a receiving end, and an iterative process is performed by using a cascaded CD-OAMP detection decoding receiver or a joint CD-OAMP detection decoding receiver; a linear estimator of the CD-OAMP performs linear minimum mean square error estimation, a nonlinear estimator performs symbol-by-symbol demodulation, and iteration is performed until convergence, so that a decoding result removing inter-symbol interference is obtained. The application makes equivalent channels approximate AWGN channels by random multiplexing, so that a single AWGN code is still robust. Inter-symbol interference introduced by random multiplexing is eliminated by a CD-OAMP detector with low complexity and Bayesian optimality. Decoding information is fully utilized by joint decoding detection, so that signal estimation is more accurate.

Description

Technical Field

[0001] This invention relates to the field of communication encoding and decoding, and in particular to a one-code-multi-stream transmission method based on random multiplexing and joint detection decoding. Background Technology

[0002] Modern wireless communication systems, such as massive MIMO, multipath channels, and block fading channels, commonly employ multi-stream transmission mechanisms to improve spectral efficiency and data transmission rates. However, these parallel-transmitting sub-channels exhibit significant gain differences during actual propagation. Especially when the system employs a water-filled power allocation strategy, the channel quality differences between different streams are further amplified, making it difficult for a single Additive White Gaussian Noise (AWGN) coding scheme based on a fixed signal-to-noise ratio threshold to adapt to the dynamically changing signal-to-noise ratio conditions between the fading streams. Once some sub-channels are in deep fading, and the instantaneous signal-to-noise ratio falls below the decoding threshold, it can easily trigger continuous bit errors or even decoding failures, resulting in a significant decrease in the overall system throughput and reliability.

[0003] Existing solutions for mitigating multi-fading streams mainly fall into two categories. One category assigns a unique AWGN code to each stream. While this one-stream-one-code approach allows for individual optimization, it requires multiple codecs, significantly increasing hardware resource consumption and system complexity. Furthermore, the stream splitting process leads to shorter code lengths, resulting in a decrease in coding gain. The other category designs dedicated codes for multi-fading streams. However, this approach requires replacing existing systems with application-specific integrated circuits (ASICs), resulting in high development costs and incompatibility with existing communication hardware, thus limiting its widespread adoption and application.

[0004] Most existing technologies lack cross-scenario versatility and cannot effectively handle arbitrarily multiple fading streams while maintaining the single AWGN coding structure of existing practical systems. Specifically, these include:

[0005] Using only a single standard AWGN code: Employing a single AWGN code across all fading streams introduces fundamental limitations. Because the error correction capability of this code is designed for a fixed target SNR, deep fading streams with instantaneous SNRs below this threshold will exhibit uncorrectable burst errors exceeding the codeword correction capability. This leads to complete decoding failure in severely fading streams, limiting the overall system performance to worst-case channel conditions and resulting in a significant decrease in reliability.

[0006] One stream, one code, each stream uses an independent matching AWGN code: Using an instantaneously signal-to-noise ratio matched code for each fading stream introduces the following core bottlenecks: (1) Maintaining and switching multiple codebooks leads to excessive system complexity; (2) Adaptability to dynamic environments is impaired; (3) To achieve A fading stream needs The hardware resource consumption of the set of encoding / decoding units varies. Present Scale growth; (4) Due to the code length from Reduced to This results in compromised coding gain. These drawbacks often outweigh the potential gains from stream-level performance, making stream-by-stream coding schemes difficult to apply in practical wireless systems.

[0007] Code optimization schemes: Although advanced coding schemes can theoretically optimize the performance of multi-fading streams, their practical deployment faces two fundamental obstacles: (1) Fixed-function ASICs commonly used in commercial transceivers physically prevent any modifications to the coding scheme after production; (2) Standardization specifications such as 3GPP list AWGN optimized codes (LDPC / polar codes) as mandatory schemes, excluding adaptive alternatives. This dual limitation of hardware and standards makes coding schemes designed for multi-fading streams currently infeasible in commercial systems.

[0008] In summary, existing technologies suffer from the following drawbacks: high implementation costs and difficulty in compatibility with existing practical systems. Existing "one-code-per-thread" and dedicated code design schemes require the development of new ASIC chips for encoding and decoding. ASIC chip design cycles are long, manufacturing costs are high, and they are incompatible with the hardware of existing practical communication systems. System flexibility is limited, and versatility is lacking.

[0009] The "one stream, one code" scheme requires adjusting the code rate according to different sub-channel states, while dedicated coding schemes are typically customized for specific channel characteristics. Both lack the ability to adapt to dynamically changing channel conditions, making them unsuitable for a wide range of multi-stream fading scenarios and severely limiting system deployment and maintenance flexibility. Coding gain also decreases.

[0010] The "one code per stream" scheme results in a shorter code length due to split coding. According to Shannon's theory, a shorter code length weakens the coding gain, thereby reducing the system's error correction capability and overall throughput performance.

[0011] The existing system uses only one AWGN code, and its performance is limited in deep fading streams in multi-fading streams, resulting in a significant decrease in overall performance.

[0012] The industry urgently needs a communication architecture that can achieve efficient and stable transmission in multi-fading streams without redesigning the coding or significantly increasing the system complexity. Summary of the Invention

[0013] This invention aims to achieve efficient and stable transmission in any multi-fading stream without altering existing encoding and decoding methods and using only a single standard AWGN code. This invention proposes a joint detection and decoding method based on random multiplexing and Cross-Domain Orthogonal Approximate Message Passing (CD-OAMP).

[0014] The objective of this invention is achieved through the following technical solution: a one-code-multiplexed transmission method based on random multiplexing and joint detection decoding, the method comprising: randomly multiplexing the original signal at the transmitting end to evenly distribute the signal energy to all fading branches;

[0015] The receiver receives the signal transmitted from the transmitter and performs iterative processing using a CD-OAMP combined with a standard decoder. The linear estimator of the CD-OAMP performs linear minimum mean square error estimation, and the nonlinear estimator performs symbol-by-symbol demodulation. The process is iterated until convergence, and the decoding result with inter-symbol interference removed is obtained.

[0016] Furthermore, the random multiplexing of the original signal at the transmitting end specifically involves:

[0017] Original signal Through an orthogonal random matrix independent of the channel and signal Random multiplexing is performed, and the baseband model of the system after random multiplexing is as follows:

[0018] .

[0019] in Represents the received signal vector; Represents the transmitted signal vector; This represents a noise vector that follows a normal distribution. Then it means the first The fading coefficient of each fading stream; This represents the set of fading flows that have been allocated power.

[0020] Furthermore, the linear estimator of the CD-OAMP is specifically as follows:

[0021] Based on the system baseband model after random multiplexing For a constrained linear estimator, let ,

[0022] ,

[0023] ,

[0024] in, It is the estimator of the linear estimator. It is the variance of the estimator of the linear estimator. For noise power, , ; For orthogonal operations, The variance of the estimator for the nonlinear estimator. Then it means the first The fading coefficient of each fading flow, where B is the number of fading flows. It is the vector input to the linear end after the estimator of the nonlinear end undergoes orthogonal and cross-domain transformation.

[0025] Furthermore, the CD-OAMP combined with the standard decoder specifically includes a cascaded CD-OAMP detection decoder receiver or a combined CD-OAMP detection decoder receiver;

[0026] The cascaded CD-OAMP detection decoder receiver is specifically configured such that: first, the CD-OAMP detector iterates until convergence, and then an independent AWGN decoder processes the detector's output;

[0027] The joint CD-OAMP detector-decoder receiver specifically integrates the CD-OAMP detector and decoder into a unified iterative process.

[0028] Furthermore, the nonlinear estimator in the cascaded CD-OAMP detection decoder receiver is:

[0029] correspond Constrained nonlinear estimators, i.e. obey Distribution; Let Represents a priori constellation chart,

[0030] ,

[0031] ,

[0032] in, It is the estimation function for the nonlinear end. It is an estimator for symbol-by-symbol demodulation at the nonlinear end. It is the variance of the nonlinear end estimator; It is the vector input to the nonlinear end after the estimator of the linear end undergoes cross-domain transformation and orthogonal operation.

[0033] Furthermore, the vector input to the nonlinear end after the estimator of the linear end undergoes cross-domain transformation and orthogonal operation is specifically as follows:

[0034] ;

[0035] in ; ; For orthogonal operations,

[0036] ;

[0037] It is the estimator of the linear estimator. It is the variance of the estimator of the linear estimator. Orthogonal random matrices are used for random reuse; This is the final output estimate.

[0038] Furthermore, during the iterative process of the joint CD-OAMP detection decoding receiver,

[0039] The decoder uses the prior log-likelihood ratio provided by the demodulator. To calculate the posterior log-likelihood ratio, denoted as... Then, from the posterior log-likelihood ratio The derived mean and variance are passed to the linear estimator; the initial state is... The final output is based on hard verdict ,in This represents the estimation function for the nonlinear end.

[0040] Furthermore, in the nonlinear estimator of the joint CD-OAMP detection decoder receiver, the nonlinear end estimator... and its variance Given by the following formula:

[0041] ,

[0042] .

[0043] On the other hand, a one-code-multiplexed transmission device based on random multiplexing and joint detection decoding is also provided, including a memory and one or more processors. The memory stores executable code, and when the processor executes the executable code, it implements the one-code-multiplexed transmission method based on random multiplexing and joint detection decoding.

[0044] On the other hand, a computer-readable storage medium is also provided, on which a program is stored, which, when executed by a processor, implements the aforementioned one-code-multi-stream transmission method based on random multiplexing and joint detection decoding.

[0045] The beneficial effects of this invention are as follows: This invention uses random multiplexing to make the equivalent channel approximate an AWGN channel, ensuring the robustness of a single AWGN code. It eliminates inter-symbol interference introduced by random multiplexing through a low-complexity, Bayesian-optimal CD-OAMP detector. By fully utilizing decoding information through joint decoding detection, it achieves more accurate signal estimation and system performance significantly superior to existing technologies. Attached Figure Description

[0046] Figure 1 This is a block diagram of the transmitter provided in an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of a receiver-cascaded CD-OAMP detection decoder (CDD) provided in an embodiment of the present invention;

[0048] Figure 3 A schematic diagram of a receiver-side combined CD-OAMP detection decoding receiver (JDD) provided in an embodiment of the present invention;

[0049] Figure 4 Simulation comparison of the CD-OAMP detection decoding receiver scheme provided in the embodiments of the present invention with the scheme using a single AWGN code and a first-class-one-code scheme in the case of medium-long codes;

[0050] Figure 5 Simulation comparison of the CD-OAMP detection decoding receiver scheme provided in the embodiments of the present invention with the scheme using a single AWGN code and a first-class-one-code scheme in the case of long codes;

[0051] Figure 6 This is a schematic diagram of the apparatus provided in an embodiment of the present invention. Detailed Implementation

[0052] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0053] The technical solution of this invention to deal with multi-fading streams is to use random multiplexing at the transmitting end of the communication system and to use cascaded or combined CD-OAMP detection and decoding receivers at the receiving end.

[0054] like Figure 1 As shown, random multiplexing is introduced at the transmitting end:

[0055] Random multiplexing is a preprocessing technique. It employs an orthogonal random matrix independent of the channel and signal. ,Right now ,in It is an identity matrix, which, through transformation, distributes the signal energy evenly across all fading branches. Original signal The signal is obtained after random multiplexing. ,

[0056] .

[0057] The system baseband model after random multiplexing is as follows

[0058] .

[0059] Random multiplexing can effectively transform asymmetric channel streams into approximately additive white Gaussian noise channels while maintaining the same channel capacity. ,in It consists of a set of fading coefficients ( The equivalent channel matrix of the multi-fading stream is composed of symbols. However, random multiplexing introduces inter-symbol interference, which poses a new challenge to signal detection. To address this issue, we employ a low-complexity, Bayesian-optimal CD-OAMP detector.

[0060] The receiving end uses either a cascaded CD-OAMP detection and decoding receiver (CDD) or a joint CD-OAMP detection and decoding receiver (JDD).

[0061] Specifically, such as Figure 2 As shown, the receiver uses a cascaded CD-OAMP detection decoder receiver, which includes:

[0062] The cascaded CD-OAMP detector-decoder receiver first iterates through a CD-OAMP detector until convergence, and then a separate AWGN decoder processes the detector's output. Since this invention uses a standard AWGN decoder, the decoder will not be described in detail. The following will focus on the CD-OAMP detector.

[0063] CD-OAMP performs cross-domain orthogonal iterations between a linear estimator (LE) and a nonlinear estimator (NLE). The LE performs linear minimum mean square error estimation (LMMSE), while the NLE performs symbol-by-symbol demodulation. The initial state of the iteration is... The final output estimate is The iterative process is as follows, including four parts: LE, NLE, cross-domain transformation including random multiplexing and inverse random multiplexing, and orthogonal operations.

[0064] correspond A constrained linear estimator, we let ,

[0065] ,

[0066] ,

[0067] in, It is the estimator of the linear estimator. It is the variance of the estimator of the linear estimator. It is the vector input to the linear end after the estimator of the nonlinear end undergoes orthogonal and cross-domain transformation.

[0068] Corresponding nonlinear constraints Nonlinear estimator, where Indicates sending signal The first in A symbol, To represent any distribution, and obey Distribution, i.e., sending signals Each symbol in the code obeys Distribution. Let us let Represents a priori constellation chart, ,

[0069] ,

[0070] in, It is the estimation function for the nonlinear end. It is an estimator for symbol-by-symbol demodulation at the nonlinear end. It is the variance of the nonlinear estimator. It is the vector input to the nonlinear end after the estimator at the linear end undergoes cross-domain transformation and orthogonal operation. The corresponding cross-domain transformation... Constrained random reuse and inverse random reuse,

[0071] .

[0072] To solve the orthogonalization of correlation, we define Scalar orthogonal operations are ,

[0073] ;

[0074] ;

[0075] ;

[0076] in It is the orthogonal linear estimate of the variance. It is the nonlinear estimate of variance after orthogonalization. Specifically, such as... Figure 3 As shown, the receiver using the joint CD-OAMP detection decoder includes:

[0077] The Joint CD-OAMP Detector-Decoder Receiver integrates the CD-OAMP detector and decoder into a unified iterative process. JDD fully utilizes the decoded information, thus outperforming traditional cascaded receivers.

[0078] Specifically, JDD performs cross-domain orthogonal iterations between a linear estimator and a joint nonlinear estimator (JNLE). The linear estimator, cross-domain transformation, and orthogonal operation are consistent with the iterative process of CDD, and will not be repeated here. The joint nonlinear estimator will be the focus of the following discussion.

[0079] In JNLE, the decoder uses the prior log-likelihood ratio provided by the demodulator. To calculate the posterior log-likelihood ratio, denoted as... ,in This represents the estimated function of the decoder, and then the posterior log-likelihood ratio is used to... The derived mean and variance are passed to the linear estimator. The initial state is... The final output is based on hard verdict JNLE is given by the following formula,

[0080] ,

[0081] .

[0082] The following provides a more detailed description of specific embodiments of the present invention:

[0083] This invention employs random multiplexing at the transmitting end of the communication system to approximate the equivalent channel as an Additive White Gaussian Noise (AWGN) channel. At the receiving end, it uses cascaded or joint detection decoding receivers to resolve inter-symbol interference introduced by random multiplexing, thereby enabling the handling of multi-fading streams without changing the code structure and using only a single standard AWGN code.

[0084] The communication system model considered in this invention is as follows:

[0085] ,

[0086] in, Represents the received signal vector; Represents the transmitted signal vector; This represents a noise vector that follows a normal distribution. Then it means the first The fading coefficient of each fading stream; This represents the set of fading flows that have been allocated power. A fading stream occupies Symbol length. Without loss of generality, we assume that all fading streams have the same length, i.e., satisfying... The total symbol length of the system is . This is the multi-fading stream channel matrix. In the simulation of this invention, the random multiplexing matrix... From the random permutation matrix and fast transformation matrix Composition. For simplicity, this invention simulates the system performance in a dual-fading stream with significantly different fading coefficients, i.e. .

[0087] Example 1: Cascaded CD-OAMP Detection and Decoding Scheme Based on Random Multiplexing

[0088] S1, Initialization

[0089] S11, Initialize the transmission signal

[0090] S111, Assume the transmitter transmits a normalized BPSK signal. Signal length Adjustable, can be a short code, for example ; medium-length codes, for example Long codes, for example In the Sionna v0.19.2 simulation platform, the BPSK signal can be implemented using the BinarySource() function.

[0091] S112. This invention assumes that the transmitted signal is normalized, then the simulated signal-to-noise ratio is defined as the reciprocal of the noise power, i.e. .

[0092] S12, Encoder / Decoder Initialization

[0093] S121, Comparison Scheme Baseline 2 (one code per stream, each stream uses a matching AWGN code independently) sets up an encoder for each of the two fading streams, with code rates of respectively To ensure a fair comparison, the present invention provides the following solution.

[0094] Use the settings to set an encoder with a bitrate of .

[0095] S122. In order to ensure that the decoder decodes fully, the number of Belief Propagation (BP) decoding iterations is set to 10.

[0096] S13, Fading coefficient of double fading flow set up.

[0097] S131. This invention assumes that the transmitter has already used water-filled power allocation, and the equivalent channel gain after water filling is: During simulation It is determined by the following two conditions. (1) The channel gain has been normalized, that is, it satisfies the following conditions. (2) The bit rate that matches the corresponding fading stream. Achieve on AWGN channel The signal-to-noise ratio at the block error rate satisfies This condition ensures that all links can maintain a uniform transmit signal-to-noise ratio. Go to work.

[0098] S14. To ensure statistical reliability, the number of repeated experiments is set to 10,000.

[0099] S2, Receiver-end cascaded CD-OAMP detection and decoding receiver

[0100] S21. Initialization .

[0101] S22. Calculate the linear estimator estimator. and its variance Among them, ,

[0102] .

[0103] .

[0104] S23, Linear Estimator Estimator Obtained through cross-domain transformation ,

[0105] .

[0106] S24, after cross-domain transformation and its variance After orthogonal operation, we obtain and

[0107]

[0108] .

[0109] S25, Number of Update Iterations .

[0110] S26, Order This represents the BPSK prior constellation diagram. Based on... obey Distribution, i.e. Calculate the nonlinear end estimator and its variance ,

[0111] ,

[0112] ,

[0113] Among them, let This represents the estimation function for the nonlinear end.

[0114] S27, Nonlinear Estimator Estimator and its variance After orthogonal operation, we obtain and ,

[0115] ,

[0116] .

[0117] S28 Obtained through cross-domain transformation and will Input to the linear terminal,

[0118]

[0119] S29. Repeat S22-S28 until... Final output It goes into the cascaded decoder.

[0120] This application also performs a complexity analysis on the CD-OAMP detector in its embodiments. First, in the linear estimator, due to... It is a diagonal matrix. The matrix inversion calculation can be simplified to element-wise operations, avoiding the high complexity of matrix inversion. Therefore, the complexity of the linear estimator is... Secondly, the nonlinear estimator performs symbol-by-symbol demodulation, therefore its complexity is also... If a random reuse matrix is ​​used... From the random permutation matrix and fast transformation matrix If the structure is correct, the complexity of cross-domain transformations can be reduced to [value missing]. If interleaved block sparse transform is used, the complexity of cross-domain transform can be further reduced to [missing value]. This is because the interleaved block sparse transform decomposes the large transform into multiple smaller transforms, and the performance degradation is negligible. In summary, the overall complexity of the CD-OAMP algorithm is mainly determined by the complexity of the cross-domain transform.

[0121] We perform an optimality analysis on the CD-OAMP detector. Random multiplexing reshapes the equivalent channel matrix to satisfy orthogonality, ensuring that CD-OAMP can achieve maximum a posteriori bit error rate performance when a unique fixed point exists.

[0122] Finally, regarding the achievable rate analysis of the above-mentioned cascaded CD-OAMP detection and decoding scheme based on random multiplexing, this invention analyzes its achievable rate through the state evolution of CD-OAMP. Let the estimation error of the linear end be... The estimation error of the nonlinear end is The state evolution is then given by the following iterative process.

[0123] ,

[0124] ,

[0125] ,

[0126] in, For linear terminal state evolution functions, And with Irrelevant And initial variance .make For state evolution iteration The subsequent linear end estimation error can be known from the state evolution iteration process. and If relevant, then The achievable rate of CDD based on random reuse after the nth iteration is:

[0127] .

[0128] Example 2: Joint CD-OAMP detection and decoding scheme based on random multiplexing

[0129] The Joint CD-OAMP Detection and Decoding (JDD) receiver integrates the CD-OAMP detector and decoder into a unified iterative process. JDD can fully utilize the decoded information, thus outperforming traditional cascaded receivers. The initialization of the joint CD-OAMP detection and decoding scheme based on random multiplexing, as well as the detector linearization process, remain consistent with Embodiment 1, i.e., consistent with S1-S25 of Embodiment 1, and will not be repeated here. The subsequent steps of this embodiment are as follows.

[0130] S26. In the joint nonlinear terminal, the decoder uses the prior log-likelihood ratio provided by the demodulator. To calculate the posterior log-likelihood ratio, denoted as... Then, from the posterior log-likelihood ratio... The mean and variance are derived, i.e., the estimators of the joint nonlinear end. and its variance ,

[0131] ,

[0132] .

[0133] S27, Joint Nonlinear Estimator Estimator and its variance After orthogonal operation, we obtain and ,

[0134] ,

[0135] .

[0136] S28 Obtained through cross-domain transformation and will Input to the linear terminal,

[0137]

[0138] S29. Repeat S22-S28 until... The final output is based on hard verdict .

[0139] For the achievable rate analysis of the above-mentioned joint CD-OAMP detection and decoding scheme based on random multiplexing, this invention analyzes its achievable rate through the state evolution of CD-OAMP. Let... Let represent the composite function of the entire estimation process involving the nonlinear side. Let the estimation error of the linear side be... The estimation error of the joint nonlinear end is The state evolution is then given by the following iterative process.

[0140] ,

[0141] ,

[0142] ,

[0143] make For state evolution iteration The subsequent linear end estimation error, then The achievable speed of JDD based on random reuse after the nth iteration is

[0144] .

[0145] The simulation verification process in this embodiment is as follows:

[0146] The multi-fading stream channel model used in the simulation:

[0147] This invention uses a series of independent and identically distributed fading coefficients to characterize multiple fading streams; this model is applicable in both the time and frequency domains. The channel gain remains almost constant in each continuous stream, but varies independently across different continuous streams. The baseband channel model for fading streams is expressed as:

[0148]

[0149] in, It is used for index inclusion A collection of independent fading streams; Represents the received signal vector; Represents the transmitted signal vector; This represents a noise vector that follows a normal distribution. Then, this represents the fading coefficient. Without loss of generality, we assume that the fading coefficient satisfies... The order is descending. A fading stream occupies The symbol length is assumed, without loss of generality, to be equal to the length of all fading streams, i.e., satisfying... At this point, the total symbol length of the system is .

[0150] After distributing the injection power to the multi-fading flow, the first The baseband channel model of fading stream is expressed as:

[0151]

[0152] Among them, power is only allocated to those normalized noise powers. Below the water level The decline of the trend. Is assigned to the first The power of each fading current is given by the following formula.

[0153] ,

[0154] in max ,and We obtain the following equation:

[0155] .

[0156] make ,in ,and This indicates that power has been allocated (i.e. The set of fading streams. The transmission of the communication system is restricted to this active set. The total symbol length is Therefore, the effective channel model used in this invention is:

[0157] .

[0158] Distributed power With channel gain Monotonically increasing. This water-filling process amplifies the differences between effective channel gains, making the allocated gains... Compared to the original gain The differences between them are even greater. Therefore, the water-filling algorithm enhances the differences in channel gain while maintaining the key characteristics of multi-fading streams.

[0159] This invention assumes that the signal power has been normalized, that is The signal-to-noise ratio is defined as the reciprocal of the noise power, i.e. Its effective channel capacity is given by the following formula.

[0160] .

[0161] Parameter Description

[0162] This invention assumes that the transmitter has already used water-filled power allocation, and the equivalent channel gain after water filling is: During simulation It is determined by the following two conditions. (1) The channel gain has been normalized, that is, it satisfies the following conditions. (2) The bit rate that matches the corresponding fading stream. Achieve on AWGN channel The signal-to-noise ratio at the block error rate satisfies This condition ensures that all links can maintain a uniform transmit signal-to-noise ratio. Go to work.

[0163] The total symbol length, i.e. the code length, is The code length is adjustable; it can be a short code, for example... ; medium-length codes, for example Long codes, for example .

[0164] like Figure 4As shown, in a two-fading flow, i.e. The code length is bitrate , Performance comparisons of various systems were conducted. Baseline 1 is a scheme using only one AWGN code in existing practical systems; Baseline 2 is a "first-class decoding" scheme using multiple matching AWGN codes to handle multi-fading streams; CDD is a cascaded detection decoding scheme based on random multiplexing and CD-OAMP; JDD is a joint detection decoding scheme based on random multiplexing and CD-OAMP. The results show that JDD has a 0.6dB gain over Baseline 1 and a 2.7dB gain over Baseline 2; CDD has a 0.2dB gain over Baseline 1 and a 2.3dB gain over Baseline 2.

[0165] like Figure 5 As shown, in a two-fading flow, i.e. The code length is bitrate , Performance comparisons of various systems were conducted. Baseline 1 is a scheme using only one AWGN code in existing practical systems; Baseline 2 is a "first-class decoding" scheme using multiple matching AWGN codes to handle multi-fading streams; CDD is a cascaded detection decoding scheme based on random multiplexing and CD-OAMP; JDD is a joint detection decoding scheme based on random multiplexing and CD-OAMP. The results show that JDD has a 2.2dB gain compared to Baseline 1 and a 1.3dB gain compared to Baseline 2.

[0166] Corresponding to the aforementioned embodiment of a one-code-multiplexed transmission method based on random multiplexing and joint detection decoding, the present invention also provides an embodiment of a one-code-multiplexed transmission device based on random multiplexing and joint detection decoding.

[0167] See Figure 6 The present invention provides a one-code-multiplexed-stream transmission device based on random multiplexing and joint detection decoding, comprising a memory and one or more processors. The memory stores executable code, and when the processor executes the executable code, it is used to implement a one-code-multiplexed-stream transmission method based on random multiplexing and joint detection decoding in the above embodiment.

[0168] The embodiment of the one-code-multiplexed-stream transmission device based on random multiplexing and joint detection decoding provided by this invention can be applied to any device with data processing capabilities, such as a computer. The device embodiment can be implemented in software, hardware, or a combination of both. Taking software implementation as an example, as a logical device, it is formed by the processor of any data processing device loading the corresponding computer program instructions from non-volatile memory into memory for execution. From a hardware perspective, such as... Figure 6 The diagram shown is a hardware structure diagram of any device with data processing capabilities, which is a one-code multi-stream transmission device based on random multiplexing and joint detection decoding provided by the present invention. Except for... Figure 6 In addition to the processor, memory, network interface, and non-volatile memory shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.

[0169] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0170] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the present invention according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0171] This invention also provides a computer-readable storage medium storing a program thereon, which, when executed by a processor, implements a one-code-multi-stream transmission method based on random multiplexing and joint detection decoding as described in the above embodiments.

[0172] The computer-readable storage medium can be an internal storage unit of any data processing device described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device of any data processing device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units and external storage devices of any data processing device. The computer-readable storage medium is used to store the computer program and other programs and data required by the data processing device, and can also be used to temporarily store data that has been output or will be output.

[0173] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the aforementioned one-code-multi-stream transmission method based on random multiplexing and joint detection decoding.

[0174] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0175] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this application. This application is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A one-code multi-stream transmission method based on random multiplexing and joint detection decoding, characterized in that, The method includes: randomly multiplexing the original signal at the transmitting end to evenly distribute the signal energy across all fading branches; the random multiplexing of the original signal at the transmitting end specifically involves: Original signal Through an orthogonal random matrix independent of the channel and signal Random multiplexing is performed, and the baseband model of the system after random multiplexing is as follows: ； in Represents the received signal vector; Represents the transmitted signal vector; This represents a noise vector that follows a normal distribution. Then it means the first The fading coefficient of each fading stream; This represents the set of fading flows that have been allocated power. The receiver receives the signal transmitted from the transmitter and performs iterative processing using CD-OAMP combined with a standard decoder. The linear estimator of CD-OAMP performs linear minimum mean square error estimation, and the nonlinear estimator performs symbol-by-symbol demodulation. The process is iterated until convergence to obtain the decoding result with inter-symbol interference removed. The CD-OAMP combined with the standard decoder specifically includes a cascaded CD-OAMP detection decoder receiver or a combined CD-OAMP detection decoder receiver; The cascaded CD-OAMP detection decoder receiver is specifically configured such that: first, the CD-OAMP detector iterates until convergence, and then an independent AWGN decoder processes the detector's output; The joint CD-OAMP detector-decoder receiver specifically integrates the CD-OAMP detector and decoder into a unified iterative process.

2. The one-code-multiplexed transmission method based on random multiplexing and joint detection decoding according to claim 1, characterized in that, The linear estimator for CD-OAMP is specifically as follows: Based on the system baseband model after random multiplexing For a constrained linear estimator, let , ； ； in, It consists of a set of fading coefficients ( The equivalent channel matrix of the multiple fading streams, composed of ) It is the estimator of the linear estimator. It is the variance of the estimator of the linear estimator. For noise power, , ; For orthogonal operations, The variance of the estimator for the nonlinear estimator. Then it means the first The fading coefficient of each fading flow, where B is the number of fading flows. It is the vector input to the linear end after the estimator of the nonlinear end undergoes orthogonal and cross-domain transformation.

3. The one-code-multiplexed transmission method based on random multiplexing and joint detection decoding according to claim 1, characterized in that, The nonlinear estimator in the cascaded CD-OAMP detection decoder receiver is: correspond A constrained nonlinear estimator, i.e., a signal transmitter. The first in a symbol obey Distribution; Let Represents a priori constellation chart, ； ； in, It is the estimation function for the nonlinear end. It is an estimator for symbol-by-symbol demodulation at the nonlinear end. It is the variance of the nonlinear end estimator; It is the vector input to the nonlinear end after the estimator of the linear end undergoes cross-domain transformation and orthogonal operation.

4. The one-code-multiplexed transmission method based on random multiplexing and joint detection decoding according to claim 3, characterized in that, The vector input to the nonlinear end after the estimator of the linear end undergoes cross-domain transformation and orthogonal operation is specifically as follows: ； in ; ; For orthogonal operations, ； It is the estimator of the linear estimator. It is the variance of the estimator of the linear estimator. Orthogonal random matrices are used for random reuse; To output the final estimated value, It is the orthogonal linear estimate of the variance. It is the nonlinear estimate of variance after orthogonalization.

5. The one-code-multiplexed transmission method based on random multiplexing and joint detection decoding according to claim 1, characterized in that, During the iterative process of the joint CD-OAMP detection decoding receiver, The decoder uses the prior log-likelihood ratio provided by the demodulator. To calculate the posterior log-likelihood ratio, denoted as... Then, from the posterior log-likelihood ratio The derived mean and variance are passed to the linear estimator; the initial state is... The final output is based on hard verdict ,in This represents the estimation function for the nonlinear end.

6. The one-code-multiplexed transmission method based on random multiplexing and joint detection decoding according to claim 5, characterized in that, In the nonlinear estimator of the joint CD-OAMP detection decoder receiver, the nonlinear end estimator... and its variance Given by the following formula: ； ； in This represents the estimation function of the decoder.

7. A one-code-multiplexed transmission device based on random multiplexing and joint detection decoding, comprising a memory and one or more processors, wherein the memory stores executable code, characterized in that, When the processor executes the executable code, it implements a one-code multi-stream transmission method based on random multiplexing and joint detection decoding as described in any one of claims 1-6.

8. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements a one-code multi-stream transmission method based on random multiplexing and joint detection decoding as described in any one of claims 1-6.

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