The orthogonal time frequency space(OTFS)modulation has emerged as a promis⁃ing modulation scheme for wireless communications in high-mobility scenarios.An efficient detector is of paramount importance to harvesting t...The orthogonal time frequency space(OTFS)modulation has emerged as a promis⁃ing modulation scheme for wireless communications in high-mobility scenarios.An efficient detector is of paramount importance to harvesting the time and frequency diversities promised by OTFS.Recently,some message passing based detectors have been developed by exploiting the features of the OTFS channel matrices.In this paper,we provide an overview of some re⁃cent message passing based OTFS detectors,compare their performance,and shed some light on potential research on the design of message passing based OTFS receivers.展开更多
The extra-large scale multiple-input multiple-output(XL-MIMO)for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access service.However,th...The extra-large scale multiple-input multiple-output(XL-MIMO)for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access service.However,the extremely large antenna array aperture arouses the channel near-field effect,resulting in the deteriorated data rate and other challenges in the practice communication systems.Meanwhile,multi-panel MIMO technology has attracted extensive attention due to its flexible configuration,low hardware cost,and wider coverage.By combining the XL-MIMO and multi-panel array structure,we construct multi-panel XL-MIMO and apply it to massive Internet of Things(IoT)access.First,we model the multi-panel XL-MIMO-based near-field channels for massive IoT access scenarios,where the electromagnetic waves corresponding to different panels have different angles of arrival/departure(AoAs/AoDs).Then,by exploiting the sparsity of the near-field massive IoT access channels,we formulate a compressed sensing based joint active user detection(AUD)and channel estimation(CE)problem which is solved by AMP-EM-MMV algorithm.The simulation results exhibit the superiority of the AMP-EM-MMV based joint AUD and CE scheme over the baseline algorithms.展开更多
The uplink of mobile satellite communication(MSC) system with hundreds of spot beams is essentially a multiple-input multiple-output(MIMO) channel. Dual-turbo iterative detection and decoding as a kind of MIMO receive...The uplink of mobile satellite communication(MSC) system with hundreds of spot beams is essentially a multiple-input multiple-output(MIMO) channel. Dual-turbo iterative detection and decoding as a kind of MIMO receiver, which exchanges soft extrinsic information between a soft-in soft-out(SISO) detector and an SISO decoder in an iterative fashion, is an efficient method to reduce the uplink inter-beam-interference(IBI),and so the receiving bit error rate(BER).We propose to replace the linear SISO detector of traditional dual-turbo iterative detection and decoding with the AMP detector for the low-density parity-check(LDPC) coded multibeam MSC uplink. This improvement can reduce the computational complexity and achieve much lower BER.展开更多
Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)systems.However,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complex...Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)systems.However,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complexity,resulting in slow convergence or high complexity.To address this issue,a low-complexity Approximate Message Passing(AMP)detection algorithm with Deep Neural Network(DNN)(denoted as AMP-DNN)is investigated in this paper.Firstly,an efficient AMP detection algorithm is derived by scalarizing the simplification of Belief Propagation(BP)algorithm.Secondly,by unfolding the obtained AMP detection algorithm,a DNN is specifically designed for the optimal performance gain.For the proposed AMP-DNN,the number of trainable parameters is only related to that of layers,regardless of modulation scheme,antenna number and matrix calculation,thus facilitating fast and stable training of the network.In addition,the AMP-DNN can detect different channels under the same distribution with only one training.The superior performance of the AMP-DNN is also verified by theoretical analysis and experiments.It is found that the proposed algorithm enables the reduction of BER without signal prior information,especially in the spatially correlated channel,and has a lower computational complexity compared with existing state-of-the-art methods.展开更多
针对正交时频空(Orthogonal Time Frequency Space,OTFS)调制系统采用矩形窗函数时,信道矩阵结构复杂导致的鲁棒性差的问题,提出了一种基于时域处理和酉近似消息传递的检测算法。该算法首先添加循环前缀,将时域信道转换为分块对角矩阵;...针对正交时频空(Orthogonal Time Frequency Space,OTFS)调制系统采用矩形窗函数时,信道矩阵结构复杂导致的鲁棒性差的问题,提出了一种基于时域处理和酉近似消息传递的检测算法。该算法首先添加循环前缀,将时域信道转换为分块对角矩阵;然后应用酉变换和近似消息传递建立迭代检测算法。仿真结果表明,所提检测算法能够在不增加复杂度的条件下有效提升检测精度和鲁棒性,特别是存在信道编码的条件下表现出2 dB的性能增益,使得该算法更适用于杂散多径、高速移动等环境,具有较高的应用价值。展开更多
针对正交时频空(Orthogonal Time Frequency Space,OTFS)通信系统信号检测复杂度高的问题,提出一种改进的高斯近似消息传递(Gaussian Approximate Message Passing,GA-MP)检测算法。依据最大后验概率检测准则,对发送信号及隐变量进行逐...针对正交时频空(Orthogonal Time Frequency Space,OTFS)通信系统信号检测复杂度高的问题,提出一种改进的高斯近似消息传递(Gaussian Approximate Message Passing,GA-MP)检测算法。依据最大后验概率检测准则,对发送信号及隐变量进行逐符号高斯近似,基于置信传播算法与联合因子图进行消息传递,用边缘后验概率替代GA-MP中的外部信息以减少运算量,结合阻尼因子提升收敛速度,同时引入概率阈值减少后续更新的节点数,从而使运算复杂度得到有效降低。实验结果表明,改进后的GA-MP算法在保证误码率性能的前提下具有更低的复杂度。展开更多
Massive machine-type communications(mMTC)is envisioned to be one of the pivotal scenarios in the fifth-generation(5G)wireless communication,where the explosively emerging Internet-of-Things(IoT)applications have trigg...Massive machine-type communications(mMTC)is envisioned to be one of the pivotal scenarios in the fifth-generation(5G)wireless communication,where the explosively emerging Internet-of-Things(IoT)applications have triggered the demand for services with low-latency and high-reliability.To this end,grant-free random access paradigm has been proposed as a promising enabler in simplifying the connection procedure and significantly reducing access latency.In this paper,we propose to leverage the burgeoning reconfigurable intelligent surface(RIS)for grant-free massive access working at millimeter-wave(mmWave)frequency to further boost access reliability.By attaching independently controllable phase shifts,reconfiguring,and refracting the propagation of incident electromagnetic waves,the deployed RISs could provide additional diversity gain and enhance the access channel conditions.On this basis,to address the challenging active device detection(ADD)and channel estimation(CE)problem,we develop a joint-ADDCE(JADDCE)method by resorting to the existing approximate message passing(AMP)algorithm with expectation maximization(EM)to extract the structured common sparsity in traffic behaviors and cascaded channel matrices.Finally,simulations are carried out to demonstrate the superiority of our proposed scheme.展开更多
基金supported by the National Natural Science Foundation of Chi⁃na(61901417,U1804152,61801434)Science and Technology Re⁃search Project of Henan Province(212102210556,212102210566,212400410179).
文摘The orthogonal time frequency space(OTFS)modulation has emerged as a promis⁃ing modulation scheme for wireless communications in high-mobility scenarios.An efficient detector is of paramount importance to harvesting the time and frequency diversities promised by OTFS.Recently,some message passing based detectors have been developed by exploiting the features of the OTFS channel matrices.In this paper,we provide an overview of some re⁃cent message passing based OTFS detectors,compare their performance,and shed some light on potential research on the design of message passing based OTFS receivers.
基金supported by National Key Research and Development Program of China under Grants 2021YFB1600500,2021YFB3201502,and 2022YFB3207704Natural Science Foundation of China(NSFC)under Grants U2233216,62071044,61827901,62088101 and 62201056+1 种基金supported by Shandong Province Natural Science Foundation under Grant ZR2022YQ62supported by Beijing Nova Program,Beijing Institute of Technology Research Fund Program for Young Scholars under grant XSQD-202121009.
文摘The extra-large scale multiple-input multiple-output(XL-MIMO)for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access service.However,the extremely large antenna array aperture arouses the channel near-field effect,resulting in the deteriorated data rate and other challenges in the practice communication systems.Meanwhile,multi-panel MIMO technology has attracted extensive attention due to its flexible configuration,low hardware cost,and wider coverage.By combining the XL-MIMO and multi-panel array structure,we construct multi-panel XL-MIMO and apply it to massive Internet of Things(IoT)access.First,we model the multi-panel XL-MIMO-based near-field channels for massive IoT access scenarios,where the electromagnetic waves corresponding to different panels have different angles of arrival/departure(AoAs/AoDs).Then,by exploiting the sparsity of the near-field massive IoT access channels,we formulate a compressed sensing based joint active user detection(AUD)and channel estimation(CE)problem which is solved by AMP-EM-MMV algorithm.The simulation results exhibit the superiority of the AMP-EM-MMV based joint AUD and CE scheme over the baseline algorithms.
基金supported by the National Natural Science Foundation of China under Grants 61320106003 and 61401095the Civil Aerospace Technologies Research Project under Grant D010109The Fundamental Research Funds for the Central Universities under Grant YZZ17009
文摘The uplink of mobile satellite communication(MSC) system with hundreds of spot beams is essentially a multiple-input multiple-output(MIMO) channel. Dual-turbo iterative detection and decoding as a kind of MIMO receiver, which exchanges soft extrinsic information between a soft-in soft-out(SISO) detector and an SISO decoder in an iterative fashion, is an efficient method to reduce the uplink inter-beam-interference(IBI),and so the receiving bit error rate(BER).We propose to replace the linear SISO detector of traditional dual-turbo iterative detection and decoding with the AMP detector for the low-density parity-check(LDPC) coded multibeam MSC uplink. This improvement can reduce the computational complexity and achieve much lower BER.
基金supported by Major Project of Science and Technology Research Program of Chongqing Education Commission of China(Grant No.KJZD-M201900601)China Postdoctoral Science Foundation(Grant No.2021MD703932)Project Supported by Engineering Research Center of Mobile Communications,Ministry of Education,China(Grant No.cqupt-mct-202006)。
文摘Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)systems.However,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complexity,resulting in slow convergence or high complexity.To address this issue,a low-complexity Approximate Message Passing(AMP)detection algorithm with Deep Neural Network(DNN)(denoted as AMP-DNN)is investigated in this paper.Firstly,an efficient AMP detection algorithm is derived by scalarizing the simplification of Belief Propagation(BP)algorithm.Secondly,by unfolding the obtained AMP detection algorithm,a DNN is specifically designed for the optimal performance gain.For the proposed AMP-DNN,the number of trainable parameters is only related to that of layers,regardless of modulation scheme,antenna number and matrix calculation,thus facilitating fast and stable training of the network.In addition,the AMP-DNN can detect different channels under the same distribution with only one training.The superior performance of the AMP-DNN is also verified by theoretical analysis and experiments.It is found that the proposed algorithm enables the reduction of BER without signal prior information,especially in the spatially correlated channel,and has a lower computational complexity compared with existing state-of-the-art methods.
文摘针对正交时频空(Orthogonal Time Frequency Space,OTFS)调制系统采用矩形窗函数时,信道矩阵结构复杂导致的鲁棒性差的问题,提出了一种基于时域处理和酉近似消息传递的检测算法。该算法首先添加循环前缀,将时域信道转换为分块对角矩阵;然后应用酉变换和近似消息传递建立迭代检测算法。仿真结果表明,所提检测算法能够在不增加复杂度的条件下有效提升检测精度和鲁棒性,特别是存在信道编码的条件下表现出2 dB的性能增益,使得该算法更适用于杂散多径、高速移动等环境,具有较高的应用价值。
文摘针对正交时频空(Orthogonal Time Frequency Space,OTFS)通信系统信号检测复杂度高的问题,提出一种改进的高斯近似消息传递(Gaussian Approximate Message Passing,GA-MP)检测算法。依据最大后验概率检测准则,对发送信号及隐变量进行逐符号高斯近似,基于置信传播算法与联合因子图进行消息传递,用边缘后验概率替代GA-MP中的外部信息以减少运算量,结合阻尼因子提升收敛速度,同时引入概率阈值减少后续更新的节点数,从而使运算复杂度得到有效降低。实验结果表明,改进后的GA-MP算法在保证误码率性能的前提下具有更低的复杂度。
基金supported by the National Natural Science Foundation of China(NSFC)(No.62071044)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2022D09)+1 种基金Beijing Institute of Technology Research Fund Program for Young Scholars(No.XSQD-202121009)Ensan Foundation(No.2022006).
文摘Massive machine-type communications(mMTC)is envisioned to be one of the pivotal scenarios in the fifth-generation(5G)wireless communication,where the explosively emerging Internet-of-Things(IoT)applications have triggered the demand for services with low-latency and high-reliability.To this end,grant-free random access paradigm has been proposed as a promising enabler in simplifying the connection procedure and significantly reducing access latency.In this paper,we propose to leverage the burgeoning reconfigurable intelligent surface(RIS)for grant-free massive access working at millimeter-wave(mmWave)frequency to further boost access reliability.By attaching independently controllable phase shifts,reconfiguring,and refracting the propagation of incident electromagnetic waves,the deployed RISs could provide additional diversity gain and enhance the access channel conditions.On this basis,to address the challenging active device detection(ADD)and channel estimation(CE)problem,we develop a joint-ADDCE(JADDCE)method by resorting to the existing approximate message passing(AMP)algorithm with expectation maximization(EM)to extract the structured common sparsity in traffic behaviors and cascaded channel matrices.Finally,simulations are carried out to demonstrate the superiority of our proposed scheme.
