Ultra-reliable and low-latency communication(URLLC)is still in the early stage of research due to its two strict and conflicting requirements,i.e.,ultra-low latency and ultra-high reliability,and its impact on securit...Ultra-reliable and low-latency communication(URLLC)is still in the early stage of research due to its two strict and conflicting requirements,i.e.,ultra-low latency and ultra-high reliability,and its impact on security performance is still unclear.Specifically,short-packet communication is expected to meet the delay requirement of URLLC,while the degradation of reliability caused by it makes traditional physical-layer security metrics not applicable.In this paper,we investigate the secure short-packet transmission in uplink massive multiuser multiple-inputmultiple-output(MU-MIMO)system under imperfect channel state information(CSI).We propose an artificial noise scheme to improve the security performance of the system and use the system average secrecy throughput(AST)as the analysis metric.We derive the approximate closed-form expression of the system AST and further analyze the system asymptotic performance in two regimes.Furthermore,a one-dimensional search method is used to optimize the maximum system AST for a given pilot length.Numerical results verify the correctness of theoretical analysis,and show that there are some parameters that affect the tradeoff between security and latency.Moreover,appropriately increasing the number of antennas at the base station(BS)and transmission power at user devices(UDs)can increase the system AST to achieve the required threshold.展开更多
This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst inte...This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.展开更多
Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which ent...Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.展开更多
A symbol level secure precoding scheme based on band-region constraint of the eavesdropper’s receiving signal is proposed to enhance the energy efficiency of cell-free multiple-input multiple-output(MIMO)networks in ...A symbol level secure precoding scheme based on band-region constraint of the eavesdropper’s receiving signal is proposed to enhance the energy efficiency of cell-free multiple-input multiple-output(MIMO)networks in the presence of an eavesdropper while guaranteeing the quality of service(QoS)of user and the security of system.Moreover,to lighten its high computational complexity,original problem is divided into several cascade sub-problems firstly,and then those sub-problems are handled by combining Lagrangian dual function and improved Hooke-Jeeves method together.Comparative ex-periment with other secure symbol-level precoding schemes demonstrate that proposed scheme can achieve the lower power consumption with almost same symbol error rate and QoS of user.展开更多
For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in ...For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.展开更多
Differential spatial modulation(DSM)is a multiple-input multiple-output(MIMO)transmission scheme.It has attracted extensive research interest due to its ability to transmit additional data without increasing any radio...Differential spatial modulation(DSM)is a multiple-input multiple-output(MIMO)transmission scheme.It has attracted extensive research interest due to its ability to transmit additional data without increasing any radio frequency chain.In this paper,DSM is investigated using two mapping algorithms:Look-Up Table Order(LUTO)and Permutation Method(PM).Then,the bit error rate(BER)performance and complexity of the two mapping algorithms in various antennas and modulation methods are verified by simulation experiments.The results show that PM has a lower BER than the LUTO mapping algorithm,and the latter has lower complexity than the former.展开更多
Holographic multiple-input multiple-output(HMIMO)has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems.The increasing antenna apertu...Holographic multiple-input multiple-output(HMIMO)has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems.The increasing antenna aperture leads to a more significant characterization of the spherical wavefront in near-field communications in HMIMO scenarios.Beam training as a key technique for wireless communication is worth exploring in this near-field scenario.Compared with the widely researched far-field beam training,the increased dimensionality of the search space for near-field beam training poses a challenge to the complexity and accuracy of the proposed algorithm.In this paper,we introduce several typical near-field beam training methods:exhaustive beam training,hierarchical beam training,and multi-beam training that includes equal interval multi-beam training and hash multi-beam training.The performances of these methods are compared through simulation analysis,and their effectiveness is verified on the hardware testbed as well.Additionally,we provide application scenarios,research challenges,and potential future research directions for near-field beam training.展开更多
This paper investigates the device-to-device(D2 D) communication underlaying multi-user multi-input multi-output(MU-MIMO) cellular networks. It is assumed that D2 D users reuse the downlink time-frequency resources of...This paper investigates the device-to-device(D2 D) communication underlaying multi-user multi-input multi-output(MU-MIMO) cellular networks. It is assumed that D2 D users reuse the downlink time-frequency resources of cellular links, and the base station(BS) is assumed to be equipped with multiple antennas. We investigate the ergodic achievable sum rate of the system when the interference cancellation(IC) precoding strategy is employed at the BS. The distributions of the received signal-to-interference-plus-noise ratio(SINR) for each link are firstly analyzed, and an exact ergodic achievable sum rate of the whole system with closedform expressions is then derived. Furthermore, we present novel upper and lower bounds with simpler expressions, which are later verified to be fairly close to the Monte-Carlo simulations. All the expressions we presented are suitable for arbitrary network topology and arbitrary number of antennas at BS. Based on the derived bounds, the influence of the antennas at BS on system performance is then analyzed. We reveal that the system performance increases along with the number of antennas at BS in a logarithmic way. The accuracy of our analytical results is validated via comparisons with Monte-Carlo simulations.展开更多
This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the b...This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.展开更多
基金supported by the National Key R&D Program of China under Grant 2018YFB1801103the National Natural Science Foundation of China under Grant(no.62171464,no.62122094)。
文摘Ultra-reliable and low-latency communication(URLLC)is still in the early stage of research due to its two strict and conflicting requirements,i.e.,ultra-low latency and ultra-high reliability,and its impact on security performance is still unclear.Specifically,short-packet communication is expected to meet the delay requirement of URLLC,while the degradation of reliability caused by it makes traditional physical-layer security metrics not applicable.In this paper,we investigate the secure short-packet transmission in uplink massive multiuser multiple-inputmultiple-output(MU-MIMO)system under imperfect channel state information(CSI).We propose an artificial noise scheme to improve the security performance of the system and use the system average secrecy throughput(AST)as the analysis metric.We derive the approximate closed-form expression of the system AST and further analyze the system asymptotic performance in two regimes.Furthermore,a one-dimensional search method is used to optimize the maximum system AST for a given pilot length.Numerical results verify the correctness of theoretical analysis,and show that there are some parameters that affect the tradeoff between security and latency.Moreover,appropriately increasing the number of antennas at the base station(BS)and transmission power at user devices(UDs)can increase the system AST to achieve the required threshold.
基金supported by the National Key Laboratory of Wireless Communications Foundation,China (IFN20230204)。
文摘This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.
基金supported by National Natural Science Foundation of China(62371225,62371227)。
文摘Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.
基金the National Natural Science Foundation of China(No.61976080)the Key Research Projects in Henan Province of China(No.231111212500).
文摘A symbol level secure precoding scheme based on band-region constraint of the eavesdropper’s receiving signal is proposed to enhance the energy efficiency of cell-free multiple-input multiple-output(MIMO)networks in the presence of an eavesdropper while guaranteeing the quality of service(QoS)of user and the security of system.Moreover,to lighten its high computational complexity,original problem is divided into several cascade sub-problems firstly,and then those sub-problems are handled by combining Lagrangian dual function and improved Hooke-Jeeves method together.Comparative ex-periment with other secure symbol-level precoding schemes demonstrate that proposed scheme can achieve the lower power consumption with almost same symbol error rate and QoS of user.
基金This work was supported by the National Natural Science Foundation of China(62073093)the Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province(LBH-Q19098)+1 种基金the Heilongjiang Provincial Natural Science Foundation of China(LH2020F017)the Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology.
文摘For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant No.62061024the Project of Gansu Province Science and Technology Department under Grant No.22ZD6GA055.
文摘Differential spatial modulation(DSM)is a multiple-input multiple-output(MIMO)transmission scheme.It has attracted extensive research interest due to its ability to transmit additional data without increasing any radio frequency chain.In this paper,DSM is investigated using two mapping algorithms:Look-Up Table Order(LUTO)and Permutation Method(PM).Then,the bit error rate(BER)performance and complexity of the two mapping algorithms in various antennas and modulation methods are verified by simulation experiments.The results show that PM has a lower BER than the LUTO mapping algorithm,and the latter has lower complexity than the former.
文摘Holographic multiple-input multiple-output(HMIMO)has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems.The increasing antenna aperture leads to a more significant characterization of the spherical wavefront in near-field communications in HMIMO scenarios.Beam training as a key technique for wireless communication is worth exploring in this near-field scenario.Compared with the widely researched far-field beam training,the increased dimensionality of the search space for near-field beam training poses a challenge to the complexity and accuracy of the proposed algorithm.In this paper,we introduce several typical near-field beam training methods:exhaustive beam training,hierarchical beam training,and multi-beam training that includes equal interval multi-beam training and hash multi-beam training.The performances of these methods are compared through simulation analysis,and their effectiveness is verified on the hardware testbed as well.Additionally,we provide application scenarios,research challenges,and potential future research directions for near-field beam training.
基金supported by the Natural Science Foundation of Jiangsu Province (No. BK20170758)the National Natural Science Foundation for Young Scholars of China (No. 61701201)+1 种基金the Natural Science Foundation for colleges and universities of Jiangsu Province (No. 17KJB510011)Project of Key Laboratory of Wireless Communications of Jiangsu Province
文摘This paper investigates the device-to-device(D2 D) communication underlaying multi-user multi-input multi-output(MU-MIMO) cellular networks. It is assumed that D2 D users reuse the downlink time-frequency resources of cellular links, and the base station(BS) is assumed to be equipped with multiple antennas. We investigate the ergodic achievable sum rate of the system when the interference cancellation(IC) precoding strategy is employed at the BS. The distributions of the received signal-to-interference-plus-noise ratio(SINR) for each link are firstly analyzed, and an exact ergodic achievable sum rate of the whole system with closedform expressions is then derived. Furthermore, we present novel upper and lower bounds with simpler expressions, which are later verified to be fairly close to the Monte-Carlo simulations. All the expressions we presented are suitable for arbitrary network topology and arbitrary number of antennas at BS. Based on the derived bounds, the influence of the antennas at BS on system performance is then analyzed. We reveal that the system performance increases along with the number of antennas at BS in a logarithmic way. The accuracy of our analytical results is validated via comparisons with Monte-Carlo simulations.
基金supported by the National Natural Science Foundation of China(Grant Nos.61071163,61271327,and 61471191)the Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics,China(Grant No.BCXJ14-08)+2 种基金the Funding of Innovation Program for Graduate Education of Jiangsu Province,China(Grant No.KYLX 0277)the Fundamental Research Funds for the Central Universities,China(Grant No.3082015NP2015504)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PADA),China
文摘This paper addresses the direction of arrival （DOA） estimation problem for the co-located multiple-input multiple- output （MIMO） radar with random arrays. The spatially distributed sparsity of the targets in the background makes com- pressive sensing （CS） desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to ac- curately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio （SNR） scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification （MUSIC） algorithm and other CS recovery algorithms.
