Existing minimum-mean-squared-error (MMSE) transceiver designs in amplified-and-forward (AF) multiple-input multiple-output (MIMO) two-way relay systems all assume a linear precoder at the sources. Non-linear source p...Existing minimum-mean-squared-error (MMSE) transceiver designs in amplified-and-forward (AF) multiple-input multiple-output (MIMO) two-way relay systems all assume a linear precoder at the sources. Non-linear source precoders in such a system have not been considered yet. In this paper, we study the joint design of source Tomlinson-Harashima precoders (THPs), relay linear precoder and MMSE receivers in two-way relay systems. This joint design problem is a highly nonconvex optimization problem. By dividing the original problem into three sub-problems, we propose an iterative algorithm to optimize precoders and receivers. The convergence of the algorithm is ensured since the updated solution is optimal to each sub-problem. Numerical simulation results show that the proposed iterative algorithm outperforms other algorithms in the high signal-to-noise ratio (SNR) region.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
In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and no...In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.展开更多
Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works abo...Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output（MIMO） communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems.展开更多
This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and t...This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.展开更多
The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced pr...The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.展开更多
Joint sub-optimization of cooperative relays in Multiple-Input and Multiple-Output (MIMO) multiple relays aided communication system is discussed in this paper. Because the instantaneous channel state information of a...Joint sub-optimization of cooperative relays in Multiple-Input and Multiple-Output (MIMO) multiple relays aided communication system is discussed in this paper. Because the instantaneous channel state information of all source-relay channels and all relay-user channels is difficult to get at each relay node, an unjoined solution is designed according to the channel state information of that relay only. Then a multi-user loading algorithm is proposed to utilize the space diversity through multi-relay transmission. The simulation results show that with the newly proposed multi-user loading algorithm, the unjoined solution can achieve better system performance comparing with joint one in low SNR. However, the complexity of the former is much lower, for only partial CSI is needed.展开更多
Based on the existing incremental selection algorithm for Decode-and-Forward (DF) Multiple Input Multiple Output (MIMO) systems, a faster one which combines the incremental selection with the decremental exclussion is...Based on the existing incremental selection algorithm for Decode-and-Forward (DF) Multiple Input Multiple Output (MIMO) systems, a faster one which combines the incremental selection with the decremental exclussion is proposed. Firstly, the algorithm selects one antenna which makes the increment of the capacity greatest in every step. Then, excludes the antennas whose contribution to the capacity is less than μ% of that of the best antenna. Simulations show that the proposed algorithm achieves comparable performance to the existing one and has obviously decreased complexity under the appropriate threshold μ% .展开更多
Spatial diversity plays a significant role in wireless communication systems,including the Fourth Generation(4G)and Fifth Generation(5G)systems,and it is expected to be a fundamental part of the future wireless commun...Spatial diversity plays a significant role in wireless communication systems,including the Fourth Generation(4G)and Fifth Generation(5G)systems,and it is expected to be a fundamental part of the future wireless communication systems as well.The Multiple-Input Multiple-Output(MIMO)technology,which is included in the IEEE 802.16j standard,still holds the most crucial position in the 4G spectrum as it promises to improve the throughput,capacity,spectral,and energy efficiency of wireless communication systems in the 2020s.This makes MIMO a viable technology for delay constrained medical and health care facilities.This paper presents an approximate closed-form expression of the ergodic capacity for the Decode-and-Forward(DF)protocol MIMO-Orthogonal Frequency Division Multiplexing(OFDM)relaying network.Although MIMO-OFDM is highly valuable for modern high-speed wireless communication systems,especially in the medical sciences,its performance degrades in multi-hop relay networks.Therefore,in this paper,an approximate closed-form expression is derived for an end-to-end ergodic capacity of multi-hop DF MIMO-OFDM wireless communication system has been presented.Monte-Carlo simulations are conducted to verify the performance of the presented analysis regarding the capacity(bits/s/Hz)for different SNR-dB values for single,2×2,4×4,and multi-hop DF MIMOOFDM systems.The presented results provide useful insights for the research on the end-to-end ergodic capacity evaluation.展开更多
Based on massive MIMO （ multiple-input multiple-output） （M2M） systems, in order to avoid pilot contamination and improve the performance of rapacity, a pilot training transmission scheme was designed for pilot dec...Based on massive MIMO （ multiple-input multiple-output） （M2M） systems, in order to avoid pilot contamination and improve the performance of rapacity, a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal mbearriers of OFDM （ orthogonal frequency division multiplexing） during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase. The massive M2M system included a single relay station, multiple paired source nodes and destination nodes. Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems. After some mathematical manipulation to sum-rate, the cost function of sum.rate was expressed as quadratic optimizing expressions which could be solved by regular convex optlmiTation softwares. Different from existing algorithms, the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement. Simulations indicate the effectiveness of the proposed optimal precoding system. The proposed scheme not only can reduce pilot contamination, but also can improve performance of bit-error-rate （BER） as wed as sum- rate contrast to existing algorithms. In addition, it shows that the proposed M2M massive MIMO system works steadily when the number of users increases in large scale.展开更多
The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-inpu...The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.展开更多
Codebooks have been indispensable for wireless communication standard since the first release of the Long-Term Evolution in 2009.They offer an efficient way to acquire the channel state information(CSI)for multiple an...Codebooks have been indispensable for wireless communication standard since the first release of the Long-Term Evolution in 2009.They offer an efficient way to acquire the channel state information(CSI)for multiple antenna systems.Nowadays,a codebook is not limited to a set of pre-defined precoders,it refers to a CSI feedback framework,which is more and more sophisticated.In this paper,we review the codebooks in 5G New Radio(NR)standards.The codebook timeline and the evolution trend are shown.Each codebook is elaborated with its motivation,the corresponding feedback mechanism,and the format of the precoding matrix indicator.Some insights are given to help grasp the underlying reasons and intuitions of these codebooks.Finally,we point out some unresolved challenges of the codebooks for future evolution of the standards.In general,this paper provides a comprehensive review of the codebooks in 5G NR and aims to help researchers understand the CSI feedback schemes from a standard and industrial perspective.展开更多
Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance ...Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance in multiple-input multipleoutput(MIMO)scenario with antenna selection(AS)scheme.We first derive the analytical expressions of average secrecy capacity(ASC)and secrecy outage probability(SOP)by the first order Marcum Q function.Then,the asymptotic expressions of ASC and SOP in two specific scenarios are further derived.The correctness of analytical and asymptotic expressions is verified by Monte Carlo simulations.The conclusions suggest that the analytical expressions of ASC and SOP are related to the product of transmitting and receiving antennas;increasing the number of antennas is beneficial to ASC and SOP.Besides,when the target rate is set at a low level,strong channel correlation is bad for ASC,but is beneficial to SOP.展开更多
The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this con...The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this context,age of information(AoI),as the metric of information freshness,gets more and more recognition,and simultaneously,the status packet blocklength plays an important role in improving the information freshness.In this work,we firstly consider a case with perfect channel state information(CSI)at the base station(BS),and derive the closed-form expression of the average AoI by using the Shannon theory.Guided by this,we obtain the tradeoff relationship among the status packet blocklength,transmission time and transmission failure probability.Accordingly,we optimize the status packet blocklength to minimize the average AoI.Then,we consider a more practical case with finite blocklength and imperfect CSI at the BS.In this case,we exploit pilot sequence to assist channel estimation,and derive an approximated closed-form expression of the average AoI according to short packet communication theory.It is found that increasing pilot block-length can improve the accuracy of channel estimation but reduce the frequency of status updates.Hence,we jointly optimize the pilot blocklength and status packet blocklength to improve the AoI performance.Extensive simulation results validate that the proposed methods can achieve almost the same performance as the exhaustive search methods.展开更多
In order to solve the control problem of multiple-input multiple-output(MIMO)systems in complex and variable control environments,a model-free adaptive LSAC-PID method based on deep reinforcement learning(RL)is propos...In order to solve the control problem of multiple-input multiple-output(MIMO)systems in complex and variable control environments,a model-free adaptive LSAC-PID method based on deep reinforcement learning(RL)is proposed in this paper for automatic control of mobile robots.According to the environmental feedback,the RL agent of the upper controller outputs the optimal parameters to the lower MIMO PID controllers,which can realize the real-time PID optimal control.First,a model-free adaptive MIMO PID hybrid control strategy is presented to realize real-time optimal tuning of control parameters in terms of soft-actor-critic(SAC)algorithm,which is state-of-the-art RL algorithm.Second,in order to improve the RL convergence speed and the control performance,a Lyapunov-based reward shaping method for off-policy RL algorithm is designed,and a self-adaptive LSAC-PID tuning approach with Lyapunov-based reward is then determined.Through the policy evaluation and policy improvement of the soft policy iteration,the convergence and optimality of the proposed LSAC-PID algorithm are proved mathematically.Finally,based on the proposed reward shaping method,the reward function is designed to improve the system stability for the line-following robot.The simulation and experiment results show that the proposed adaptive LSAC-PID approach has good control performance such as fast convergence speed,high generalization and high real-time performance,and achieves real-time optimal tuning of MIMO PID parameters without the system model and control loop decoupling.展开更多
Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,a...Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,an NLOS target localization method in unknown L-shaped corridor based ultra-wideband(UWB)multiple-input multiple-output(MIMO)radar is proposed in this paper.Firstly,the multipath propagation model of Lshaped corridor is established.Then,the localization process is analyzed by the propagation characteristics of diffraction and reflection.Specifically,two different back-projection imaging processes are performed on the radar echo,and the positions of focus regions in the two images are extracted to generate candidate targets.Furthermore,the distances of propagation paths corresponding to each candidate target are calculated,and then the similarity between each candidate target and the target is evaluated by employing two matching factors.The locations of the targets and the width of the corridor are determined based on the matching rules.Finally,two experiments are carried out to demonstrate that the method can effectively obtain the target positions and unknown scene information even when partial paths are lost.展开更多
The fifth-generation (5G) communication requires a highly accurate estimation of the channel state information (CSI)to take advantage of the massive multiple-input multiple-output(MIMO) system. However, traditional ch...The fifth-generation (5G) communication requires a highly accurate estimation of the channel state information (CSI)to take advantage of the massive multiple-input multiple-output(MIMO) system. However, traditional channel estimation methods do not always yield reliable estimates. The methodology of this paper consists of deep residual shrinkage network (DRSN)neural network-based method that is used to solve this problem.Thus, the channel estimation approach, based on DRSN with its learning ability of noise-containing data, is first introduced. Then,the DRSN is used to train the noise reduction process based on the results of the least square (LS) channel estimation while applying the pilot frequency subcarriers, where the initially estimated subcarrier channel matrix is considered as a three-dimensional tensor of the DRSN input. Afterward, a mixed signal to noise ratio (SNR) training data strategy is proposed based on the learning ability of DRSN under different SNRs. Moreover, a joint mixed scenario training strategy is carried out to test the multi scenarios robustness of DRSN. As for the findings, the numerical results indicate that the DRSN method outperforms the spatial-frequency-temporal convolutional neural networks (SF-CNN)with similar computational complexity and achieves better advantages in the full SNR range than the minimum mean squared error (MMSE) estimator with a limited dataset. Moreover, the DRSN approach shows robustness in different propagation environments.展开更多
多输入多输出(MIMO,Multiple-Input Multiple-Output)雷达用多个发射天线同时发射多个独立信号照射目标,并使用多个接收天线接收目标回波信号.本文研究了MIMO雷达中参数估计的稳健性问题.本文应用幅度相位估计(APES,Amplitude and Phase...多输入多输出(MIMO,Multiple-Input Multiple-Output)雷达用多个发射天线同时发射多个独立信号照射目标,并使用多个接收天线接收目标回波信号.本文研究了MIMO雷达中参数估计的稳健性问题.本文应用幅度相位估计(APES,Amplitude and Phase EStimation)技术,利用目标的方位角最大似然估计值,得到了衰落向量的APES估计算法.考虑到方位角估计的不准确性,借鉴稳健的Capon波束形成器的设计思想,本文推导了衰落向量的稳健的APES估计算法.仿真实验表明,衰落向量的APES算法与稳健的APES算法性能十分接近.因此,衰落向量的APES估计算法是稳健的.展开更多
基金the China National Science and Technology Major Project "New generation broadband wireless-mobile communication networks" (No. 2011ZX03001-002-01)
文摘Existing minimum-mean-squared-error (MMSE) transceiver designs in amplified-and-forward (AF) multiple-input multiple-output (MIMO) two-way relay systems all assume a linear precoder at the sources. Non-linear source precoders in such a system have not been considered yet. In this paper, we study the joint design of source Tomlinson-Harashima precoders (THPs), relay linear precoder and MMSE receivers in two-way relay systems. This joint design problem is a highly nonconvex optimization problem. By dividing the original problem into three sub-problems, we propose an iterative algorithm to optimize precoders and receivers. The convergence of the algorithm is ensured since the updated solution is optimal to each sub-problem. Numerical simulation results show that the proposed iterative algorithm outperforms other algorithms in the high signal-to-noise ratio (SNR) region.
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.
文摘In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61331007,61361166008,and 61401065)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20120185130001)
文摘Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output（MIMO） communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems.
文摘This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.
文摘The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.
基金Supported by National Basic Research Program of China (2007CB310603)National Natural Science Foundation of China (No.60672093)National High Technology Project of China (2007AA01Z262)
文摘Joint sub-optimization of cooperative relays in Multiple-Input and Multiple-Output (MIMO) multiple relays aided communication system is discussed in this paper. Because the instantaneous channel state information of all source-relay channels and all relay-user channels is difficult to get at each relay node, an unjoined solution is designed according to the channel state information of that relay only. Then a multi-user loading algorithm is proposed to utilize the space diversity through multi-relay transmission. The simulation results show that with the newly proposed multi-user loading algorithm, the unjoined solution can achieve better system performance comparing with joint one in low SNR. However, the complexity of the former is much lower, for only partial CSI is needed.
基金Supported by the National Natural Science Foundation of Jiangsu Province(No.08KJB510015)
文摘Based on the existing incremental selection algorithm for Decode-and-Forward (DF) Multiple Input Multiple Output (MIMO) systems, a faster one which combines the incremental selection with the decremental exclussion is proposed. Firstly, the algorithm selects one antenna which makes the increment of the capacity greatest in every step. Then, excludes the antennas whose contribution to the capacity is less than μ% of that of the best antenna. Simulations show that the proposed algorithm achieves comparable performance to the existing one and has obviously decreased complexity under the appropriate threshold μ% .
文摘Spatial diversity plays a significant role in wireless communication systems,including the Fourth Generation(4G)and Fifth Generation(5G)systems,and it is expected to be a fundamental part of the future wireless communication systems as well.The Multiple-Input Multiple-Output(MIMO)technology,which is included in the IEEE 802.16j standard,still holds the most crucial position in the 4G spectrum as it promises to improve the throughput,capacity,spectral,and energy efficiency of wireless communication systems in the 2020s.This makes MIMO a viable technology for delay constrained medical and health care facilities.This paper presents an approximate closed-form expression of the ergodic capacity for the Decode-and-Forward(DF)protocol MIMO-Orthogonal Frequency Division Multiplexing(OFDM)relaying network.Although MIMO-OFDM is highly valuable for modern high-speed wireless communication systems,especially in the medical sciences,its performance degrades in multi-hop relay networks.Therefore,in this paper,an approximate closed-form expression is derived for an end-to-end ergodic capacity of multi-hop DF MIMO-OFDM wireless communication system has been presented.Monte-Carlo simulations are conducted to verify the performance of the presented analysis regarding the capacity(bits/s/Hz)for different SNR-dB values for single,2×2,4×4,and multi-hop DF MIMOOFDM systems.The presented results provide useful insights for the research on the end-to-end ergodic capacity evaluation.
基金National Natural Science Foundations of China(Nos.61505035,81470661,11604057)Science and Technology Project of Guangdong Province,China(No.2016A010101024)
文摘Based on massive MIMO （ multiple-input multiple-output） （M2M） systems, in order to avoid pilot contamination and improve the performance of rapacity, a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal mbearriers of OFDM （ orthogonal frequency division multiplexing） during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase. The massive M2M system included a single relay station, multiple paired source nodes and destination nodes. Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems. After some mathematical manipulation to sum-rate, the cost function of sum.rate was expressed as quadratic optimizing expressions which could be solved by regular convex optlmiTation softwares. Different from existing algorithms, the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement. Simulations indicate the effectiveness of the proposed optimal precoding system. The proposed scheme not only can reduce pilot contamination, but also can improve performance of bit-error-rate （BER） as wed as sum- rate contrast to existing algorithms. In addition, it shows that the proposed M2M massive MIMO system works steadily when the number of users increases in large scale.
文摘The simultaneous transmitting and reflecting reconfigurable intelligent surface(STAR-RIS)can independently adjust surface’s reflection and transmission coefficients so as to enhance space coverage.For a multiple-input multiple-output(MIMO)communication system with a STAR-RIS,a base station(BS),an eavesdropper,and multiple users,the system security rate is studied.A joint design of the power allocation at the transmitter and phase shift matrices for reflection and transmission at the STAR-RIS is conducted,in order to maximize the worst achievable security data rate(ASDR).Since the problem is nonconvex and hence challenging,a particle swarm optimization(PSO)based algorithm is developed to tackle the problem.Both the cases of continuous and discrete phase shift matrices at the STAR-RIS are considered.Simulation results demonstrate the effectiveness of the proposed algorithm and shows the benefits of using STAR-RIS in MIMO mutliuser systems.
基金supported by the Fundamental Research Funds for the Central Universitiesthe National Natural Science Foundation of China under Grant 62071191
文摘Codebooks have been indispensable for wireless communication standard since the first release of the Long-Term Evolution in 2009.They offer an efficient way to acquire the channel state information(CSI)for multiple antenna systems.Nowadays,a codebook is not limited to a set of pre-defined precoders,it refers to a CSI feedback framework,which is more and more sophisticated.In this paper,we review the codebooks in 5G New Radio(NR)standards.The codebook timeline and the evolution trend are shown.Each codebook is elaborated with its motivation,the corresponding feedback mechanism,and the format of the precoding matrix indicator.Some insights are given to help grasp the underlying reasons and intuitions of these codebooks.Finally,we point out some unresolved challenges of the codebooks for future evolution of the standards.In general,this paper provides a comprehensive review of the codebooks in 5G NR and aims to help researchers understand the CSI feedback schemes from a standard and industrial perspective.
基金supported in part by the National Natural Science Foundation of China under Grants NO.61971161 and 62171151in part by the Foundation of Heilongjiang Touyan Team under Grant NO.HITTY-20190009+3 种基金and in part by the Fundamental Research Funds for the Central Universities under Grant NO.HIT.OCEF.2021012supported in part by the Natural Science Foundation of China under Grant NO.62171160in part by the Fundamental Research Funds for the Central Universities under Grant NO.HIT.OCEF.2022055in part by the Shenzhen Science and Technology Program under Grants NO.JCYJ20190806143212658 and ZDSYS20210623091808025.
文摘Physical layer security is an important method to improve the secrecy performance of wireless communication systems.In this paper,we analyze the effect of employing channel correlation to improve security performance in multiple-input multipleoutput(MIMO)scenario with antenna selection(AS)scheme.We first derive the analytical expressions of average secrecy capacity(ASC)and secrecy outage probability(SOP)by the first order Marcum Q function.Then,the asymptotic expressions of ASC and SOP in two specific scenarios are further derived.The correctness of analytical and asymptotic expressions is verified by Monte Carlo simulations.The conclusions suggest that the analytical expressions of ASC and SOP are related to the product of transmitting and receiving antennas;increasing the number of antennas is beneficial to ASC and SOP.Besides,when the target rate is set at a low level,strong channel correlation is bad for ASC,but is beneficial to SOP.
基金supported by National Natural Science Foundation of China (Grants No. 62122094 and No.62171464)
文摘The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this context,age of information(AoI),as the metric of information freshness,gets more and more recognition,and simultaneously,the status packet blocklength plays an important role in improving the information freshness.In this work,we firstly consider a case with perfect channel state information(CSI)at the base station(BS),and derive the closed-form expression of the average AoI by using the Shannon theory.Guided by this,we obtain the tradeoff relationship among the status packet blocklength,transmission time and transmission failure probability.Accordingly,we optimize the status packet blocklength to minimize the average AoI.Then,we consider a more practical case with finite blocklength and imperfect CSI at the BS.In this case,we exploit pilot sequence to assist channel estimation,and derive an approximated closed-form expression of the average AoI according to short packet communication theory.It is found that increasing pilot block-length can improve the accuracy of channel estimation but reduce the frequency of status updates.Hence,we jointly optimize the pilot blocklength and status packet blocklength to improve the AoI performance.Extensive simulation results validate that the proposed methods can achieve almost the same performance as the exhaustive search methods.
基金the National Key R&D Program of China(No.2018YFB1308400)。
文摘In order to solve the control problem of multiple-input multiple-output(MIMO)systems in complex and variable control environments,a model-free adaptive LSAC-PID method based on deep reinforcement learning(RL)is proposed in this paper for automatic control of mobile robots.According to the environmental feedback,the RL agent of the upper controller outputs the optimal parameters to the lower MIMO PID controllers,which can realize the real-time PID optimal control.First,a model-free adaptive MIMO PID hybrid control strategy is presented to realize real-time optimal tuning of control parameters in terms of soft-actor-critic(SAC)algorithm,which is state-of-the-art RL algorithm.Second,in order to improve the RL convergence speed and the control performance,a Lyapunov-based reward shaping method for off-policy RL algorithm is designed,and a self-adaptive LSAC-PID tuning approach with Lyapunov-based reward is then determined.Through the policy evaluation and policy improvement of the soft policy iteration,the convergence and optimality of the proposed LSAC-PID algorithm are proved mathematically.Finally,based on the proposed reward shaping method,the reward function is designed to improve the system stability for the line-following robot.The simulation and experiment results show that the proposed adaptive LSAC-PID approach has good control performance such as fast convergence speed,high generalization and high real-time performance,and achieves real-time optimal tuning of MIMO PID parameters without the system model and control loop decoupling.
基金supported by National Natural Science Foundation of China(U20B2070,62001091)Sichuan Science and Technology Program(2022YFS0531).
文摘Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,an NLOS target localization method in unknown L-shaped corridor based ultra-wideband(UWB)multiple-input multiple-output(MIMO)radar is proposed in this paper.Firstly,the multipath propagation model of Lshaped corridor is established.Then,the localization process is analyzed by the propagation characteristics of diffraction and reflection.Specifically,two different back-projection imaging processes are performed on the radar echo,and the positions of focus regions in the two images are extracted to generate candidate targets.Furthermore,the distances of propagation paths corresponding to each candidate target are calculated,and then the similarity between each candidate target and the target is evaluated by employing two matching factors.The locations of the targets and the width of the corridor are determined based on the matching rules.Finally,two experiments are carried out to demonstrate that the method can effectively obtain the target positions and unknown scene information even when partial paths are lost.
基金supported by the National Key Scientific Instrument and Equipment Development Project(61827801).
文摘The fifth-generation (5G) communication requires a highly accurate estimation of the channel state information (CSI)to take advantage of the massive multiple-input multiple-output(MIMO) system. However, traditional channel estimation methods do not always yield reliable estimates. The methodology of this paper consists of deep residual shrinkage network (DRSN)neural network-based method that is used to solve this problem.Thus, the channel estimation approach, based on DRSN with its learning ability of noise-containing data, is first introduced. Then,the DRSN is used to train the noise reduction process based on the results of the least square (LS) channel estimation while applying the pilot frequency subcarriers, where the initially estimated subcarrier channel matrix is considered as a three-dimensional tensor of the DRSN input. Afterward, a mixed signal to noise ratio (SNR) training data strategy is proposed based on the learning ability of DRSN under different SNRs. Moreover, a joint mixed scenario training strategy is carried out to test the multi scenarios robustness of DRSN. As for the findings, the numerical results indicate that the DRSN method outperforms the spatial-frequency-temporal convolutional neural networks (SF-CNN)with similar computational complexity and achieves better advantages in the full SNR range than the minimum mean squared error (MMSE) estimator with a limited dataset. Moreover, the DRSN approach shows robustness in different propagation environments.
文摘多输入多输出(MIMO,Multiple-Input Multiple-Output)雷达用多个发射天线同时发射多个独立信号照射目标,并使用多个接收天线接收目标回波信号.本文研究了MIMO雷达中参数估计的稳健性问题.本文应用幅度相位估计(APES,Amplitude and Phase EStimation)技术,利用目标的方位角最大似然估计值,得到了衰落向量的APES估计算法.考虑到方位角估计的不准确性,借鉴稳健的Capon波束形成器的设计思想,本文推导了衰落向量的稳健的APES估计算法.仿真实验表明,衰落向量的APES算法与稳健的APES算法性能十分接近.因此,衰落向量的APES估计算法是稳健的.
