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SEMI-BLIND CHANNEL ESTIMATION OF MULTIPLE-INPUT/MULTIPLE-OUTPUT SYSTEMS BASED ON MARKOV CHAIN MONTE CARLO METHODS 认领 引用 被引量：1
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作者 JiangWei XiangHaige 《Journal of Electronics(China)》 2004年第3期184-190,共7页
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
关键词 Multiple-Input/Multiple-Output (MIMO) system Channel estimation Markov Chain Monte Carlo (MCMC) method
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Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning 认领 引用 被引量：5
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作者 文方青 张弓 贲德 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第11期70-76,共7页
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
关键词 multiple-input multiple-output radar random arrays direction of arrival estimation sparseBayesian learning
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A new layered space-time detection algorithm for frequency selective fading multiple-input multiple-output channels based on particle filter 认领 引用 被引量：1
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作者 杜正聪 唐斌 刘立新 《Chinese Physics B》 CAS 2006年第11期2481-2488,共8页
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
关键词 particle filter multiple-input multiple-output layered space-time structure frequency selective fading channels
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Shannon information capacity of time reversal wideband multiple-input multiple-output system based on correlated statistical channels 认领 引用 被引量：3
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作者 杨瑜 王秉中 丁帅 《Chinese Physics B》 SCIE EI CAS CSCD 2016年第5期5-10,共6页
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
关键词 information entropy time reversal wideband multiple-input multiple-output（MIMO） system antenna mutual coupling
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Joint Tomlinson-Harashima Source and Linear Relay Precoder Design in Amplify-and-Forward Multiple-Input Multiple-Output Two-Way Relay Systems 认领 引用
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作者 钱成 张萌 +1 位作者 罗汉文 刘伟 《Journal of Shanghai Jiaotong university(Science)》 EI 2013年第2期180-185,共6页
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
关键词 multiple-input multiple-output (MIMO) two-way relay Tomlinson-Harashima precoding minimum- mean-square-error (MMSE)
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Performance Improvement of Multi-User Multiple-Input Multiple-Output Protocol for WLAN 认领 引用
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作者 Maha Bakalla Mznah Al-Rodhaan Yuan Tian 《Communications and Network》 2017年第2期124-141,共18页
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
关键词 Clustering Multi-User Multiple-Input Multiple-Output Multi-user Multiple-Input Multiple-Output MIMOMate Padovan Backoff Algorithm Wireless Local Arewa Network
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AI and Deep Learning for Terahertz Ultra-Massive MIMO:From Model-Driven Approaches to Foundation Models 认领 引用 被引量：1
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作者 Wentao Yu Hengtao He +4 位作者 Shenghui Song Jun Zhang Linglong Dai Lizhong Zheng Khaled B.Letaief 《Engineering》 SCIE EI CSCD 2026年第1期14-33,共20页
This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the ch... This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the characteristics of terahertz UM-MIMO systems and identifies three primary challenges for transceiver design:computational complexity,modeling difficulty,and measurement limitations.The study posits that AI provides a promising solution to these challenges.Three systematic research roadmaps are proposed for developing AI algorithms tailored to terahertz UM-MIMO systems.The first roadmap,model-driven deep learning(DL),emphasizes the importance of leveraging available domain knowledge and advocates the adoption of AI only to enhance bottleneck modules within an established signal processing or optimization framework.Four essential steps are discussed:algorithmic frameworks,basis algorithms,loss function design,and neural architecture design.The second roadmap presents channel state information(CSI)foundation models,aimed at unifying the design of different transceiver modules by focusing on their shared foundation,that is,the wireless channel.The training of a single compact foundation model is proposed to estimate the score function of wireless channels,which serve as a versatile prior for designing a wide variety of transceiver modules.Four essential steps are outlined:general frameworks,conditioning,site-specific adaptation,and the joint design of CSI foundation models and model-driven DL.The third roadmap aims to explore potential directions for applying pretrained large language models(LLMs)to terahertz UM-MIMO systems.Several application scenarios are envisioned,including LLM-based estimation,optimization,search,network management,and protocol understanding.Finally,the study highlights open problems and future research directions. 展开更多
关键词 Terahertz communications Ultra-massive multiple-input multiple-output Model-driven deep learning Foundation models Large language models
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Optimization of the frequency offset increment of FDA-MIMO based on cuckoo search algorithm 认领 引用 被引量：1
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作者 WANG Bo ZHAO Yu +2 位作者 LI Yonglin YANG Rennong XUE Junjie 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2026年第1期157-170,共14页
Frequency diverse array multiple-input multiple-output(FDA-MIMO)radar has gained considerable research attention due to its ability to effectively counter active repeater deception jamming in complex electromagnetic e... Frequency diverse array multiple-input multiple-output(FDA-MIMO)radar has gained considerable research attention due to its ability to effectively counter active repeater deception jamming in complex electromagnetic environments.The effectiveness of interference suppression by FDA-MIMO is limited by the inherent range-angle coupling issue in the FDA beampattern.Existing literature primarily focuses on control methods for FDA-MIMO radar beam direction under the assumption of static beampatterns,with insufficient exploration of techniques for managing nonstationary beam directions.To address this gap,this paper initially introduces the FDA-MIMO signal model and the calculation formula for the FDA-MIMO array output using the minimum variance distortionless response(MVDR)beamformer.Building on this,the problem of determining the optimal frequency offset for the FDA is rephrased as a convex optimization problem,which is then resolved using the cuckoo search(CS)algorithm.Simulations confirm the effectiveness of the proposed approach,showing that the frequency offsets obtained through the CS algorithm can create a dot-shaped beam direction at the target location while effectively suppressing interference signals within the mainlobe. 展开更多
关键词 frequency diverse array multiple-input multiple-output(FDA-MIMO) convex optimization cuckoo search algorithm beampattern
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Radar Beampattern Gain Maximization for MIMO Integrated Sensing and Communication Systems 认领 引用
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作者 Ren Hong Zhang Ruoyu +2 位作者 Chen Guangyi Lin Xu Wu Wen 《China Communications》 SCIE EI CSCD 2026年第2期268-284,共17页
Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for ... Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system. 展开更多
关键词 integrated sensing and communication multiple-input multiple-output performance tradeoff radar beampattern gain semidefinite relaxation
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Adaptive Denoising Diffusion Null-Space Models for Semantic Communications over MIMO Channels 认领 引用
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作者 Tao Meixia Chen Zhiyong +2 位作者 Duan Yiheng Wu Tong Zhang Hongwei 《China Communications》 SCIE EI CSCD 2026年第4期312-329,共18页
Multiple-input multiple-output(MIMO)systems are essential for improving capacity and reliability in semantic communications.Existing methods mainly design the channel-aware neural networks but neglect the underlying s... Multiple-input multiple-output(MIMO)systems are essential for improving capacity and reliability in semantic communications.Existing methods mainly design the channel-aware neural networks but neglect the underlying signal distribution.In this paper,we develop a denoising diffusion null-space model-based module over MIMO channels(DDNM-MIMO),which is a plug-in module deployed at the receiver.By modeling the MIMO channel,precoding,and equalization as a linear transformation with additive noise,we design corresponding linear and scaling matrices to construct a sampling process for denoising the received signal.The DDNM-MIMO integrates channel state information(CSI)embedding,supporting both closed-loop MIMO with CSI at the transmitter and open-loop MIMO with CSI at the receiver,thereby improving channel adaptability across various noise levels.As a plug-in,the DDNM-MIMO module operates independently of the joint source-channel coding(JSCC)coder structure,offering flexible integration into diverse systems.Experimental results show that DDNM-MIMO effectively reduces the mean square errors(MSE)between the encoded and equalized signals.Consequently,the proposed DDNM-MIMO semantic communication system achieves superior image reconstruction performance compared to existing JSCC-based semantic communication method. 展开更多
关键词 channel state information(CSI) diffusion model(DM) multiple-input multiple-output(MIMO) semantic communications
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High-performance CDRA with surface-mounted horn at 5.8 GHz to enhance wireless communication system performance 认领 引用
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作者 Hanane Bendjedi Samira Mekki +7 位作者 Sarra Khacha Djamel Sayad Yamina Tighilt Issa Elfergani Mohamed Lamine Bouknia Atul Varshney Jonathan Rodriguez Chemseddine Zebiri 《Journal of Electronic Science and Technology》 EI CAS CSCD 2026年第2期75-90,共16页
With an increasing demand for high-performance wireless communication systems,particularly in wireless local area network(WLAN)applications,there is a critical need for antennas that deliver high gain,excellent isolat... With an increasing demand for high-performance wireless communication systems,particularly in wireless local area network(WLAN)applications,there is a critical need for antennas that deliver high gain,excellent isolation,and robust diversity performance.This study introduces an improved multipleinput multiple-output(MIMO)cylindrical dielectric resonator antenna(CDRA)integrated with a cylindrical horn tailored for operation at 5.80 GHz.The design employs a single radiating element fed by two closely positioned coaxial cables to achieve high isolation between ports,whereas the cylindrical horn enhances the gain.The performance was evaluated and optimized using HFSS software,focusing on metrics such as the envelope correlation coefficient(ECC),channel capacity loss(CCL),mean effective gain(MEG),and diversity gain(DG)to ensure the MIMO compatibility.The CDRA with surface-mounted horn achieved a very high gain of 15.6 dBi by flaring the circular aperture of the circular base of the antenna in canonical form at 5.80 GHz.The results reveal a significant gain increase to 15.6 dBi,improving the signal strength and coverage,which lowers ECC<0.017,DG close to 10 dB,MEG<-3 dB,CCL<0.5 bps/Hz over the bandwidth of 5.60 GHz to 5.90 GHz,radiation efficiency of 90.1%,isolation less than -20 dB,and boosts diversity performance.The experimental testing of the prototype aligns closely with the simulated outcomes,validating the effectiveness of the design. 展开更多
关键词 Cylindrical dielectric resonator antenna Diversity gain Envelope correlation coefficient Horn antenna Isolation Multiple-input multiple-output Wireless local area network
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Multi-agent deep deterministic policy gradient algorithm for predictive UAV deployment in CF-mMIMO for identifying coverage holes 认领 引用
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作者 Kenneth Okello Elijah Mwangi Dominic Bernard Onyango Konditi 《Journal of Electronic Science and Technology》 EI CAS CSCD 2026年第2期91-108,共18页
Unmanned aerial vehicles(UAVs),due to their adaptable mobility and various applications,including supporting communication infrastructure,monitoring,and rescue,are becoming increasingly valuable,making them a valuable... Unmanned aerial vehicles(UAVs),due to their adaptable mobility and various applications,including supporting communication infrastructure,monitoring,and rescue,are becoming increasingly valuable,making them a valuable addition to emergency communication networks.Even though cell-free massive multiple-input multiple-output(CF-mMIMO)networks provide high communication data rates,their immobility makes it difficult to maintain quality network continuity in emergency,unpredictable,and congested areas where users’equipment is located.To mitigate this challenge,the integration of aerial access points(AAPs)into CF-mMIMO networks is proposed by using the multi-agent deep deterministic policy gradient(MADDPG)framework,which teaches several UAVs to jointly learn the best deployment plans by estimating user distributions and traffic demand trends on invitations to provide tremendous dynamic coverage,increased spectral efficiency(SE),and throughput maximization.The predictive component framework utilizes a long short-term memory(LSTM)network model incorporating concepts of learning,association,movement,and service provision for temporal traffic forecasting,thereby ensuring proactive UAV positioning before coverage holes emerge.Our extensive simulation results demonstrate that the MADDPG-based throughput deployment strategy achieves approximately 45 Gbps for 50 UAVs,the SE for downlink and uplink of 10.2 bps/Hz and 15.2 bps/Hz,respectively,and the minimal transmit power of 3.5 kJ as compared with the multi-agent soft actorcritic(MASAC)method,traditional heuristic-LSTM,and single-agent reinforcement learning approaches. 展开更多
关键词 Aerial access points Cell-free massive multiple-input multiple-output Long short-term memory Multi-agent deep deterministic policy gradient Unmanned aerial vehicles
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Multiuser Scheduling and Precoding in Cell-Free Massive MIMO Systems with Finite and Infinite Blocklengths 认领 引用
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作者 Fu Jiafei Zhu Pengcheng +2 位作者 Li Jiamin Jiang Yanxiang Wang Dongming 《China Communications》 SCIE EI CSCD 2026年第5期151-167,共17页
This paper centres on achieving the maximization of weighted throughput(WTP)in a multiuser cell-free massive multiple-input multiple-output(mMIMO)system with both finite blocklength(FBL)and infinite blocklength(INFBL)... This paper centres on achieving the maximization of weighted throughput(WTP)in a multiuser cell-free massive multiple-input multiple-output(mMIMO)system with both finite blocklength(FBL)and infinite blocklength(INFBL),which is conducted against the backdrop of constrained time-frequency resources.We aim to ensure quality of service(QoS)for all users,particularly in the FBL scenario,maintaining an acceptable latency and block error rate(BLER).To counteract the impact of reduced DoF of channel matrix due to a large number of users accessing the system,which leads to decreased system performance,we strive to optimize WTP by scheduling multiple users to different resource elements(REs)and applying precoding operations accordingly,subject to the limitations imposed by total power consumption per time slot and requisite QoS parameters.Simulation results demonstrate the superiority of the proposed multiuser processing(MUP)scheme over both single-user processing(SUP)and all-user processing(AUP)alternatives,and the proposed iterative algorithm based on genetic algorithm(GA)achieves up to 49.36%system performance gains compared to the benchmark algorithms.This substantiates the efficacy of our method in enhancing network performance and user satisfaction. 展开更多
关键词 cell-free(CF) finite blocklength(FBL) infinite blocklength(INFBL) massive multiple-input and multiple-output(mMIMO)
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Low-altitude UAV swarm ISAC:new opportunities and challenges 认领 引用
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作者 Hongqi MIN Dingbang YANG +1 位作者 Chenhao QI Yong ZENG 《ENGINEERING Information Technology & Electronic Engineering》 SCIE EI CSCD 2026年第4期1-16,共16页
With the rapid development of the low-altitude economy,low-altitude unmanned aerial vehicle(UAV)swarms are emerging as important components of sixth-generation(6G)mobile communication networks,facilitating“full cover... With the rapid development of the low-altitude economy,low-altitude unmanned aerial vehicle(UAV)swarms are emerging as important components of sixth-generation(6G)mobile communication networks,facilitating“full coverage”and“Internet of Intelligence.”Integrated sensing and communication(ISAC)deeply integrates sensing functionality into wireless communication networks by sharing wireless infrastructures and resources such as base stations,antennas,radio frequency chains,and signal waveforms,thereby significantly improving the performance of low-altitude UAV swarms.This paper reviews the research status of low-altitude UAV swarm ISAC systems,analyzes the new challenges arising from key features of UAV swarms,including low–slow–small characteristics,high density,large quantity,complex low-altitude environments,and high swarm coordination requirements,presents a vision for future deployment,and proposes the so-called“Ten Ones”performance metrics tailored to low-altitude UAV swarm ISAC.To realize these ambitious key performance indicators for future UAV swarm ISAC,several promising technologies are discussed,such as new array architectures,including extremely-large multiple-input multiple-output(XL-MIMO),sparse XL-MIMO,and reconfigurable antenna arrays,sparse time–frequency resource allocation,and channel knowledge maps.Furthermore,the potential of exploiting UAV swarms as airborne ISAC platforms is discussed.Finally,future research directions are outlined,offering a guideline for the design and development of low-altitude UAV swarm ISAC systems. 展开更多
关键词 Unmanned aerial vehicle(UAV)swarm Integrated sensing and communication(ISAC) Sparse extremely-large multiple-input multiple-output(XL-MIMO) Reconfigurable antenna arrays Sparse time-frequency resource allocation Channel knowledge maps(CKMs)
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基于新型MIMO技术的5G室分低成本高性能技术及应用 认领 引用 被引量：3
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作者 李建朋 魏志刚 +4 位作者 王鹏 孙正辉 仇勇 盛明威 谢慧强 《江苏通信》 2025年第2期30-36,共7页
2.6G室分主要以传统室分建设为主,通过合路存量4G室分,快速实现5G覆盖,但同时也面临单路室分性能差、峰值速率低、吞吐量受限、同频干扰明显、无源器件无法监控等突出问题。本文针对存量传统室分,从覆盖方案调优、驻留能力提升、容量性... 2.6G室分主要以传统室分建设为主,通过合路存量4G室分,快速实现5G覆盖,但同时也面临单路室分性能差、峰值速率低、吞吐量受限、同频干扰明显、无源器件无法监控等突出问题。本文针对存量传统室分,从覆盖方案调优、驻留能力提升、容量性能挖掘、智慧监控应用等方面进行融合创新,让5G室分真正做到低成本、高性能、可管控,并规模应用于生产实践。 展开更多
关键词 传统室分 MIMO(multiple-input multiple-output) 低成本 智慧室分 物联网
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Secrecy Performance Analysis Considering Channel Correlation of MIMO Scenario in Physical Layer Security 认领 引用
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作者 Zhang Jiuning Wu Xuanli +3 位作者 Xu Zhicong Zhang Tingting Xu Tao Meng Xiangyun 《China Communications》 SCIE EI CSCD 2025年第6期276-290,共15页
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
关键词 average secrecy capacity channel correlation multiple-input multiple-output physical layer security secrecy outage probability
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Analysis and Optimization of the Status Update Performance in Massive MIMO-Enabled IoT Systems 认领 引用
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作者 Yu Baoquan Wu Dan +2 位作者 Cai Yueming Yang Wendong Chen Xiaoming 《China Communications》 SCIE EI CSCD 2025年第11期84-102,共19页
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
关键词 age of information finite blocklength imperfect channel state information Internet of Things massive multiple-input multiple-output
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A Review of Codebooks for CSI Feedback in 5G New Radio and Beyond 认领 引用
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作者 Qin Ziao Yin Haifan 《China Communications》 SCIE EI CSCD 2025年第2期112-127,共16页
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
关键词 codebook CSI 5G NR frequency division duplex Multiple-Input Multiple-Output
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Non-line-of-sight target localization in unknown L-shaped corridor based UWB MIMO radar 认领 引用
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作者 JIA Chao SONG Caiping +4 位作者 WANG Lingyu CUI Guolong GUO Shisheng GU Jie JIA Yong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第3期681-693,共13页
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
关键词 non-line-of-sight(NLOS)localization unknown Lshaped corridor multiple-input multiple-output(MIMO)radar back-projection imaging multipath propagation
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Deep residual systolic network for massive MIMO channel estimation by joint training strategies of mixed-SNR and mixed-scenarios 认领 引用
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作者 SUN Meng JING Qingfeng ZHONG Weizhi 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第4期903-913,共11页
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
关键词 massive multiple-input multiple-output(MIMO) channel estimation deep residual shrinkage network(DRSN) deep convolutional neural network(CNN).
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