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
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 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
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
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
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
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
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
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
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
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
This paper investigates the secrecy performance of maximal ratio combining (MRC) and selection combining (SC) with imperfect channel state information (CSI) in the physical layer. In a single-input multiple- out...This paper investigates the secrecy performance of maximal ratio combining (MRC) and selection combining (SC) with imperfect channel state information (CSI) in the physical layer. In a single-input multiple- output (SIMO) wiretap channel, a source transmits confidential messages to the destination equipped with M antennas using the MRC/SC scheme to process the received multiple signals. An eavesdropper equipped with N antennas also adopts the MRC/SC scheme to promote successful eavesdropping. We derive the exact and asymptotic closed-form expressions for the ergodic secrecy capacity (ESC) in two cases: (1) MRC with weighting errors, and (2) SC with outdated CSI. Moreover, two important indicators, namely high signal-to-noise ratio (SNR) slope and high SNR power offset, which govern ESC at the high SNR region, are derived. Finally, simulations are conducted to validate the accuracy of our proposed analytical models. Results indicate that ESC rises with the increase of the number of antennas and the received SNR at the destination, and fades with the increase of those at the eavesdropper. Another finding is that the high SNR slope is constant, while the high SNR power offset is correlated with the number of antennas at both the destination and the eavesdropper.展开更多
We propose and experimentally demonstrate a 2 x 2 imaging multiple-input-multiple-output (MIMO) Ny quist single carrier visible light communication (VLC) system based on spectral efficient 64/32-ary quadrature amp...We propose and experimentally demonstrate a 2 x 2 imaging multiple-input-multiple-output (MIMO) Ny quist single carrier visible light communication (VLC) system based on spectral efficient 64/32-ary quadrature amplitude modulation, as well as pre- and post-equalizations. Two commercially available red-green- blue light-emitting diodes (LEDs) with 3 dB bandwidth of I0 MHz and two avalanche photodiodes with 3 dB bandwidth of i00 MHz are employed. Due to the limited experiment condition, three different colors/ wavelengths are transmitted separately. The achieved data rates of red, green, and blue LED chips are 1.5 , 1.25, and 1.25 Gb/s, respectively. The resulting bit error ratios are below the 7% pre-forward error correction limit of 3.8 × 10-3 after 75 cm indoor transmission. To the best of our knowledge, this is the first experimental investigation of imaging MIMO system, and it is the highest data rate ever achieved in MIMO VLC system.展开更多
In MIMO(multiple-input,multiple-output)systems,signals from different transmitting antennas interfere at each receiving antenna and multiuser detection(MUD)algorithms may be adopted to improve the system performance.T...In MIMO(multiple-input,multiple-output)systems,signals from different transmitting antennas interfere at each receiving antenna and multiuser detection(MUD)algorithms may be adopted to improve the system performance.This paper proposes a novel multiuser detection algorithm in MIMO systems based on the idea of'belief propagation'which has achieved great accomplishment in decoding of low-density parity-check codes.The proposed algorithm has a low computation complexity proportional to the square of transmittingeceiving antenna number.Simulation results show that under low signal-to-noise ratio(SNR)circumstances,the proposed algorithm outperforms the traditional linear minimum mean square error(MMSE)detector while it encounters a'floor'of bit error rate under high SNR circumstances.So the proposed algorithm is applicable to MIMO systems with channel coding and decoding.Although in this paper the proposed algorithm is derived in MIMO systems,obviously it can be applied to ordinary code-division multiple access(CDMA)systems.展开更多
In order to suppress the influence of symmetrical noise component on multiple-input multiple-output(MIMO)sonar’s direction of arrival(DOA)estimation under the condition of low signal-to-noise ratio,we propose a DOA e...In order to suppress the influence of symmetrical noise component on multiple-input multiple-output(MIMO)sonar’s direction of arrival(DOA)estimation under the condition of low signal-to-noise ratio,we propose a DOA estimation algorithm based on covariance matrix reconstruction method.Firstly,the noise field can be decomposed into symmetrical noise field and asymmetrical noise field.We utilize symmetry property of colored noise matrix and the feature that the imaginary part of covariance matrix has no relation with the symmetry noise to remove the real part of covariance matrix.This operation helps to suppress the influence of colored noise on DOA estimation accuracy.Based on the principle of the imaginary matrix part displacement and the dimension reduction transformation method,the real part of covariance matrix is reconstructed,which helps to suppress the bilateral spectrum interference.Thereafter,Toeplitz method is applied for the covariance matrix decorrelation amendment,and a noise subspace is formed by singular value decomposition(SVD).Finally,we can estimate the DOA of target signals.Both theoretical analysis results and numerical simulation results verify the symmetrical noise suppression performance of this algorithm,and the estimation performance of target azimuth is improved obviously.This method has the characteristics of lower operational complexity,higher degrees of freedom and stronger target resolution.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
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
摘要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.
摘要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)
摘要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.
基金the China National Science and Technology Major Project "New generation broadband wireless-mobile communication networks" (No. 2011ZX03001-002-01)
摘要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.
摘要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.
摘要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 in part by the Hong Kong Research Grant Council(16209023)。
摘要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.
基金supported by the National Natural Science Foundation of China(61503408)。
摘要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.
基金National Natural Science Foundation of China under Grant 62571248 and Grant 62201266Key Laboratory of Intelligent Space TTC&O(Space Engineering University),Ministry of Education under Grant CYK2025-01-12。
摘要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.
基金supported by the National Natural Science Foundation of China(NSFC)under grant 62125108the National Science and Technology Major Project-Mobile Information Networks under Grant No.2024ZD1300700.
摘要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.
摘要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.
摘要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.
基金supported by National Natural Science Foundation of China(No.62531003)the Natural Science Foundation of Jiangsu Province under Grant BK20252019the Science and Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX230261).
摘要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.
基金supported by the National Natural Science Foundation of China(No.62571116)the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province,China(No.BK20240070).
摘要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.
基金Project supported by the National Natural Science Foundation of China (No. 61401372) and the Fundamental Research Funds for the Central Universities, China (Nos. XDJK2015B023 and XDJK2016A011)
摘要This paper investigates the secrecy performance of maximal ratio combining (MRC) and selection combining (SC) with imperfect channel state information (CSI) in the physical layer. In a single-input multiple- output (SIMO) wiretap channel, a source transmits confidential messages to the destination equipped with M antennas using the MRC/SC scheme to process the received multiple signals. An eavesdropper equipped with N antennas also adopts the MRC/SC scheme to promote successful eavesdropping. We derive the exact and asymptotic closed-form expressions for the ergodic secrecy capacity (ESC) in two cases: (1) MRC with weighting errors, and (2) SC with outdated CSI. Moreover, two important indicators, namely high signal-to-noise ratio (SNR) slope and high SNR power offset, which govern ESC at the high SNR region, are derived. Finally, simulations are conducted to validate the accuracy of our proposed analytical models. Results indicate that ESC rises with the increase of the number of antennas and the received SNR at the destination, and fades with the increase of those at the eavesdropper. Another finding is that the high SNR slope is constant, while the high SNR power offset is correlated with the number of antennas at both the destination and the eavesdropper.
基金supported by the National Natural Science Foundation of China(No.61177071)the National 863 Program of China(No.2003AA013603)the Key Program of Shanghai Science and Technology Association(No.12dz1143000)
摘要We propose and experimentally demonstrate a 2 x 2 imaging multiple-input-multiple-output (MIMO) Ny quist single carrier visible light communication (VLC) system based on spectral efficient 64/32-ary quadrature amplitude modulation, as well as pre- and post-equalizations. Two commercially available red-green- blue light-emitting diodes (LEDs) with 3 dB bandwidth of I0 MHz and two avalanche photodiodes with 3 dB bandwidth of i00 MHz are employed. Due to the limited experiment condition, three different colors/ wavelengths are transmitted separately. The achieved data rates of red, green, and blue LED chips are 1.5 , 1.25, and 1.25 Gb/s, respectively. The resulting bit error ratios are below the 7% pre-forward error correction limit of 3.8 × 10-3 after 75 cm indoor transmission. To the best of our knowledge, this is the first experimental investigation of imaging MIMO system, and it is the highest data rate ever achieved in MIMO VLC system.
基金supported by the National Natural Science Foundation of China(Grant No.60302006)the Namonal Defence Foundaton of Chuna(Grant No.514200801031W02054).
摘要In MIMO(multiple-input,multiple-output)systems,signals from different transmitting antennas interfere at each receiving antenna and multiuser detection(MUD)algorithms may be adopted to improve the system performance.This paper proposes a novel multiuser detection algorithm in MIMO systems based on the idea of'belief propagation'which has achieved great accomplishment in decoding of low-density parity-check codes.The proposed algorithm has a low computation complexity proportional to the square of transmittingeceiving antenna number.Simulation results show that under low signal-to-noise ratio(SNR)circumstances,the proposed algorithm outperforms the traditional linear minimum mean square error(MMSE)detector while it encounters a'floor'of bit error rate under high SNR circumstances.So the proposed algorithm is applicable to MIMO systems with channel coding and decoding.Although in this paper the proposed algorithm is derived in MIMO systems,obviously it can be applied to ordinary code-division multiple access(CDMA)systems.
基金supported by the National Natural Science Foundation for Young Scientists of China(51309191)the National Natural Science Foundation for Young Scientists of China(11704313)the National Natural Science Foundation for Young Scientists of China(61701405)
摘要In order to suppress the influence of symmetrical noise component on multiple-input multiple-output(MIMO)sonar’s direction of arrival(DOA)estimation under the condition of low signal-to-noise ratio,we propose a DOA estimation algorithm based on covariance matrix reconstruction method.Firstly,the noise field can be decomposed into symmetrical noise field and asymmetrical noise field.We utilize symmetry property of colored noise matrix and the feature that the imaginary part of covariance matrix has no relation with the symmetry noise to remove the real part of covariance matrix.This operation helps to suppress the influence of colored noise on DOA estimation accuracy.Based on the principle of the imaginary matrix part displacement and the dimension reduction transformation method,the real part of covariance matrix is reconstructed,which helps to suppress the bilateral spectrum interference.Thereafter,Toeplitz method is applied for the covariance matrix decorrelation amendment,and a noise subspace is formed by singular value decomposition(SVD).Finally,we can estimate the DOA of target signals.Both theoretical analysis results and numerical simulation results verify the symmetrical noise suppression performance of this algorithm,and the estimation performance of target azimuth is improved obviously.This method has the characteristics of lower operational complexity,higher degrees of freedom and stronger target resolution.
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.
摘要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.