Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple inpu...Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.展开更多
Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a locatio...Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.展开更多
Pilot contamination can spoil the accuracy of channel estimation and then has become one of the key problems influencing the performance of massive multiple input multiple output(MIMO)systems.This paper proposes a met...Pilot contamination can spoil the accuracy of channel estimation and then has become one of the key problems influencing the performance of massive multiple input multiple output(MIMO)systems.This paper proposes a method based on cell classification and users grouping to mitigate the pilot contamination in multi-cell massive MIMO systems and improve the spectral efficiency.The pilots of the terminals are allocated onebit orthogonal identifier to diminish the cell categories by the operation of exclusive OR(XOR).At the same time,the users are divided into edge user groups and central user groups according to the large-scale fading coefficients by the clustering algorithm,and different pilot sequences are assigned to different groups.The simulation results show that the proposed method can effectively improve the spectral efficiency of multi-cell massive MIMO systems.展开更多
针对大规模MIMO系统中存在的导频污染问题,结合目前研究的基于奇异值(SVD)分解的信道估计算法,在考虑到该算法中的协方差矩阵是用有限的样本数据代替真实数据必然存在偏差的问题,给出了一种联合ILSP(Iterative Least Square with Projec...针对大规模MIMO系统中存在的导频污染问题,结合目前研究的基于奇异值(SVD)分解的信道估计算法,在考虑到该算法中的协方差矩阵是用有限的样本数据代替真实数据必然存在偏差的问题,给出了一种联合ILSP(Iterative Least Square with Projection)的基于SVD的半盲信道估计算法。仿真结果表明改进后的信道估计算法能够有效减小已有算法中存在的偏差问题,提高信道估计精确度,有效减轻导频污染给大规模MIMO系统带来的影响,从而实现大规模MIMO系统性能的提升。展开更多
For multiuser multiple-input-multiple-output (MIMO) cognitive radio (CR) networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibi...For multiuser multiple-input-multiple-output (MIMO) cognitive radio (CR) networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibility is exploited to estimate the channel state information ( CSI ) between primary (PR) terminals and CR terminals. By using channel training in the second stage of CR frame, the channels between CR terminals can be achieved. In the third stage, a multi-criteria user selection scheme is proposed to choose the best user set for service. In data transmission stage, the total capacity maximization problem is solved with the interference constraint of PR terminals. Finally, simulation results show that the multi-criteria user selection scheme, which has the ability of changing the weights of criterions, is more flexible than the other three traditional schemes and achieves a tradeoff between user fairness and system performance.展开更多
A multiuser multiple input multiple output (MIMO) broadcast scheme was proposed through applying dirty paper coding (DPC) at the transmitter and linear equalization at the receiver. Assuming single data stream communi...A multiuser multiple input multiple output (MIMO) broadcast scheme was proposed through applying dirty paper coding (DPC) at the transmitter and linear equalization at the receiver. Assuming single data stream communication for each user, joint transmitter and linear receiver design were done to enhance the system performance. Furthermore, a multiuser scheduling algorithm was presented to exploit multiuser diversity when the number of the users is larger than that of transmit antennas. The proposed system achieves the sum rate close to the Sato bound and is superior to some of the existing schemes.展开更多
Based on massive MIMO ( multiple-input multiple-output) (M2M) systems, in order to avoid pilot contamination and improve the performance of rapacity, a pilot training transmission scheme was designed for pilot dec...Based on massive MIMO ( multiple-input multiple-output) (M2M) systems, in order to avoid pilot contamination and improve the performance of rapacity, a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal mbearriers of OFDM ( orthogonal frequency division multiplexing) during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase. The massive M2M system included a single relay station, multiple paired source nodes and destination nodes. Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems. After some mathematical manipulation to sum-rate, the cost function of sum.rate was expressed as quadratic optimizing expressions which could be solved by regular convex optlmiTation softwares. Different from existing algorithms, the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement. Simulations indicate the effectiveness of the proposed optimal precoding system. The proposed scheme not only can reduce pilot contamination, but also can improve performance of bit-error-rate (BER) as wed as sum- rate contrast to existing algorithms. In addition, it shows that the proposed M2M massive MIMO system works steadily when the number of users increases in large scale.展开更多
A multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) broadcast channel is considered where both transmitter and receivers are equipped with multiple antennas. The Channel S...A multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) broadcast channel is considered where both transmitter and receivers are equipped with multiple antennas. The Channel State Information (CSI) is quantized and provided through limited feedback links. In the first part of this work, the Maximum Expected SINR Combining (MESC) strategy for feedback decrease is investigated. Then a combination of MESC with subcarrier assigning is presented to further reduce the feedback load. The basic idea is the subcarriers are partitioned into resource blocks. For each block, only one quantized channel vector is feedback. The simulation results show MESC can obtain the performance gain over the relevant combiner strategies in MIMO-OFDM system. Moreover the effectiveness on the reduction of feedback overhead by the use of partitioning blocks in the studied system is evaluated.展开更多
A novel scheme‘user assisted cooperative relaying in beamspace massive multiple input multiple output(M-MIMO)non-orthogonal multiple access(NOMA)system’has been proposed to improve coverage area,spectrum and energy ...A novel scheme‘user assisted cooperative relaying in beamspace massive multiple input multiple output(M-MIMO)non-orthogonal multiple access(NOMA)system’has been proposed to improve coverage area,spectrum and energy efficiency for millimeter wave(mmWave)communications.A downlink system for M users,where base station(BS)is equipped with beamforming lens antenna structure having NRF radio frequency(RF)chains,has been considered.A dynamic cluster of users is formed within a beam and the intermediate users(in that cluster)between beam source and destination(user)act as relaying stations.By the use of successive interference cancellation(SIC)technique of NOMA within a cluster,the relaying stations relay the symbols with improved power to the destination.For maximizing achievable sum rate,transmit precoding and dynamic power allocation for both intra and inter beam power optimization are implemented.Simulations for performance evaluation are carried out to validate that the proposed system outperforms the conventional beamspace M-MIMO NOMA system for mmWave communications in terms of spectrum and energy efficiency.展开更多
摘要Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.
基金supported by the National Natural Science Foundation of China(61901341).
摘要Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.
基金supported by the Scientific and Technological Innovation Foundation of Shunde Graduate School,USTB(BK19CF002).
摘要Pilot contamination can spoil the accuracy of channel estimation and then has become one of the key problems influencing the performance of massive multiple input multiple output(MIMO)systems.This paper proposes a method based on cell classification and users grouping to mitigate the pilot contamination in multi-cell massive MIMO systems and improve the spectral efficiency.The pilots of the terminals are allocated onebit orthogonal identifier to diminish the cell categories by the operation of exclusive OR(XOR).At the same time,the users are divided into edge user groups and central user groups according to the large-scale fading coefficients by the clustering algorithm,and different pilot sequences are assigned to different groups.The simulation results show that the proposed method can effectively improve the spectral efficiency of multi-cell massive MIMO systems.
摘要针对大规模MIMO系统中存在的导频污染问题,结合目前研究的基于奇异值(SVD)分解的信道估计算法,在考虑到该算法中的协方差矩阵是用有限的样本数据代替真实数据必然存在偏差的问题,给出了一种联合ILSP(Iterative Least Square with Projection)的基于SVD的半盲信道估计算法。仿真结果表明改进后的信道估计算法能够有效减小已有算法中存在的偏差问题,提高信道估计精确度,有效减轻导频污染给大规模MIMO系统带来的影响,从而实现大规模MIMO系统性能的提升。
基金Supported by National S&T Major Project of China(2013ZX03003002-003)
摘要For multiuser multiple-input-multiple-output (MIMO) cognitive radio (CR) networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibility is exploited to estimate the channel state information ( CSI ) between primary (PR) terminals and CR terminals. By using channel training in the second stage of CR frame, the channels between CR terminals can be achieved. In the third stage, a multi-criteria user selection scheme is proposed to choose the best user set for service. In data transmission stage, the total capacity maximization problem is solved with the interference constraint of PR terminals. Finally, simulation results show that the multi-criteria user selection scheme, which has the ability of changing the weights of criterions, is more flexible than the other three traditional schemes and achieves a tradeoff between user fairness and system performance.
基金The National Nature Science foundation of China (No. 60772100, 60372076)The Science and Technology Committee of Shanghai Municipality (No. 06DZ15013)
摘要A multiuser multiple input multiple output (MIMO) broadcast scheme was proposed through applying dirty paper coding (DPC) at the transmitter and linear equalization at the receiver. Assuming single data stream communication for each user, joint transmitter and linear receiver design were done to enhance the system performance. Furthermore, a multiuser scheduling algorithm was presented to exploit multiuser diversity when the number of the users is larger than that of transmit antennas. The proposed system achieves the sum rate close to the Sato bound and is superior to some of the existing schemes.
基金National Natural Science Foundations of China(Nos.61505035,81470661,11604057)Science and Technology Project of Guangdong Province,China(No.2016A010101024)
摘要Based on massive MIMO ( multiple-input multiple-output) (M2M) systems, in order to avoid pilot contamination and improve the performance of rapacity, a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal mbearriers of OFDM ( orthogonal frequency division multiplexing) during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase. The massive M2M system included a single relay station, multiple paired source nodes and destination nodes. Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems. After some mathematical manipulation to sum-rate, the cost function of sum.rate was expressed as quadratic optimizing expressions which could be solved by regular convex optlmiTation softwares. Different from existing algorithms, the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement. Simulations indicate the effectiveness of the proposed optimal precoding system. The proposed scheme not only can reduce pilot contamination, but also can improve performance of bit-error-rate (BER) as wed as sum- rate contrast to existing algorithms. In addition, it shows that the proposed M2M massive MIMO system works steadily when the number of users increases in large scale.
基金Supported by the National Post-doctoral Research Funding(No.20090451239)
摘要A multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) broadcast channel is considered where both transmitter and receivers are equipped with multiple antennas. The Channel State Information (CSI) is quantized and provided through limited feedback links. In the first part of this work, the Maximum Expected SINR Combining (MESC) strategy for feedback decrease is investigated. Then a combination of MESC with subcarrier assigning is presented to further reduce the feedback load. The basic idea is the subcarriers are partitioned into resource blocks. For each block, only one quantized channel vector is feedback. The simulation results show MESC can obtain the performance gain over the relevant combiner strategies in MIMO-OFDM system. Moreover the effectiveness on the reduction of feedback overhead by the use of partitioning blocks in the studied system is evaluated.
摘要A novel scheme‘user assisted cooperative relaying in beamspace massive multiple input multiple output(M-MIMO)non-orthogonal multiple access(NOMA)system’has been proposed to improve coverage area,spectrum and energy efficiency for millimeter wave(mmWave)communications.A downlink system for M users,where base station(BS)is equipped with beamforming lens antenna structure having NRF radio frequency(RF)chains,has been considered.A dynamic cluster of users is formed within a beam and the intermediate users(in that cluster)between beam source and destination(user)act as relaying stations.By the use of successive interference cancellation(SIC)technique of NOMA within a cluster,the relaying stations relay the symbols with improved power to the destination.For maximizing achievable sum rate,transmit precoding and dynamic power allocation for both intra and inter beam power optimization are implemented.Simulations for performance evaluation are carried out to validate that the proposed system outperforms the conventional beamspace M-MIMO NOMA system for mmWave communications in terms of spectrum and energy efficiency.