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
Terahertz(THz) communication is being considered as a potential solution to mitigate the demand for high bandwidth. The characteristic of THz band is relatively different from present wireless channel and imposes tech...Terahertz(THz) communication is being considered as a potential solution to mitigate the demand for high bandwidth. The characteristic of THz band is relatively different from present wireless channel and imposes technical challenges in the design and development of communication systems. Due to the high path loss in THz band,wireless THz communication can be used for relatively short distances. Even,for a distance of few meters( > 5 m),the absorption coefficient is very high and hence the performance of the system is poor. The use of multiple antennas for wireless communication systems has gained overwhelming interest during the last two decades.Multiple Input Multiple Output( MIMO) Spatial diversity technique has been exploited in this paper to improve the performance in terahertz band. The results show that the Bit Error Rate( BER) is considerably improved for short distance( < 5 m) with MIMO. However,as the distance increases,the improvement in the error performance is not significant even with increase in the order of diversity. This is because,as distance increases,in some frequency bands the signal gets absorbed by water vapor and results in poor transmission. Adaptive modulation scheme is implemented to avoid these error prone frequencies. Adaptive modulation with receiver diversity is proposed in this work and has improved the BER performance of the channel for distance greater than 5 m.展开更多
This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. ...This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.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
针对多输入多输出正交时频空间(multiple-input multiple-output orthogonal time frequency space,MIMO-OTFS)系统由最大时延、多普勒扩展、天线数量增加带来信道估计计算开销大、准确率下降的问题,提出了一种基于感知辅助和原子选择...针对多输入多输出正交时频空间(multiple-input multiple-output orthogonal time frequency space,MIMO-OTFS)系统由最大时延、多普勒扩展、天线数量增加带来信道估计计算开销大、准确率下降的问题,提出了一种基于感知辅助和原子选择门限的广义正交匹配追踪(sensing aided generalized orthogonal matching pursuit algorithm based on atomic threshold,SA-TGOMP)信道估计算法。该算法首先将雷达探测的用户和周围环境信息转化为OTFS信道的初始索引集,然后引入以固定值选取相关性原子进行迭代的策略和原子选择门限进行支撑集更新。实验结果表明,本文算法能够有效提高信道估计精度的同时减少导频开销。展开更多
针对基于定向传输的飞行器自组织网络(flying ad-hoc network,FANET)中拓扑变化频繁、链路质量波动以及初始建网困难等问题,提出了一种基于多输入多输出(multiple-input multipleoutput,MIMO)正交时频空(orthogonal time frequency spac...针对基于定向传输的飞行器自组织网络(flying ad-hoc network,FANET)中拓扑变化频繁、链路质量波动以及初始建网困难等问题,提出了一种基于多输入多输出(multiple-input multipleoutput,MIMO)正交时频空(orthogonal time frequency space,OTFS)通感一体化波形的感知辅助快速邻居发现方法,借助感知机制实时获取邻节点信息以加速建网效率,并采用新型的通感一体波形OTFS以对抗快变信道中的多普勒效应,提升链路质量。针对FANET场景研究物理层基于MIMOOTFS通感一体化波形的多目标检测技术;将物理层感知方案映射到上层网络中,设计感知辅助的高效邻居发现算法;最后提出一种多点通感协同机制,通过邻节点间交互感知信息和邻居发现表以间接感知及发现潜在目标,提升FANET初始建网的效率。仿真结果表明,所提方案相比传统通信组网协议可以极大降低FANET的初始建网耗时,增加目标感知精度,提升组网的整体性能。展开更多
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
基金supported by the National Natural Science Foundation of China(61901341).
文摘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.
文摘Terahertz(THz) communication is being considered as a potential solution to mitigate the demand for high bandwidth. The characteristic of THz band is relatively different from present wireless channel and imposes technical challenges in the design and development of communication systems. Due to the high path loss in THz band,wireless THz communication can be used for relatively short distances. Even,for a distance of few meters( > 5 m),the absorption coefficient is very high and hence the performance of the system is poor. The use of multiple antennas for wireless communication systems has gained overwhelming interest during the last two decades.Multiple Input Multiple Output( MIMO) Spatial diversity technique has been exploited in this paper to improve the performance in terahertz band. The results show that the Bit Error Rate( BER) is considerably improved for short distance( < 5 m) with MIMO. However,as the distance increases,the improvement in the error performance is not significant even with increase in the order of diversity. This is because,as distance increases,in some frequency bands the signal gets absorbed by water vapor and results in poor transmission. Adaptive modulation scheme is implemented to avoid these error prone frequencies. Adaptive modulation with receiver diversity is proposed in this work and has improved the BER performance of the channel for distance greater than 5 m.
基金supported by the National Natural Science Foundation of China (60972152 61001153)the Aeronautics Science Foundation of China (2009ZC53031)
文摘This paper analyzes the effect of waveform parame- ters on the joint target location and velocity estimation by a non- coherent multiple input multiple output （MIMO） radar transmitting multiple subcarriers signals. How the number of subcarriers in- fluences the estimation accuracy is illustrated by considering the joint Cramer-Rao bound and the mean square error of the maxi- mum likelihood estimate. The non-coherent MIMO radar ambiguity function with multiple subcarriers is developed and investigated by changing the number of subcarriers, the pulse width and the frequency spacing between adjacent subcarriers. The numerical results show that more subcarriers mean more accurate estimates, higher localization resolution, and larger pulse width results in a worse performance of target location estimation, while the fre- quency spacing affects target location estimation little.
文摘针对大规模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。
文摘针对多输入多输出正交时频空间(multiple-input multiple-output orthogonal time frequency space,MIMO-OTFS)系统由最大时延、多普勒扩展、天线数量增加带来信道估计计算开销大、准确率下降的问题,提出了一种基于感知辅助和原子选择门限的广义正交匹配追踪(sensing aided generalized orthogonal matching pursuit algorithm based on atomic threshold,SA-TGOMP)信道估计算法。该算法首先将雷达探测的用户和周围环境信息转化为OTFS信道的初始索引集,然后引入以固定值选取相关性原子进行迭代的策略和原子选择门限进行支撑集更新。实验结果表明,本文算法能够有效提高信道估计精度的同时减少导频开销。
文摘针对基于定向传输的飞行器自组织网络(flying ad-hoc network,FANET)中拓扑变化频繁、链路质量波动以及初始建网困难等问题,提出了一种基于多输入多输出(multiple-input multipleoutput,MIMO)正交时频空(orthogonal time frequency space,OTFS)通感一体化波形的感知辅助快速邻居发现方法,借助感知机制实时获取邻节点信息以加速建网效率,并采用新型的通感一体波形OTFS以对抗快变信道中的多普勒效应,提升链路质量。针对FANET场景研究物理层基于MIMOOTFS通感一体化波形的多目标检测技术;将物理层感知方案映射到上层网络中,设计感知辅助的高效邻居发现算法;最后提出一种多点通感协同机制,通过邻节点间交互感知信息和邻居发现表以间接感知及发现潜在目标,提升FANET初始建网的效率。仿真结果表明,所提方案相比传统通信组网协议可以极大降低FANET的初始建网耗时,增加目标感知精度,提升组网的整体性能。
文摘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.
