Artificial Noise Based Security Algorithm for Multi-User MIMO System

The existing physical layer security algorithm, which is based on artificial noise, could affect legitimate receivers negatively when the number of users is no less than sending antennas in multi-user MIMO system. In order to improve security of multi-user MIMO system under this scenario, we propose a new multi-user MIMO system physical layer security algorithm based on joint channel state matrix. Firstly, multiple users are processed together, thus a multi-user joint channel state matrix is established. After achieving Singular Value Decomposition (SVD) of the joint channel state matrix, the minimum singular value is obtained, which can be utilized for precoding to eliminate the interference of artificial noise to legitimate receivers. Further, we also present an approach to optimize the power allocation. Simulation results show that the proposed algorithm can increase secrecy capacity by 0.1 bit/s/HZ averagely.

Optimal Power Allocation with Limited Feedback of Channel State Information in Multi-User MIMO Systems

In this paper,an expression for the user’s achievable data rate in the multi-user multiple-input multiple-output(MU-MIMO)system with limited feedback(LF)of channel state information(CSI)is derived.The energy efficiency(EE)is optimized through power allocation under quality of service(QoS)constraints.Based on mathematical equivalence and Lagrange multiplier approach,an energy-efficient unequal power allocation(EEUPA)with LF of CSI scheme is proposed.The simulation results show that as the number of transmitting antennas increases,the EE also increases which is promising for the next generation wireless communication networks.Moreover,it can be seen that the QoS requirement has an effect on the EE of the system.Ultimately,the proposed EEUPA with LF of CSI algorithm performs better than the existing energy-efficient equal power allocation(EEEPA)with LF of CSI schemes.

Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.

Hybrid Block Diagonalization Precoding for Multi-User Weighted Sum-Rate Maximization

This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates with multiple users equipped with multi-antenna.We develop a hybrid precoding design to maximize the weighted sum-rate(WSR)of the users by optimizing the digital and the analog precoders alternately.For the digital part,we employ block-diagonalization to eliminate inter-user interference and apply water-filling power allocation to maximize the WSR.For the analog part,the optimization of the PSN is formulated as an unconstrained problem,which can be efficiently solved by a gradient descent method.Numerical results show that the proposed block-diagonal hybrid precoding algorithm can outperform the existing works.

User Fairness Scheme with Proportional Fair Scheduling in Multi-user MIMO Limited Feedback System

In Multi-user MIMO (MU-MIMO) downlink system, suitable user selection schemes can improve spatial diversity gain. In most of previous studies, it is always assumed that the base station (BS) knows full channel state information (CSI) of each user, which does not consider the reality. However, there are only limited feedback bits in real system. Besides, user fairness is often ignored in most of current user selection schemes. To discuss the user fairness and limited feedback, in this paper, the user selection scheme with limited feedback bits is proposed. The BS utilizes codebook precoding transmitting strategy with LTE codebook. Furthermore, this paper analyzes the influence of the number of feedback bits and the number of users on user fairness and system sum capacity. Simulation results show that in order to achieve better user fairness, we can use fewer bits for feedback CSI when the number of user is small, and more feedback bits when the number of users is large.

Power allocation for MIMO-OFDM systems with multi-user decoupling and scheduling

A power allocation scheme for multi-user multiple-input multiple-output orthogonal frequency division multiplexing （MI- MO-OFDM） systems with channel state information （CSI） on transmitter and receiver is pressed. Multi-user lower allocation can be decoupled into single user lower allocation throughout null space mapping of multi-user channel and lower allocation can be performed throughout spatial-spectral water-filling for per user.To deal with more users in system and fading correlation,scheduling is oerformed to maintain the gain of power allocation.The proposed scheme can substantially improve system＇s spectral efficiency with low complexity.Simulation results validate the accuracy of theoretic analyses.

A pilot allocation method for multi-cell multi-user massive MIMO system

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.

Efficient user selection for multi-cell multi-user MIMO systems with limited backhaul

Multi-cell multi-user multiple-input multiple-output （MC-MU-MIMO） is a promising technique to eliminate inter-user interference and inter-cell cochannel interference in wireless telecommunication systems. As the large number of users in the system and the limited number of simultaneously supportable users with MC-MU-MIMO, it is necessary to select a subset of users to maximize the total throughput. However, the fully centralized user selection algorithms used in single cell system, which will incur high complexity and backhaul load in multi-cell cooperative processing （MCP） systems, are not suitable to MC-MU-MIMO systems. This article presents a two cascaded user selection method for MCP systems with multi-cell block diagonalization. In this paper, a local optimal subset of users, which can maximize the local sum capacity, is first chosen by the greedy method in every cooperative base station in parallel. Then, all the cooperative base stations report their local optimal users to the central unit （CU）. Finally, the global optimal users, which can maximize the global sum capacity of MCP systems, are selected from the aggregated local optimal users at the CU. The simulation results show that the proposed method performs closely to the optimal and centralized algorithm. Meanwhile, the complexity and backhaul load are reduced dramatically.

Adaptive Co-Channel Interference Suppression Technique for Multi-User MIMO MC DS/CDMA Systems

In this paper, an adaptive co-channel interference suppression technique for multi-user MIMO MC DS/CDMA system is envisaged. MC DS/CDMA offers many advantages like flexibility, robustness, low PAPR and spectral efficiency. In spite of these advantages, performance of MC DS/CDMA system is greatly impaired by interference. Common interferences, which degrade the performance of the system, are MAI and CCI. Mitigating these interferences can directly increase the capacity of the system. In this work, an adaptive co-channel interference suppression technique based on single-stage and two-stage MMSE IC is considered for multi-user MIMO MC DS/CDMA system. Simulation results show that, at low SNR two-stage MMSE IC outperforms single-stage, while at high SNR, single-stage provides better BER performance. Based on this, a selection criterion has been propounded for improved system performance as a whole in interference limited environment. Also, adaptive selection criterion resulted in better error performance.

Analyses of Virtual MIMO Multi-User System Performance with Linear Precoding Schemes Using Indoor Measurements at 5 GHz

In this paper, based on 5 GHz indoor multi-user measurements, linear precoding schemes such as zero-forcing (ZF), minimum mean square error (MMSE) and successive interference cancelation (SIC) are applied in the base station in order to investigate the performance of virtual multi-input multi-output (MIMO) over single-user MIMO system. However, to form a virtual MIMO multi-user system, the resources of two users are brought together. In order to achieve a low spatial correlation, two spaced antennas in the MS have been chosen and four spaced antennas elements in BS have been selected. Therefore, the resources of two users (U1 and U2) are brought together to form a 4 × 4 virtual MIMO multi-user system with the BS. The properties of the user_1 (U1) and user_2 (U2) will be analyzed and compared to those properties of virtual MIMO multi-user system formed by U1 and U2. In most cases, the maximum achievable rate is seen with virtual MIMO multi-user compared to single-user MIMO. So virtual MIMO multi-user is desirable for boosting system capacity than single-user MIMO. .

Improved Hybrid Beamforming for mmWave Multi-User Massive MIMO

Massive multiple input multiple output(MIMO)has become essential for the increase of capacity as the millimeter-wave(mmWave)communication is considered.Also,hybrid beamforming systems have been studied since full-digital beamforming is impractical due to high cost and power consumption of the radio frequency(RF)chains.This paper proposes a hybrid beamforming scheme to improve the spectral efciency for multi-user MIMO(MU-MIMO)systems.In a frequency selective fading environment,hybrid beamforming schemes suffer from performance degradation since the analog precoder performs the same precoding for all subcarriers.To mitigate performance degradation,this paper uses the average channel covariance matrix for all subcarriers and considers an iterative algorithm to design analog precoder using approximation techniques.The analog precoder is iteratively updated for each column until it converges.The proposed scheme can reduce errors in the approximating process of the overall spectral efciency.This scheme can be applied to fully-connected and partially-connected structures.The simulation results show that spectral efciency performance for the proposed scheme is better than the conventional schemes.The proposed scheme can achieve similar performance with full-digital beamforming by using a sufciently large number of RF chains.Also,this paper shows that the proposed scheme outperforms other schemes in the frequency selective fading environment.This performance improvement can be achieved in both structures.

Triple-Polarized Multi-User Mimo-Idma System under Correlated Fading Channel

A multiple-input multiple-output interleave division multiple access (MIMO-IDMA) system with Triple Polarized Division Multiplexing (TPDM) is presented in this paper. The present methodology replaces three independent linearly polarized antennas with a single triple polarized antenna at both the transmitter and receiver. The users in the communication link are accommodated and separated using a user-specific interleaver combined with low rate spreading sequence. To eliminate the effects of multi-stream interference (MSI), minimum mean square error (MMSE) algorithm based on successive interference cancellation (SIC) Multi-user detection (MUD) technique is employed at the receiver. Furthermore, log-maximum a posteriori probability (MAPP) decoding algorithm is implemented at the mobile stations (MSs) to overcome the effects of multi-user interference (MUI) effects. The paper also evaluates the effects of coded MIMO-IDMA in the downlink communication by adopting the Stanford University Interim (SUI) and Long-term Evolution (LTE)channel model specifications. In comparison with the traditional uncoded system, the present solution considering turbo coded triple-polarized MIMO-IDMA system with iterative decoding algorithm provides better bit error rate (BER) with reduced signal to noise ratio (SNR). The simulation results also show that though the SNR requirement is higher for the proposed technique compared to the conventional uni-polarized antenna based MIMO-IDMA system, it gives the advantages of achieving higher data rate with reduced cost and space requirements in the context of a downlink (DL).

Performance evaluation of channel inversion precoding for downlink multi-user MIMO system

In downlink multi-user multi-input multi-output （MU-MIMO） system, not every user （user equipment （UE）） can calculate accurately signal to interference and noise ratio （SINR） without prior knowledge of the other users＇ precoding vector. To solve this problem, this article proposes a channel inversion precoding scheme by using the lower bound of S1NR and zero-forcing （ZF） algorithm. However, the SINR mismatch between lower bound SINR and actual SINR causes the inaccurateness of adaptive modulation and coding （AMC）. As a result, it causes degradation in performance. Simulation results show that channel inversion precoding provides lower throughput than that of single user multi-input multi-output （SU-MIMO） at high signal-to-noise ratio （SNR） （〉14 dB）, due to the SINR mismatch, although the sum-rate of channel inversion precoding is higher than that of SU-MIMO at full SNR regime.

Closed BER expression of multi-user DS UWB systemsin indoor fading channel

The bit error rate （BER） performance of multi-user direct spreading bi-phase shift keying （DSBPSK） direct impulse ultra wideband （UWB） systems is analyzed and simulated based on a statistical indoor multi-path fading channel model. The BER of the system is theoretically derived and given in closed form, which is expressed in terms of channel parameters and system parameters such as pulse width parameter, pulse repeat period, user number and pulse waveform. With this BER expression, the effect of these parameters on the system performance can be evaluated in a uniform way. Simulation results well match the theory numerical results, and prove that the multi-access interference （MAI） of DS-BPSK UWB is a normal distribution.

Adaptive resource allocation in downlink multi-user MC-CDMA systems

The joint channel and power allocation in the downlink transmission of multi-user multi-carrier code division multiple access（MC-CDMA） systems are investigated and the throughput maximization problem is considered as a mixed integer optimization problem. For simplicity of analysis, the problem is divided into two less complex sub-problems： power allocation and channel allocation, which can be solved by a suboptimal adaptive power allocation （APA）algorithm and an optimal adaptive channel allocation （ACA） algorithm, respectively. By combining APA and ACA algorithms, an adaptive channel and power allocation scheme is proposed. The numerical results show that the proposed APA algorithm is more suitable for MC-CDMA systems than the conventional equal power allocation algorithm, and that the proposed channel and power allocation scheme can significantly improve the system throughout performance.

无蜂窝大规模MIMO系统接入点动态选择算法

在无蜂窝大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)系统中,所有接入点(Access Point,AP)为用户提供服务的方式会造成较大的功率消耗和增加前传链路压力。以“用户为中心”的AP选择方案为每个用户选择最佳的AP集合,使系统频谱效率和能量效率得以提升。为了给每个用户选择最佳的AP集合,提出了一种基于反向传播(Back Propagation,BP)神经网络的接入点动态选择算法。将AP与用户之间的大尺度衰落向量作为输入,AP与用户之间的连接关系作为BP神经网络输出的预测向量,同时,针对BP神经网络初始化权值,提出了一种改进的自适应遗传算法以提高算法的收敛速度和收敛性能。仿真结果表明,改进后的BP神经网络预测结果更接近于实际值,并且比全连接和启发式的AP选择方案具有更高的系统和速率。

基于位置分配的去蜂窝massive MIMO系统导频分配功率控制算法

针对去蜂窝(cell free,CF)大规模多输入多输出(multiple-input multiple-output,MIMO)系统中存在严重的导频污染问题,提出了一种基于位置分配的贪婪导频分配功率控制算法(greedy pilot assignment based on location with pilot power control,GPABL with PPC).首先,遵循相邻用户不分配相同导频序列的原则进行贪婪导频分配(greedy pilot assignment,GPA);然后,在导频分配的基础上叠加了导频功率控制,选择合理的导频功率控制系数减小信道估计的均方误差.仿真结果表明,将两种方式结合起来进行导频优化,系统的吞吐能力有所提升.

基于对抗自编码填补网络的MIMO雷达故障阵元缺失数据重构

多输入多输出(Multiple In Multiple Out,MIMO)雷达的阵元故障会导致其协方差矩阵出现整行整列数据缺失,从而降低其角度估计性能。为此,提出一种对抗自编码填补网络(Adversarial Autoencoder Imputation Network,AAEIN)来重构故障阵元的缺失数据。该网络由负责重构缺失数据的自动编码(Autoencoder,AE)网络和负责分辨数据来源的鉴别器组成。在二者的对抗训练中,AE网络的重构能力和鉴别器的分辨能力不断得到提升,直至两者收敛。为避免网络训练过程中参数量大和计算复杂度高的问题,文中结合MIMO雷达协方差矩阵的Hermitian特性,使用协方差矩阵上三角部分构建数据集用于网络训练。仿真结果表明,文中方法可以有效地重构故障阵元的缺失数据且具有较高的重构精度。

低复杂度的大规模MIMO分布式信道估计

针对大规模多输入多输出(multiple-input multiple-output,MIMO)系统传统信道矩阵获取方式导频开销大、计算复杂度高的问题,提出了一种低复杂度的二阶段分布式信道估计方案。该方案的初始阶段在基站侧采用传统压缩感知算法恢复信道矩阵,第2阶段在用户端利用信道的时间相关性,将大规模MIMO的角度域信道分解为密集部分和稀疏部分,并分别估计以实现连续信道追踪。稀疏部分信道通过所提的分布式自适应弱匹配追踪(distributed adaptive weak matching pursuit,DAWMP)算法,利用子信道的联合稀疏性进行多维重建。相比于线性最小均方误差(linear minimum mean square error,LMMSE)算法,所提方案的信道分解策略有效减少了在用户端进行信道估计的计算复杂度。仿真结果表明,所提算法与经典压缩感知信道估计算法相比,计算复杂度降低了约33%,算法性能提升了约0.5 dB。