Interference alignment scheme for massive MIMO system

The performance of massive multiple-input multiple-output （MIMO） system is limited by pilot contamination. To reduce the pilot contamination, uplink and downlink precoding algorithms are put forward based on interference alignment criterion. In the uplink receiving processing, the target function aligns the pilot contamination and the interference signals to the same null space and acquires the maximal space degree of the desired signals. The uplink receiving precoding matrix is solved on maximal signal to interference plus noise ratio （SINR） criterion considering the impact of the pilot contamination on channel estimations. The uplink receiving precoding matrix is used as the downlink transmitting precoding matrix. Exploiting the channel reciprocity, it is proved that, if the uplink receiving precoding matrix achieves maximal S1NR, the identical precoding matrix can be used in the downlink transmission and acquires maximal signal to leakage plus noise ratio （SLNR）. Simulations show that the spectrum efficiency of the proposed algorithm can reach about 1.5 times higher than that of popular matched filtering （MF） precoding algorithm, and about 1.1 times higher than multi-cell minimum mean square error （MMSE） precoding algorithm. The performance of the proposed algorithm can be improved approximately linearly with the increasing of the number of antennas.     

Pilot decontamination in massive MIMO system combining time-shifted and cell sectorization pilot assignment

Pilot contamination is appeared in massive MIMO (multiple input multiple output) system when using the same pilot sequences at different cells to get the channel state information.It becomes a bottleneck problem of massive MIMO when the number of antenna goes infinite.In order to dealt with pilot contamination,a new TS-CSPA joint scheme was proposed.This scheme can mitigate pilot contamination by reduce the reuse of pilot sequence through the time domain and space domain.And the closed-form expression for the achieved rates and signal to interference plus noise ratio(SINR) to verify the advantages of the proposed scheme were given.Numerical results show that significant performance gains to mitigate pilot contamination problem compared to other methods.     

Compressive sensing power control for interference management in D2D underlaid massive MIMO systems

This paper introduces a sparsity controlled multiple random access scheme for efficient user scheduling in Device-to-Device (D2D) underlaid massive MIMO systems. In order to both avoid collision and enhance the Energy Efficiency (EE) of two-tier Heterogeneous Cellular Networks (HCNs), a unified Compressed Sensing (CS) based interference management strategy is proposed which guarantees concurrent cellular and D2D multi-user transmissions without collision. Specifically, supposing the natural sparsity in practical fifth generation (5G) scenarios and employing the sparse signal processing techniques, an analytical random access based model is adopted where provides several user scheduling and channel gain constraints to permit user identification, channel estimation and data decoding simultaneously. Furthermore, by developing a tractable tradeoff between the total power consumption and overall throughput of D2D tier, the transmission power is optimized such that the EE of D2D tier is maximized. Numerical simulations demonstrate the effectiveness of suggested approach to improve the collision avoidance capability and EE of D2D underlaid massive MIMO systems, even for crowded scenarios where the sparsity constraint does not meet sufficiently.     

大规模MIMO系统中的动态导频分配方案

针对多小区大规模多输入多输出(MIMO)系统中存在的导频污染问题,通过分析MMSE信道估计产生的误差,提出了一种动态导频分配方案.该方案将目标小区与相邻小区相邻的边缘区域内的用户进行动态导频分配,剩余区域内的用户进行随机导频分配来提升系统下行链路的平均可达和速率.仿真结果表明,该方法不仅能显著地提升信道估计的性能,而且还能有效地提高整个系统下行链路的可达和速率.     

基于混合精度ADC量化的大规模MIMO系统能效联合优化算法

针对在接收端采用混合精度的数模转换器（analog-to-digitalconverter,ADC）的大规模MIMO系统上行链路,提出一种能效优化算法。在采用最大比合并（maximumratiocombining,MRC）检测算法的基础上,推导得到系统上行链路能效的近似闭式表达式。首先确定高精度ADC的占比率,再以低分辨率ADC的量化精度、用户的发射功率和基站端天线数为优化目标的3个变量进行交替迭代得出最优的能效值;并进一步通过调整高精度ADC的占比率分析其对能效和频效的影响。仿真结果表明,所提算法具有较高的能效值,并且可以通过调整占比率实现能效与频效更好地折中。     

大规模MIMO系统中基于用户分类的动态导频分配

针对大规模MIMO系统导频污染问题,提出一种基于用户分类的动态导频分配策略.根据目标小区用户信号强度的方差设置合理的用户信号强度临界值,将目标小区用户分为中心用户和边缘用户.中心用户采用最大载干比算法分配导频,以最大化中心用户总信道容量.边缘用户采用贪婪算法分配导频,以提高每个边缘用户的信干噪比.仿真结果表明,所提策略在提高边缘用户信干噪比的同时能够有效提高系统的信道容量.     

大规模MIMO系统中基于谱分离的导频去污染

为了克服大规模MIMO的技术瓶颈——上行链路导频污染,与现有盲导频去污染中系统参数同时设计的方法不同,提出了系统参数的分层设计方法,指出不同的系统参数对最终接收信号样本协方差矩阵谱精确分离的作用是不同的,即具有不同的优先级。然后,发现要实现谱分离,期望信号的功率并不一定要高于干扰功率,两者之间的差异才是决定因素。更进一步地,在导频序列长度小于基站接收天线数这种更实际的场景下,首次给出了一种数值算法同样能实现上述的精确谱分离。实验仿真证明,由于分层的参数设计保证了渐近谱的精确分离,所提方案比现有的盲导频去污染方案更适合实际应用。     

基于V-BLAST的特征波束形成技术在大规模MIMO中的运用

为了获得较高的频谱效率及较低的误码率,提出了大规模MIMO系统中基于V-BLAST的特征波束形成技术(the Eigen-Beamforming combined with V-BLAST,V-BLAST&E-BF),利用大规模天线形成多个特征波束,在这些特征波束上传输多个码流,既可以获得阵列增益又可以获得复用增益.仿真结果表明:提出的方案较MF预编码和传统特征波束形成技术具有较好的性能,并且在接收端无须进行传统V-BLAST的检测算法(如MMSE检测、ZF检测)亦可分离出信号.     

iPAS: A deep Monte Carlo Tree Search-based intelligent pilot-power allocation scheme for massive MIMO system

Massive Multiple-Input-Multiple-Output (MIMO) is a promising technology to meet the demand for the connection of massive devices and high data capacity for mobile networks in the next generation communication system. However, due to the massive connectivity of mobile devices, the pilot contamination problem will severely degrade the communication quality and spectrum efficiency of the massive MIMO system. We propose a deep Monte Carlo Tree Search (MCTS)-based intelligent Pilot-power Allocation Scheme (iPAS) to address this issue. The core of iPAS is a multi-task deep reinforcement learning algorithm that can automatically learn the radio environment and make decisions on the pilot sequence and power allocation to maximize the spectrum efficiency with self-play training. To accelerate the searching convergence, we introduce a Deep Neural Network (DNN) to predict the pilot sequence and power allocation actions. The DNN is trained in a self-supervised learning manner, where the training data is generated from the searching process of the MCTS algorithm. Numerical results show that our proposed iPAS achieves a better Cumulative Distribution Function (CDF) of the ergodic spectral efficiency compared with the previous suboptimal algorithms.     

Power and energy optimization with reduced complexity in different deployment scenarios of massive MIMO network

With the increase in the number of users, the role of massive MIMO has become more significant. But there is a significant increase in the power and energy consumption in the massive MIMO network for transmission, processing, and reception. Hence, the prior role is to reduce the power consumption and increase the energy efficiency of the network. In this paper, the work is done to reduce the power consumption, while maintaining the reduced complexity in the massive MIMO and small‐cell scenario, and to increase the energy efficiency, by optimizing the number of users and number of transmission antennas in the massive MIMO scenario. This paper has also found out the optimal values of the energy efficiency, number of transmission antennas, and number of users for a massive MIMO network in different deployment scenarios like indoor hotspot, ultradense, dense urban, urban, suburban, and rural areas in both single‐cell scenario and multicell scenario at the base station and user equipment side according to the ITU‐R M.2135 standard.     

大规模MIMO系统的预编码算法综述

相比于传统多输入多输出（MIMO）系统,大规模MIMO的天线数量大幅增加,使得系统的容量提升、误比特率下降,但也造成预编码矩阵维度升高,算法复杂度、系统成本及实现难度增大。将大规模MIMO系统主要采用的预编码技术分为线性和非线性两个部分,对两者进行了归纳和对比,并着重介绍了几种经过简化的线性预编码算法和几种比较典型的非线性预编码算法,指出因为非线性算法的复杂度很高,故未来大规模MIMO系统的预编码应当以线性算法为主。     

面向5G的大规模MIMO技术综述

未来第5代移动通信系统(5G)中无线数据业务量的爆发性增长推动着研究人员发展新的颠覆性技术.作为5G的关键候选技术之一,大规模多入多出(MIMO)在基站使用远超激活终端数的天线,能增加一个数量级的频谱效率并大幅降低发射功率.首先介绍了大规模MIMO的系统模型和理论性能,其次分析和归纳了在信道测量与建模、信道信息获取、传输方法的研究成果,然后简述了实验和测试进展,最后讨论了未来研究方向.     

莱斯衰落信道下大规模MIMO系统中的信道估计方法

日趋重要的高速移动工具,如高速铁路、无人驾驶飞机等,大多都处在开阔地带.由于视距传播的存在,瑞利衰落模型已经不能很好地描述该环境下的信道情况,而莱斯衰落信道模型由视距分量和多径分量组成,更能准确地表述上述信道变化.基于此模型,在大规模天线系统下,在已存在的基于叠加训练序列信道估计方法的基础上,提出了改进的信道估计方法和对应的解码方法.改进后的信道估计方法分为直射分量已知和未知两种情况,分别推导了相应的信道估计公式和解码方法.数值仿真结果验证了本文所提方案性能的优越性.     

大规模MIMO OFDMA下行系统能效资源分配算法

针对大规模多输入多输出（MIMO）正交频分多址(OFDMA)下行移动通信系统,提出了一种基于能效最优的资源分配算法。所提算法在采用迫零(ZF)预编码的情况下,以最大化系统能效的下界为准则,同时考虑每个用户的最低速率要求,通过调整带宽分配、功率分配和基站天线数分配来优化能效函数。首先根据优化条件提出了一种迭代算法确定每个用户的带宽分配,然后利用分数规划的性质并采用凸优化方法,通过联合调整基站端的发射天线数和用户的发射功率来优化能效函数。仿真结果表明,所提算法在较少迭代次数的同时能够取得较好的系统能效性能和吞吐量性能。     

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.     

Effects and optimization of pilot sequence length on rate in multiuser massive MIMO FDD system

The effect of pilot sequence length on the asymptotic performance of the ergodic rate was investigated for the multiuser massive multiple-input multiple-output (MIMO) frequency division duplexing (FDD) downlink system.Firstly,the analytical expression of the ergodic rate was derived by using the principle of deterministic equivalence,based on which,it was discovered from the analytical results in two-fold that the normalized pilot sequence length (defined as the pilot sequence length divided by the number of BS antennas) tends to zero yet the rate was guaranteed to grow large without limit as long as the BS antenna number continues to increase,the rate saturates to a certain level if the BS antenna number becomes large with fixed pilot sequence length.Moreover,the pilot sequence length was optimized based on the sum-rate maximization within a finite channel coherence time,and a closed-form solution was deduced under a special correlated channel by means of Lambert W function.Simulation results validate the correctness of the theoretical analysis results and verify the effectiveness of the proposed closed-form solution of the optimal pilot sequence length.     

大规模MIMO系统多用户PSK调制方案的优化

针对超可靠低时延通信短包传输特征,在大规模多输入多输出( Multiple-Input Multiple-Output,MIMO)上行链路系统中,利用较低导频开销来设计相移键控( Phase Shift Keying,PSK)调制方案,并对该方案进行优化兼顾无线链路传输的可靠性.首先,在接收端构建基于最小欧式距离的非相...     

非对称毫米波大规模MIMO系统信道特性研究

在大规模多输入多输出（multiple-input multiple-output,MIMO）系统中,合理的天线选择、用户调度以及用户功率分配方案,对提升系统能效、节省资源成本有着重要的作用. 针对大规模MIMO下行链路通信场景,基于能效最大化准则,提出了一种联合天线选择、用户调度以及功率分配的低复杂度优化算法. 首先,针对天线选择和用户调度问题,结合递增递减的选择思想,以最大化系统能效为目标,对天线和用户进行双向交替搜索;其次,对于搜索过程中的用户功率分配问题,采用分式规划理论和拉格朗日对偶算法得到最优能效功率的闭式解,三个参数进行迭代优化,从而得到系统最优能效. 仿真结果表明,本文所提算法不仅具有低复杂度而且具有较好性能,能够有效降低大规模MIMO系统的能耗.

     

毫米波massive MIMO系统中混合连接的混合预编码设计

为了提高混合连接的混合预编码的频谱效率,首先利用连续干扰消除(SIC)的原理得到理想条件下的最优混合预编码矩阵,然后利用梯度下降理论将最优混合预编码矩阵分解为数字预编码矩阵和模拟预编码矩阵,最后考虑模拟预编码矩阵的恒模约束条件,并以最大化频谱效率为目标利用交替最小化方法优化模拟和数字预编码矩阵。所提出的混合预编码设计算法基于混合连接结构,因而能量效率远优于部分连接的和全连接的混合预编码。同时,该算法不会增加混合连接的混合预编码的硬件复杂度且只少量增加计算量。仿真结果表明,该算法能提升混合连接的混合预编码的频谱效率,特别是当射频(RF)链路数大于数据流数时,频谱效率的提升更加显著。由于分块不需要满足正交性,该算法比现有混合连接的混合预编码更适合实际应用。