降低多用户大规模MIMO-OFDM系统PAPR的加速近端梯度算法

针对多用户大规模多输入多输出（Multiple-Input Multiple-Output,MIMO）正交频分复用（Orthogonal Frequency Division Multiplexing,OFDM）系统存在较高峰值平均功率比（Peak-to-Average Power Ratio,PAPR）问题,在系统的下行链路中利用基站大量天线提供的冗余自由度,将OFDM调制、消除多用户之间干扰及降低PAPR联合成凸优化问题,并设计加速近端梯度算法（Accelerated Proximal Gradient Method,APGM）求解上述优化问题。仿真结果表明,所提方法显著降低了发射信号的峰均比,同时获得了较好的系统误符号率。与其他相关方法对比,APGM具有更低的计算复杂度和更快的收敛速度。     

多小区MIMO系统中基于泄漏的多用户下行链路预编码新算法

针对多小区MIMO系统的多用户下行链路预编码设计是未来移动通信系统研究的重要内容之一。本文在蜂窝多小区MIMO通信环境下,基于信漏噪声比(Signal-to-Leakage-Noise Ratio,SLNR)最大准则,提出了改进的多用户下行链路线性预编码算法。通过在优化目标中考虑接收端白化滤波器的影响,该预编码算法实现了对用户间干扰和小区间干扰(OCI)的同步抑制消除;在求解预编码矩阵优化问题时,本文基于QR分解提出了一种新的低复杂度求解算法,该算法能以较低的计算复杂度实现系统性能的有效提升。仿真实验结果表明,本文的改进SLNR线性预编码算法能有效抑制小区间干扰(OCI)的影响,使多小区MIMO系统获得更高的和速率(Sum Rate)容量。      

TDD大规模MIMO系统中两种新的下行预编码方案

针对时分双工大规模MIMO系统,该文提出两种新的下行链路预编码方案,即新最大比合并(NMRC)和新迫零(NZF)方案,通过理论分析得到两种新预编码方案下目标用户和非目标用户的下行链路信干噪比和频谱效率的表达式,并与传统的迫零(ZF)和最大比合并(MRC)预编码的下行链路信干噪比、频谱效率和误码率性能进行比较.仿真结果表明,所提出的NMRC和NZF预编码与传统的MRC和ZF预编码相比,在不增加运算复杂度的前提下可以获得更好的性能,而且新的预编码方案在提高目标用户性能的同时,对其他非目标用户的性能也有一定的改善.     

一种多用户MIMO/OFDM下行链路保障QoS的自适应传输机制

在用户QoS参数限制下,该文提出一种在多用户MIMO/OFDM下行链路使系统总速率最大的资源分配机制。基站应用空分多址接入,使得每个子载波可支持多个用户,应用线性预编码方法抵消用户间的干扰,提出保障QoS的自适应功率、比特分配方案。该文并提出两种可应用到实际系统的低复杂度的比特加载和比特去除算法,仿真结果表明,该两种方法性能可非常接近最优遍历算法。     

大规模MIMO多小区TDD系统中的预编码策略和导频调度

上行导频污染是大规模MIMO多小区多用户TDD系统的主要性能瓶颈。本文推导了下行链路中MF,ZF单小区预编码,基于MMSE的多小区预编码以及基于最大化SLNR准则的预编码策略在有导频污染的大规模MIMO下的系统可达和速率渐近性能,发现当基站天线数趋向无穷时,各个策略的等效信干比均收敛到仅与大尺度衰落因子相关的一个比值,由此可以得到一个系统可达和速率的渐近结果。基于此渐近结果,以最大化系统可达和速率为目标,获得了一个导频调度方案,即使得小区间相互干扰较小的用户采用相同的导频而相互干扰较大的用户采用正交的导频,从而在存在导频污染的情况下,可以提升系统的整体性能。理论分析和数值仿真结果都验证了以上结论。      

TDD大规模MIMO系统中两种新的下行预编码方案

针对时分双工大规模MIMO系统,该文提出两种新的下行链路预编码方案,即新最大比合并(NMRC)和新迫零(NZF)方案,通过理论分析得到两种新预编码方案下目标用户和非目标用户的下行链路信干噪比和频谱效率的表达式,并与传统的迫零(ZF)和最大比合并(MRC)预编码的下行链路信干噪比、频谱效率和误码率性能进行比较。仿真结果表明,所提出的NMRC和NZF预编码与传统的MRC和ZF预编码相比,在不增加运算复杂度的前提下可以获得更好的性能,而且新的预编码方案在提高目标用户性能的同时,对其他非目标用户的性能也有一定的改善。     

一种低复杂度多用户MIMO预编码方法

针对多用户多输入多输出(MIMO,Multiple Input Multiple Output)系统下行链路,提出了一种基于特定矩阵结构的低复杂度线性预编码方法。该方法利用规则块对角化(RBD,Regularized Block Diagonalization)方法的预编码矩阵具有的内在结构设计预编码矩阵,通过最小化总的干扰与噪声功率之和得到预编码矩阵的最终形式。等效性证明和复杂度分析表明,该方法能够获得与规则块对角化方法相同的"和速率"性能,同时大幅度降低了运算复杂度。仿真实验结果验证了这一结论。     

基于最大化信干噪比的多用户MIMO下行预编码

研究多用户MIMO系统下行链路的容量，以及如何达到该容量是最近几年研究的热点．基于各用户之间干扰为零的BD（Block Diagona Jjzation）算法，由于各用户信道空间的交叠，会造成多用户MIMO系统容量较大的损失，同时BD算法要求接入点的发射天线数不能小于空间复用用户的接收天线数之和．本文提出了基于最大化信干噪比准则下的线性预编码，和减少容量损失的次优线性预编码两种方案，避免了上述两个缺点，推导出基于最大化邬恹准则的线性预编码就是各用户采用单数据流传输的方案，同时通过容量分析和误码率仿真证明，这两种算法都优于传统的BD算法。     

基于公平性的多用户OFDM系统自适应功率分配松弛算法

提出了两种多用户OFDM系统下行链路的自适应功率分配算法.通过进一步放松不同用户之间数据速率比例性要求,提出的新算法提高了功率使用效率.实验仿真表明:在降低计算复杂度的同时,大大提高了系统容量,并且也近似满足了不同用户之间数据速率比例性要求.     

一种低复杂度基于公平性的MIMO-OFDMA资源分配方案

该文针对MIMO-OFDMA下行链路系统,考虑在总功率和BER 以及用户数据速率成比例的约束下,以获取整个系统吞吐量极大化为准则,提出一种基于成比例公平性约束的资源分配方案。新的方案基于MIMO信道状态信息,利用特征子信道来确定子载波和功率分配,充分利用了空间域,频域以及多用户分集提高系统的频谱效率。在子载波分配时,松弛成比例约束条件,使用户数据速率近似地成比例于每个用户分配的子载波数,推导出一种线性的不需要迭代的低复杂度的功率分配方案。仿真和分析表明,整个方案在保证系统吞吐量的前提下,取得了用户间良好的速率公平性,同时又具有较低的计算复杂度。     

Average power allocation based sum-rate optimization in massive MIMO systems

This paper exploits variations in the average channel gains in multi-cell multi-user massive multiple input multiple output (MIMO) systems. An average transmit power-control-based sum-rate optimization scheme is presented for the uplink of the system. The matched filtering (MF) and the zero forcing (ZF) processors are considered with perfect and imperfect channel state information at receiver (CSIR) under frequency flat Rayleigh fading channel. An average power-control-based system model is constructed for analyzing the sum-rate and formulating an optimization problem. A discrete level combinatorial optimization is performed for MF and ZF sum-rate under perfect and imperfect CSIR. The numerical results show a significant improvement in the sum-rate and power consumption. A low complexity algorithm for numerical optimization of the sum-rate is proposed. The performance of algorithm is quantified with different scenarios including different number of users, macro cells, and micro cells with low and high inter-cell interference powers. The evaluation results show that the improvement in sum-rate and energy efficiency increases with inter-cell interference power and the number of MTs.     

Some results on the sum-rate capacity of MIMO fading broadcast channels

We study the ergodic sum-rate capacity of the fading MIMO broadcast channel which is used to model the downlink of a cellular system with N/sub t/ transmit antennas at the,base and K mobile users each having N/sub r/ receive antennas. Assuming perfect channel state information (CSI) for all users is available at the transmitter and the receivers, we evaluate the sum-rate capacity numerically using the duality between uplink and downlink. Assuming Nt K, we also derive both upper and lower bounds on the sum-rate capacity to study its increase rate due to multi-user diversity. Finally, we compare three transmission schemes which use the single-user-MIMO scheme (SU-MIMO), ranked known interference (RKI) and zero-forcing beamforming (ZFB), respectively, to transmit to a selected set of users in order to approach the sum-rate capacity. We show that both ZFB and RKI outperform SU-MIMO in a cellular downlink scenario. when many mobile users are present.     

An efficient combinational approach for PAPR reduction in MIMO–OFDM system

The multiple input multiple output (MIMO) with orthogonal frequency division multiplexing (OFDM) has emerged as a promising solution to enhance the channel capacity and diversity of wireless communication system without any increase in bandwidth. In this paper, a parallel combinational scheme is proposed to reduce peak-to-average power ratio (PAPR) in MIMO–OFDM system under Rayleigh fading environment. The proposed method intelligently incorporates both active gradient project and partial transmit sequence schemes. The results show that the proposed method not only reduces the PAPR and computational complexity of the system but also maintains the bit error rate compared to other schemes.     

降低多用户MIMO下行检测复杂性的联合发送技术

该文研究降低多用户MIMO下行链路检测复杂性的联合发送技术。首先给出了多用户MIMO下行链路模型,在此基础上导出了数据检测算法,每个移动台只需一个线性滤波器来完成数据检测,大大地降低了接收机的计算量,然后就TD-SCDMA系统应用环境进行了仿真和分析,结果说明了多用户MIMO联合发送方案的优越性和良好的应用前景。     

On the sum-rate scaling law of downlink MU-MIMO decomposition transmission with fixed quality imperfect CSIT

In recent years, downlink multi-user multiple-input multiple-output (MU-MIMO) transmission techniques have attracted much attention because of their potential to significantly increase system capacity compared to single-user (SU) transmission. Unfortunately, accurate channel state information at the transmitter (CSIT) is crucial for these techniques to efficiently separate multiple users in the space domain so as to realize their capacity gain. In practice however accurate CSIT is difficult to obtain. In this letter we investigate the impact of imperfect CSIT on the system performance in terms of sum-rate scaling law for systems employing MU-MIMO decomposition scheme for downlink transmission. In particular, we derive the sum-rate scaling factors for various system configurations and find that imperfect CSIT has different effects on different categories of system configurations. Simulation results demonstrate the accuracy of our analysis.     

Novel transmit antenna selection strategy for massive MIMO downlink channel

In this paper, we deal with the problem of acquiring the channel state information (CSI) at the transmitter in large-scale multiple input multiple output (MIMO) systems, so-called massive MIMO systems. Clearly, obtaining CSI plays a central role to provide high system performance. Even though, in frequency-division duplexed systems, acquiring this information requires a prohibitive amount of feedback, since it increases with the number of transmit antenna. In this work, we design an efficient transmit antenna selection strategy aware of the amount of required CSI for a point-to-multipoint transmission in massive MIMO systems. The proposed strategy provides high sum-rate with limited CSI feedback and limited computational complexity. Innovatively, the antenna selection in our strategy is performed in a decentralized fashion successively at the receiving users. Two schemes are proposed in this work to perform the antenna selection at each user. Next, taking into consideration that the large-scale MIMO transmitter suffers from imperfect knowledge of CSI, we design a new performance criterion. Computer simulations validate that, when the CSI is perfectly known, the proposed strategy is able to achieve high performance in terms of system sum-rate while a significant reduction in both CSI feedback overhead and computational complexity is observed. Moreover, assuming imperfect CSI, the new proposed criterion achieves higher performance when the estimation accuracy is low and at high SNR regime.     

多小区MU-MIMO系统中基于泄露干扰迫零的分布式块对角化预编码设计

该文对多小区MU-MIMO中的预编码设计进行了研究。通过将单小区块对角化预编码进行扩展,将泄漏到邻小区的干扰纳入考虑范围,采用泄露干扰迫零的块对角化预编码,利用发送端提供的额外自由度直接将泄露干扰进行子空间迫零,消除泄露干扰,并且小区内用户之间也进行子空间迫零,消除用户间干扰;从而降低小区间干扰对多用户MIMO系统的不利影响。并且对本文所提算法复杂度进行了定量分析,表明该方案具有较低的计算复杂度。最后通过仿真全面分析了不同参数条件下的系统性能,结果显示该方法能够提高系统的传输速率。      

基于深度学习的多用户Massive MIMO预编码方法

在下行链路传输场景中,发射机处的功率分配和波束赋形设计至关重要。考虑一个多用户Massive MIMO系统中总功率约束下最大化加权和速率问题,经典的WMMSE算法可以获取次优解,但计算复杂度过高。为了降低计算复杂度,提出了一种基于深度学习的快速波束赋形设计方法,该方法可以离线训练深度神经网络,利用训练后的神经网络求解最优波束赋形解,只需要简单的线性和非线性操作即可完成。实验结果显示,该方法可以逼近WMMSE算法精度的90%以上,同时计算复杂度和时延也大大降低。