Multiuser MIMO Systems with Random Transmit Beamforming

This paper considers the wireless downlink transmissions in a single cell environment, for which the base station (BS) is assumed to schedule its transmission to each mobile station (MS) on a time-slot basis. Only one MS is selected for transmission during each time-slot and the selected MS possibly changes from one time-slot to another. This transmission scheme is thus referred to as dynamic time-division multiple-access (D-TDMA). Random transmit beamforming with the feedback of effective signal-to-noise ratio (ESNR) was proposed by Viswanath and Tse [IEEE Transactions on Information Theory, Vol. 48, No. 6, pp. 1277–1294, 2002] for D-TDMA-based systems in which multiple transmit antennas are equipped at the BS but only single receive antenna is equipped at each MS, or the so-called “MISO” systems. It was also shown in [Viswanath and Tse, 2002] that when the number of MSs in the system becomes large, the system throughput achieved by random transmit beamforming converges to that by coherent transmit beamforming which, however, requires the complete channel state information (CSI) of each MS at the BS. This paper extends upon the work in [Viswanath and Tse, 2002] to a more general scenario for which multiple transmit antennas and multiple receive antennas are equipped at the BS and each MS, respectively, or the so-called “MIMO” systems. We also consider several linear and nonlinear receiver structures and propose novel power allocation schemes to further improve the achievable system throughput. The throughput performance of the proposed receivers and power allocations schemes is compared through computer simulations and their fast convergence to the system throughput by coherent transmit beamforming is demonstrated.

带内全双工多用户MIMO系统中的用户选择

考虑一种多用户MIMO的传输设计,配置发射天线阵列和接收天线阵列的蜂窝基站可以工作在带内全双工传输模式。在该全双工通信方案中,基站的下行发射信号对基站的上行接收产生显著的干扰,即自干扰。这里,下行预编码处理和上行发射协方差矩阵处理将被依次进行,以简化全双工的设计。其次,为了进一步改善上、下行信道的和速率性能,我们提出一种尝试性的下行用户选择方案,其基本思想是:当某一个下行用户的信道矩阵的范数较小时,关闭该下行用户的数据流。计算机仿真结果表明,在基站下行总发射功率受限时,在低的和中等的下行信噪比区域,用户选择有助于提高下行和速率;在高的上行信噪比区域,简化的用户选择使得上行和速率明显提高。      

中继辅助的MIMO系统联合最优的 功率分配研究

本文对中继辅助的多输入多输出(MIMO)系统中信源与中继的联合最优功率分配问题进行了研究.首先,基于系统容量最大化准则提出相应代价函数,并证明了该代价函数仅仅对于部分参数是凸的,而对于全局参数是非凸的.然后,通过推导系统容量的下界,给出了一个新的代价函数,从而将非凸问题转化为一个联合凸优化问题.最后,利用凸优化方法获得了联合功率分配问题的全局最优解.计算机仿真表明,与现有方案相比,所提方案获得了更好的吞吐量性能.     

一种改进的多用户下行MIM0系统用户选择算法

为了克服多用户下行MIMO系统采用迫零波束成形算法时基站天线的数目要大于等于所有同时工作的用户接收天线的数目之和的缺点,丈中提出了一种改进的多用户下行MIMO系统用户选择算法。该算法具有较低的算法复杂度,性能优于常规的基于贪婪算法的用户选择方法。     

Joint User Scheduling and Antenna Selection in Distributed Massive MIMO Systems with Limited Backhaul Capacity

Massive MIMO systems offer a high spatial resolution that can drastically increase the spectral and/or energy efficiency by employing a large number of antennas at the base station（BS）.In a distributed massive MIMO system,the capacity of fiber backhaul that links base station and remote radio heads is usually limited,which becomes a bottleneck for realizing the potential performance gain of both downlink and uplink.To solve this problem,we propose a joint antenna selection and user scheduling which is able to achieve a large portion of the potential gain provided by the massive MIMO array with only limited backhaul capacity.Three sub-optimal iterative algorithms with the objective of sumrate maximization are proposed for the joint optimization of antenna selection and user scheduling,either based on greedy fashion or Frobenius-norm criteria.Convergence and complexity analysis are presented for the algorithms.The provided Monte Carlo simulations show that,one of our algorithms achieves a good tradeoff between complexity and performance and thus is especially fit for massive MIMO systems.     

User Selection Algorithms for MU‐MIMO Systems with Coordinated Beamforming

In this paper, we propose two novel user selection algorithms for multiuser multiple‐input and multiple‐output downlink wireless systems, in which both a base station (BS) and mobile stations (MSs) are equipped with multiple antennas. Linear transmit beamforming at the BS and receive combining at the MSs are used to avoid interference between users and find a better sum‐rate capacity performance. An optimal technique for selecting users would entail an exhaustive search, which in practice becomes computationally complex for a realistic number of users. Suboptimal algorithms with low complexity are proposed for a coordinated beamforming scheme. Simulation results show that the performance of the proposed algorithms is better than that provided by previous algorithms and is very close to an optimal approach with reduced complexity.     

认知MIMO系统中波束成形和功率的联合控制博弈算法

针对认知MIMO系统中波束成形和功率的联合优化问题,建立了非合作可分离对策联合博弈模型,提出了新的代价函数,根据KT条件证明了该模型中的各个子博弈均存在最优纳什均衡,从而得到联合博弈存在最优纳什均衡的结论,并提出了新的交替迭代算法。仿真结果表明,该算法有较快的收敛速度;同时,在动态环境下,算法也能达到最优纳什均衡,具有较好的稳定性。     

基于天线选择和功率分配的联合迭代优化算法

当使用所有天线进行无线数据传输时，大规模多输入多输出（Multiple-Input multiple-Output,MIMO）系统中的基站需要使用与天线数相同的射频链路，导致系统的实现复杂度增加，降低了系统的能效。针对能效降低的问题，提出了一种天线选择和功率分配的联合迭代优化算法。该算法在给定初始发送功率的条件下，随机生成一个天线集合作为内循环的初始值，内循环每次从余下的天线集合中选择一根具有最大能效的天线进行替换，得出最优天线集合，求出相应的最优发送功率，并以此作为下次外循环发送功率的初始值。仿真结果表明，所提算法在降低计算复杂度的前提下，几乎可以达到近似于最优穷举搜索算法的能效性能。     

Joint Transmit Beamforming and Power Control for CDMA System

1　Introduction　Power control and beamforming are two main methods toreduce interference in CDMA cellular communication sys tem. In power control, the transmitters powers are constant ly adjusted when the instantaneous SIR is not equal to targetSIR, so that the quality of weak links is improved. Base sta tion equipped with antenna arrays may adjust their beam pat terns so that they have maximum gain towards the directionsof target mobiles and minimum gain towards the other direc tio…     

Beamforming and power allocation in the downlink of MIMO cognitive radio systems based on multiobjective optimization

In this paper, power allocation and beamforming are considered in a multiple input multiple output (MIMO) downlink cognitive radio (CR) communication system, which a base station (BS) serves one primary user (PU) and one secondary user (SU). In order to design the CR system, a constrained multiobjective optimization problem is presented. Two objectives are the signal to noise plus interference ratios (SINRs) of PU and SU. Since PU has a spectrum license for data communication, a constraint in the optimization problem is that the SINR of PU must be greater than a predefined threshold based on the PU demand requirement. Another constraint is a limitation on power in BS. By considering the mentioned model, three iterative algorithms are proposed. At each iteration of all algorithms, the receiver beamforming vectors are derived based on the maximization of PU and SU SINRs, by assuming that the allocated powers and BS beamforming vectors are known. Also, power is assigned to users such that the constraint of power limitation is satisfied. The difference between the algorithms is in the obtaining of transmitter beamforming parameters. We evaluate the performance of the proposed algorithms in terms of bit error rate (BER) in simulations. Also, the computational complexity of the proposed algorithms is obtained.     

Joint Relaying Selection and Power Allocation Algorithms for Cooperative Cellular System

1IntroductionWireless communications have rapidly evolved in therecent decades[1]. An architecture based on introducingcooperative relayingtechnologiesintothe cellular infras-tructure[2 ~5],seems a solution which addresses futuretoughened requirements with respect to particular datarate and range by alleviating some of the shortcomingsof today s cellular concept .Repeateris asi mple coopera-tive relaying scheme with low complexity[6 ~7], whichcan be the Non-Regenerative Relaying Station (NR…     

MIMO系统一种新的功率分配算法及容量分析

在不额外增加发射功率和带宽消耗的情况下,注水功率分配算法能够获得最大的多输入多输出(MIMO)系统容量.基于拉格朗日乘数法,推导给出了MIMO系统注水功率分配算法的显式解.利用信道冲激响应矩阵的奇异值分解(SVD)算法,推导给出了注水功率分配算法MIMO系统的容量分析公式.利用数字波束形成(DBF)技术,提出了一种新的功率分配算法,推导给出了该算法MIMO系统的容量分析公式.仿真结果表明,提出的功率分配算法的系统容量虽然略低于注水功率分配算法的系统容量,但它的计算复杂度较低.     

多用户MIMO下行链路中线性预编码器和译码器的联合优化

文章研究多用户MIMO下行链路中线性预编码器和译码器的联合优化问题。采用的优化准则是在总发射功率约束下最小化系统的和均方误差（Sum MSE,SMSE）,提出了一种启发式的迭代算法。通过在接收端引入相同的自动增益控制因子,该算法对预编码器和译码器进行交替优化,直到SMSE达到最小值。分析和仿真结果表明：该算法具有较低的复杂度和良好的收敛特性,符号差错率也优于现有算法。     

V-MIMO中的协作用户功率分配算法

针对虚拟MIMO(V-MIMO)中源用户与协作用户间的功率分配问题,给出了一种基于源用户功率分配因子的区间搜索算法。该算法通过快速寻找不需要参与协作的用户,将迭代注水功率分配过程中的方程组求解过程转化为源用户功率因子的区间搜索,大大降低了算法的复杂度。瑞利信道下的仿真结果表明,该算法与平均功率分配算法相比,协作容量性能提高显著,与最优功率分配算法相比,性能相当,从整体上提高了系统的性能。     

Energy Harvesting in Cognitive Networks with Cooperative Beamforming: Power Allocation and Stability Analysis

Energy harvesting (EH) is a promising technology to improve both energy efficiency and spectral efficiency in cognitive radio (CR) networks. However, due to the randomness of the harvested energy and the interference constraint at the primary users (PUs), the limited transmission power of secondary users (SUs) may reduce the service rate of SUs. To solve this problem, this paper investigates a cooperative transmission method where a zero-forcing beamforming method is used in the EH based secondary network. Considering the transmission power constraint and energy causality, we derive the closed-form solution of the optimal transmission power for the secondary source and relays, which achieves the maximal stable throughput of the secondary network. Numerical results show the impact of different system parameters to the maximal stable throughput. In addition, compared with the traditional decode-and-forward (DF) scheme, the cooperative beamforming method achieves higher stable throughput under an high quality source-to-relay channel.     

Joint Optimization of Source Power Allocation and Relay Beamforming in Multiuser Cooperative Wireless Networks

Relay beamforming techniques have been shown to significantly enhance the sum capacity of a multiuser cooperative wireless network through the optimization of the relay weights, where concurrent communications of multiple source-destination pairs are achieved via spatial multiplexing. Further optimization of the transmit power allocation over the source nodes is expected to improve the network throughput as well. In this paper, we maximize the sum capacity of a multiuser cooperative wireless network through the joint optimization of power allocation among source nodes and relay beamforming weights across the relay nodes. We consider a two-hop cooperative wireless network, consisting of single-antenna nodes, in which multiple concurrent links are relayed by a number of cooperative nodes. When a large number of relay nodes are available, the channels of different source-destination pairs can be orthogonalized, yielding enhanced sum network capacity. Such cooperative advantage is particularly significant in high signal-to-noise ratio (SNR) regime, in which the capacity follows a logarithm law with the SNR, whereas exploiting spatial multiplexing of multiple links yields capacity increment linear to the number of users. However, the capacity performance is compromised when the input SNR is low and/or when the number of relay nodes is limited. Joint optimization of source power allocation and relay beamforming is important when the input SNR and/or the number of relay nodes are moderate or the wireless channels experience different channel variances. In these cases, joint optimization of source power and distributed beamforming weights achieves significant capacity increment over both source selection and equal source power spatial multiplexing schemes. With consideration of the needs to deliver data from each source node, we further examine the optimization of global sum capacity in the presence of individual capacity requirements by maximizing sum capacity of the network subject to a minimum capacity constraint over each individual user.     

基于天线选择的MIMO系统能效功率分配优化

对MIMO系统在毫米波衰落信道下的能效功率分配进行研究,以期实现绿色传输。考虑发送端采用天线选择技术,接收端采用最大比合并技术,给出系统能量效率公式,并构建系统基于能效最大化的目标优化函数。利用拉格朗日乘子法,获得迭代功率分配方案。利用排序法及朗伯函数给出简单的闭式功率分配方案。利用Matlab软件验证所提功率分配方案的有效性。仿真结果表明,文章提出的功率分配方案较穷举搜索法EE性能得到了明显提升,是一种复杂度低的优化算法,能快速收敛到EE最大值。     

单用户对双向中继系统中基于梯度下降的最大化和速率功率分配方案

针对单用户对双向中继系统中的功率分配问题,提出了一种基于梯度下降法的功率分配方案。该方案在总功率约束的条件下,以最大化和速率为目标函数,通过对中继波束成形矩阵和功率分配矩阵的反复迭代,求解出局部最优的功率分配和中继波束成形矩阵。仿真结果表明:提出方案的误码性能相比于等功率分配有明显提高,在误码率为10-2时,可获得2.5d B~3 d B的信噪比增益;同时,在中高信噪比下,相比于等功率分配,该方案可获得0.3(bit/s)/Hz~0.5(bit/s)/Hz的和速率增益。     

大规模MIMO系统中联合用户分组和联盟博弈的动态导频分配方案

大量研究表明,大规模MIMO系统中的小区边缘用户比中心用户更易遭受导频污染的影响。因此,该文提出一种联合用户分组和联盟博弈(JUG-AG)的动态导频分配方案来减轻系统导频污染。根据用户信号强度将所有用户分为A,B两组,把接收基站信号强度弱的小区边缘用户记为A组,剩余用户则为B组。A组用户使用相互正交的导频,B组用户则借助联盟博弈来重复使用剩余的正交导频。在B组用户的联盟博弈中,用户被分成若干个互不相交的用户子联盟,属于不同子联盟的用户分配不同的相互正交导频序列,而属于同一子联盟中的用户使用相同的导频序列。与已有的导频分配方案相比,该文提出的JUG-AG方案更灵活,可以用于所有用户随机分布的场景。而且,该算法通过循环搜索可以获得整体最优解。仿真结果表明JUG-AG方案能够有效降低上行链路中用户信号检测的平均均方根误差(RMSE),而且可以提高用户的平均服务速率。

     

MIMO-OFDM系统中的比特和功率联合分配算法

针对MIMO-OFDM系统,该文首先提出一种实用的最优比特和功率联合分配算法;其次为简化实现,设计了一种简化的等功率自适应调制选择算法。仿真表明,提出的联合分配算法不但可以获得最优的性能,而且具有较低的复杂度。简化的次优等功率分配算法极大地降低了算法复杂度,而性能只略低于最优等功率分配算法。