一种用于MIMO系统的快速天线选择算法

在多径衰落环境中, MIMO系统的信道容量随天线数的增加呈线性增加,发射/接收天线选择方法能以很小的性能损失换取射频成本的大幅度降低,使MIMO系统不完全受射频成本的限制。为快速选择出使系统容量最优的发射/接收天线子集,该文提出一种快速天线选择算法的改进算法。该算法通过实时更新优化参数,大大降低计算复杂度。仿真结果表明,该算法在不影响系统容量的情况下大大减少了计算时间。     

一种快速的接收天线选择算法

天线选择是MIMO系统中一项重要的技术,它能从MIMO系统的多个发射天线和多个接收天线中选择出性能最好的一个或几个天线,从而以很小的性能损失换取成本的大幅降低,极大地提高了MIMO系统的性能价格比。最优算法具有较高的复杂度而限制了它的应用,文中从次优的递增递减算法入手,提出了一种具有更低复杂度的递增递减接收天线选择算法。仿真结果表明,该算法以很小的系统容量损失为代价换取了复杂度的降低。     

上行多用户MIMO系统中的用户与天线联合选择方案

在多用户MIMO系统中,基站所能同时进行通信的用户数受到基站和用户端天线数的限制,随着用户数的增加,系统的性能反而会降低,因此,用户选择技术就成为一种改善系统性能的有效技术.在本文中,针对上行多用户MIMO系统提出了一种低复杂度的用户选择算法.为获得更大的系统性能,在用户选择的基础上,进一步提出了一种用户与天线联合选择算法.这两种算法在极大地简化计算复杂度的条件下,提供了与最优算法几乎相同的性能.     

基于最大比合并的MIMO分集系统递增天线选择算法

MIMO分集系统天线选择技术可以在不增加系统射频链路的情况下,达到与全天线几乎相同的分集增益.针对发送端采用最大比发送,接收端采用最大比合并的MIMO分集系统,提出了一种递增天线选择方法,每次增加一根天线,并使得它与已选出的天线结合起来具有最大的信噪比增益.相对于对所有可用天线集进行遍历的最优算法,它减小了需要搜索的范围和每次搜索的计算量,降低了复杂度;相对于功控天线选择算法,它考虑了新增天线与已选出天线集之间的相关性,改善了性能.仿真结果表明,在误比特率、信道容量和信噪比增益方面,此算法和最优算法性能相近,且不随可用天线数和选出天线数的改变而改变.     

60GHz 室内信道下一种快速天线选择算法

传统的基于信道容量最大化准则的天线选择算法虽然使信道容量达到了最大化,但是计算复杂度很高。针对计算复杂度高的问题, 提出了一种基于Doolittle-QR 分解的低复杂度天线选择算法。该算法基于Doolittle-QR 分解,可以快速选择出使系统容量最大化的天线。与传统的天线选择算法相比,该算法的计算复杂度不仅有效地降低了, 而且容量性能相近。在60GHz 室内信道下,仿真实验结果表明, 该算法具有良好的容量性能,优于随机天线选择算法,接近最优天线选择算法。     

分布式MIMO系统一种基于容量最大化准则的快速天线选择算法研究

由于分布式MIMO系统中的穷举天线选择算法复杂度较高,难以实现的缺点,因此本文提出了一种低复杂度的基于容量最大化准则的快速天线选择算法（Fast Antenna Selection Algorithm based on Maximum Capacity Criteria,简称FASAMCC）。该算法以容量最大化为依据进行端口的动态选择,并采用快速天线选择算法来进行天线的选择。仿真表明FASAMCC不仅复杂度低,而且其性能接近穷举算法。     

一种改进的大规模MIMO发射天线选择算法

为了降低天线选择算法在大规模多输入多输出（Multiple-Input Multiple-Output,MIMO）系统下的误码率和复杂度,以用户端接收的总功率为优化目标,提出一种最大化所有用户接收总功率的天线选择算法。该算法将优化目标函数转化为凸函数,并利用凸优化方法求得其有效解。仿真结果表明,所提天线选择算法与传统的最大和容量算法相比,具有较好的系统误码率性能,且运算复杂度低,但系统容量有所降低。     

分布式MIMO系统发送天线选择与预编码联合设计

为了抑制多用户分布式多入多出(MIMO)系统中的同道干扰(CCI),使系统同时服务于更多用户,提出一种发送天线选择与预编码的联合设计方法。该方法立足于分布式MIMO系统基站端天线较多的特点,将下行发送天线选择与信漏噪比(SLNR)预编码相结合,通过为用户选择不同天线,从根本上减少CCI;在为每个用户选择天线时,先以信道子矩阵的迹为依据进行端口选择,再采用逐减的方法选择使SLNR损失值最小的天线,以保证每个用户对其他用户的干扰尽量小,从而达到进一步抑制CCI的目的。复杂度分析和仿真结果表明,该方法在具有较低复杂度同时,其容量性能仍可逼近最优算法;较之单纯的SLNR预编码,在相同的容量性能约束下,其能够有效增加系统同时服务的用户数。     

二进制猫群算法在大规模MIMO天线选择中的应用

在多输入多输出(MIMO)系统中,天线选择技术平衡了系统的性能和硬件开销,但大规模MI-MO系统收发端天线选择复杂度问题一直没有得到很好的解决.基于信道容量最大化的准则,采用两个二进制编码字符串分别表示发射端和接收端天线被选择的状态,提出将二进制猫群算法(BCSO)应用于多天线选择中,以MIMO系统信道容量公式作为猫群的适应度函数,将收发端天线选择问题转化为猫群的位置寻优过程.建立了基于BCSO的天线选择模型,给出了算法的实现步骤.仿真结果表明所提算法较之于基于矩阵简化的方法、粒子优化算法具有更好的收敛性和较低的计算复杂度,选择后的系统信道容量接近于最优算法,非常适用于联合收发端天线选择的大规模MIMO系统中.     

一种基于相异度的接收天线选择算法

对于多输入多输出系统天线选择算法而言,穷尽搜索算法能够达到最优的性能,但包含较多矩阵运算,计算复杂度较高。而传统基于相关度和相似度的天线选择算法虽具有较低计算量,但损失了较大的容量性能。针对这一问题,以容量性能为目标,提出了基于相异度的接收天线选择算法,分析了不同相异度下所提选择准则对系统性能的影响。与传统相关度和相似度天线选择算法相比,所提算法有效降低了计算复杂度,改善了系统的容量性能,仿真结果表明:所提算法具有较好的系统性能,适用于实时通信系统。     

Antenna selection and forwarding strategy in SWIPT relay channels

This letter proposes a low-complexity ‘harvest-and-forward’ relay strategy in simultaneous wireless information and power transfer (SWIPT) relay channels. In the first phase of relay transmission, the relay’s antennas are divided into two subsets. The signals received by the antennas in one subset are converted to energy, and the signals received by the antennas in the other subset are combined. In the second phase, the relay forwards the combined signal using all antennas with the harvested energy. A low complexity antenna selection (AS) algorithm is given to maximize the achievable rate over fading channels. The simulation results show that the achievable rate of this strategy is close to that of the two-stage strategy where a two-state procedure is proposed to determine the optimal ratio of received signal power split for energy harvesting, and the optimized antenna set engaged in information forwarding. The proposed strategy has better performance than the two-stage strategy when the relay is equipped with medium-scale antennas, and the performance gap between two strategies grows with the increase of the number of the relay’s antennas. The computational complexity of the proposed strategy is O(N2) (N is the number of relay antennas), which is obviously lower than that of the two-stage strategy (O(3N3)).     

大规模MIMO相关信道下的联合天线分组和天线选择

在大规模多输入多输出系统中,针对密集部署的大型天线阵列之间的强相关性会抑制天线选择增益效果的问题。在系统下行链路场景下建立空间相关信道模型,提出了基于天线分组的天线选择算法。根据瞬时信道相关矩阵将天线阵列划分为若干组,保证各组内天线之间相关性较强。在完成天线分组的基础上,基于信道矩阵列范数准则在各组发射天线与接收天线之间构成的子信道矩阵中选择天线,进而构造有效发射天线与接收天线之间的信道矩阵。仿真分析了所提天线选择算法对系统遍历和速率的影响,结果表明,在基站天线数为32、接收天线数为2、选择天线数为2、天线相关因子为0.9的假设下,当信噪比为10 dB时,与基于相邻天线分组的天线选择算法相比,所提算法使系统和速率约提高了27.5%,且所提算法若要与最优天线选择算法达到相同的和速率,仅需将其信噪比提升1～2 dB即可。     

多中继与多用户选择的中继系统安全性能分析

为了考察使用多中继选择与多用户选择的放大转发（AF）中继系统的物理层安全性能,推导了其在瑞利衰落信道上和联合发送天线选择/接收最大比合并天线分集下的非零安全容量概率和安全中断概率的精确表达式以及在高信噪比下的渐近安全中断概率解析表达式。AF中继系统的非零安全容量概率和安全中断概率的数值计算和仿真结果相吻合,验证了以上理论分析的正确性;分析结果表明,其安全分集增益为源节点发射天线数、最优中继节点接收天线数、中继节点数的三者乘积与最优中继节点发射天线数、最优用户接收天线数、用户数三者乘积之间的最小值,且与窃听信道无关。     

MF中继选择系统的物理层安全性能

针对合谋窃听场景下单天线多中继修改转发（MF）协作无线系统的安全性能较差问题,提出一种合谋窃听场景下联合源节点发送天线选择（TAS）和多中继选择的MF协作物理层安全系统,考虑最优的最大化主信道信噪比（SNR）和次优的最大化源节点-中继节点链路 SNR 两种中继选择方案,推导其安全中断概率（SOP）和遍历安全容量（ESC）的解析表达式。最优或次优中继选择的MF安全中继系统的SOP和ESC的数值计算结果与仿真结果相吻合,验证了上述理论分析的正确性;同时也表明源节点发射天线数和中继节点数越多、窃听节点数越少,最优或次优中继选择的MF安全中继系统的物理层安全性能越好。     

Fast antenna subset selection in MIMO systems

Multiple antenna wireless communication systems have recently attracted significant attention due to their higher capacity and better immunity to fading as compared to systems that employ a single-sensor transceiver. Increasing the number of transmit and receive antennas enables to improve system performance at the price of higher hardware costs and computational burden. For systems with a large number of antennas, there is a strong motivation to develop techniques with reduced hardware and computational costs. An efficient approach to achieve this goal is the optimal antenna subset selection. In this paper, we propose a fast antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Our algorithm achieves almost the same outage capacity as the optimal selection technique while having lower computational complexity than the existing nearly optimal antenna selection methods. The optimality of the proposed technique is established in several important specific cases. A QR decomposition-based interpretation of our algorithm is provided that sheds a new light on the optimal antenna selection problem.     

Transmit Antenna Selection in the Alamouti-Coded MIMO Relay Systems

In the Alamouti-coded multiple-input multiple-output relay systems, we consider selecting two transmit antennas from all available antennas, at the source and relay respectively, to maximize received signal-to-noise ratio (SNR) at the destination. Since the optimal antenna selection rule is intractable, we propose three suboptimal antenna selection rules (rule one, two and three). While these rules all select two best antennas at the relay to maximize the SNR of relay-destination link. They have different selection criteria at the source. Rule one maximizes the SNR of source-relay link but ignores source–destination link. Oppositely, rule two maximizes the SNR of source–destination link but ignores source-relay link. Rule three considers both links together. We derive the closed-form outage probability expressions of rule one and two, and find an upper bound for the outage probability of rule three. The analysis results show that rule one and two cannot achieve full diversity order, and rule three can. Simulation results verify the analysis results.     

Optimal antenna selection based on capacity maximization for MIMO systems in correlated channels

Recent work has shown that multiple-input multiple-output (MIMO) systems with multiple antennas at both the transmitter and receiver are able to achieve great capacity improvement. In such systems, it is desirable to select a subset of the available antennas so as to reduce the number of radio frequency (RF) chains. This paper addresses the problem of antenna selection in correlated channels. We consider a narrowband communication system with M transmit and N receive antennas. We present the criterion for selecting the optimal L/sub t/ out of M transmit and L/sub r/ out of N receive antennas in terms of capacity maximization, assuming that only the long-term channel statistics, instead of the instantaneous channel-state information, are known. Simulations will be used to validate our theoretical analysis and demonstrate that the number of required RF chains can be significantly decreased using our proposed selection strategy, while achieving even better performance than the conventional MIMO system without antenna selection.     

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.     

Transmit antenna selection for decision feedback detection in MIMO fading channels

In this paper, we investigate a transmit antenna selection (TAS) approach for the decision-feedback detector (DFD) over Rayleigh fading channels. In particular, for a multipleinput multiple-output (MIMO) channel with M transmit and N (N ⩾ M) receive antennas, we derive a lower bound on the outage probability for the TAS approach. The selected transmit antennas are those that maximize the post-processing signalto- noise ratio (SNR) at the receiver end. It is shown that the proposed TAS approach achieves a performance close to optimal selection based on exhaustive search, introduced in the literature, but at a lower complexity. Simulation results are presented to validate and demonstrate the performance gain of the proposed TAS approach.     

Routing and transmission scheduling for minimizing broadcast delay in multirate wireless mesh networks using directional antennas

Using directional antennas to reduce interference and improve throughput in multihop wireless networks has attracted much attention from the research community in recent years. In this paper, we consider the issue of minimum delay broadcast in multirate wireless mesh networks using directional antennas. We are given a set of mesh routers equipped with directional antennas, one of which is the gateway node and the source of the broadcast. Our objective is to minimize the total transmission delay for all the other nodes to receive a broadcast packet from the source, by determining the set of relay nodes and computing the number and orientations of beams formed by each relay node. We propose a heuristic solution with two steps. Firstly, we construct a broadcast routing tree by defining a new routing metric to select the relay nodes and compute the optimal antenna beams for each relay node. Then, we use a greedy method to make scheduling of concurrent transmissions without causing beam interference. Extensive simulations have demonstrated that our proposed method can reduce the broadcast delay significantly compared with the methods using omnidirectional antennas and single‐rate transmission. In addition, the results also show that our method performs better than the method with fixed antenna beams. Copyright © 2012 John Wiley & Sons, Ltd.