多用户MIMO系统的低复杂度天线选择算法

块对角化是一种用于多用户MIMO系统下行链路的预编码方案,它可以完全消除多用户间的干扰。论文就是针对采用块对角化预编码的多用户MIMO下行链路,基于信道F-范数提出一种新的次优天线选择算法。该算法计算复杂度较低。仿真结果显示,其系统容量接近采用最优算法的系统容量。     

率失真优化的无线多跳网络多路径选择算法

随着无线网络技术的发展,基于无线多跳网的视频通信在智能交通、灾难应急和军事指挥等多个领域得到越来越广泛的应用.但是,如何保证无线视频的传输质量,是亟待解决的一个关键问题.已有多路径视频传输研究忽略了信道变化和路径间干扰.针对该问题,提出一种基于率失真预测的多路径选择优化算法.该算法不仅分析了网络拥塞对传输质量的影响,而...     

基于朴素贝叶斯的室内VLC网络天线选择方法

在室内多天线多用户可见光通信(VLC)网络中,为了改善在发射天线和用户数量增多的情况下,最优天线选择算法存在时间复杂度过高问题,将朴素贝叶斯(NB)方法应用于室内多用户VLC网络下行链路发光二极管(LED)选择问题中.首先,将该LED选择任务建模为多分类问题,利用用户已知信道状态信息生成训练样本集,并通过VLC网络多用户通信和速率最大生成对应类标签;其次,利用生成的训练样本集,通过NB方法得到分类器模型;最后,将训练得到的分类器模型应用于新用户的LED选择.仿真分析表明,与最优多用户VLC网络LED选择算法相比,所提出的基于NB的LED选择方案可以有效地降低时间复杂度,在算法复杂度和用户传输和速率之间实现了较好的平衡.     

基于合作似然检测和球形译码的多用户多输入输出多跳中继系统

针对多输入输出(MIMO)系统在传输数据过程中的误码率(BER)和信道容量优化问题,提出一种基于合作似然检测和球形译码的多用户MIMO多跳中继系统。首先,该系统构建二阶协作的MIMO中继系统模型对信道数据的中继传输过程以及路径损耗、阴影衰落情况进行分析;接着,通过球形译码来推导出等效的最大似然规则进行对数正态阴影衰落检测;最后提出最大调和平均信道功率选择策略,基于相关性链路度量和最大信道功率阈值为用户选择误码率更小的接入链路,从而改善多用户MIMO系统的性能。实验仿真结果显示,与基于互信息最大化的多用户MIMO多跳中继系统以及基于解码转发和多入多出技术正交空时分组编码(STBC)的中继系统相比,该系统在数据传输过程中的平均比特误码率分别降低了27.4%和32.6%,平均信道容量分别提高了9.5%和12.7%,因此在减少误码率和提高信道容量上具有较好的效果。     

提升MIMO干扰信道容量的干扰对齐方案

为提高多用户MIMO干扰信道的容量,提出一种干扰对齐方案。在假设已有天线配置情况不变的条件下,将发送端的原有天线划分为数目相当的2个子组,分别设置不同的天线参数,以消除2个子组天线之间的相关性,从而形成2组独立的传输信道。在接收端将经由2组子信道传输后的接收信号进行合并,间接扩展信号空间维数。基于合并处理后的等效信道传输矩阵,分别利用优化预编码向量夹角和正交投影的方法求解预编码矩阵与联合矩阵,以减少已有干扰对齐方案通过迭代求解所需的运算量。仿真结果表明,在总天线配置情况不变时,该方案可以提高多用户MIMO信道的抗干扰能力。     

基于格基缩减的MU-MIMO下行传输策略

块对角化（Block diagonalization, BD）预编码算法通过两次奇异值分解实现多用户间干扰消除并将下行多用户多输入多输出（Multi-user multiple-input multiple-output, MU-MIMO）信道解耦成多个独立 的单用户MIMO（Single-user MIMO, SU-MIMO）信道,但其计算复杂度也随着用户数量和矩阵维数的增加而增加 。在MU-MIMO下行系统中,提出基于格基缩减的改进块对角化传输策略,将BD算法的第2次奇异值分解替换为基于格基缩减的线性检测,可得到比传统BD传输策略更好的误码率性能以及更低的计算复杂度。     

无线传感器网络中一种基于虚拟MIMO多播的多跳传输策略

虚拟MIMO技术能够有效减少信道衰落对无线链路的影响,节省无线传输时的能耗.结合MIMO多播和LEACH协议,提出新的虚拟MIMO多跳传输策略(VMMM),由于该策略避免了多跳数据转发时的簇内广播过程,从而提高整个网络的能量有效性.为优化该传输策略的性能,本文对VMMM策略的能耗进行建模分析,并在此基础上通过联合优化以确定满足最小能耗时的网络参数.仿真结果表明,与已有的虚拟MIMO多跳传输策略—vMISO协议相比,VMMM策略能够显著提高网络的能量有效性,有效延长网络生存时间达50%以上.     

IEEE 802.11n中速率、模式及信道的联合自适应算法

针对IEEE 802.11n无线网络中的速率、MIMO模式与信道宽度的联合自适应问题,提出了一种基于非静态Multi-Armed Bandit学习方法的联合自适应算法,并设计了一种新颖的报酬函数.为解决该算法收敛时间较慢的问题,基于分类回归树设计了MCS、MIMO模式以及信道宽度预测算法,其能够有效利用无线网卡驱动程序采集的相关统计数据预测不同MCS、MIMO模式以及信道宽度组合的报酬函数,大幅度缩小联合自适应算法的搜索空间.该算法具有易实现、近似最优及计算复杂度低的特点.真实实验结果表明:在无干扰和不同干扰环境下,联合自适应算法都能够有效地提高UDP吞吐量.     

一种改进的相关信道下MIMO天线选择算法

由于MIMO系统天线间距的限制等原因,实际MIMO无线信道往往是衰落相关的,而信道相关性严重影响了MIMO系统的性能。针对这个问题,提出一种改进的基于相关性天线选择算法,通过选择具有最小平均相关性和最大相关矩阵行列式的天线子集作为最优天线集合。在选择较少天线的情况,降低了计算复杂度,达到几乎与相关性选择算法相同的性能,且非常接近最优选择算法。仿真结果证明了改进算法的有效性和可靠性。     

一种优化算法物联网技术分布式协作路由研究

研究无线传感器网络分布式协作优化问题。针对无线传感器网络资源利用率和传输效率低下等问题,建立了一种基于遗传优化算法的无线信道质量预测的分布式优化协作路由技术。该技术充分利用遗传算法,采用启发式方法建立无线链路信道信噪比预测模型,然后根据信道质量选择最优者作为协作节点,以较小代价在动态无线网络拓扑中搜寻到最优路由。数学分析表明,遗传算法收敛速度快、可靠性高,可以准确地预测无线链路质量;同时该协作路由技术对无线传感器网络具有更好的适应性,并有效延长了网络生命周期。     

User density sensitive P2P streaming in wireless mesh networks

Link rate allocation is very important for supporting high video playback rate in Peer-to-Peer video streaming. Although many studies can be found on resource allocation in P2P streaming in wired networks, very few studies have studied the problem in wireless networks, especially in Wireless multi-hop Mesh Networks (WMNs), which is still challenging. To maximize the users’ satisfaction of P2P streaming in WMNs, this paper focuses on link rate allocation problem and proposes a fully distributed algorithm to efficiently utilize the upload and download bandwidth of wireless mesh nodes. We first build an efficient P2P streaming system based on the experimental results from real deployment of our wireless mesh testbed. Then we design an efficient distributed algorithm based on the solution to a linear optimization model, which optimizes towards a user-density-related objective to decide the best streaming rates among peers. Our scheme is resilient to network dynamics that is characteristic in wireless multi-hop peer-to-peer networks. The simulation experiments demonstrate the significant performance enhancement by using the proposed rate allocation algorithm in WMNs.     

Utility-based scheduling in wireless multi-hop networks over non-deterministic fading channels

In this paper, an innovative scheduling scheme is proposed for interference-limited wireless multi-hop networks with non-deterministic fading channels. The scheduling problem is considered as a network utility maximization (NUM) problem subject to link rate constraints. By jointly taking into account of the link scheduling and the statistical variations of signal and interference power, the convex sets for the NUM are derived. Two types of non-deterministic fading channels (i.e., Rayleigh fading channel and Ricean fading channel) are characterized into our NUM models as examples. To solve the convex optimization problem, the subgradient projection method based on dual decomposition is employed. Then, a heuristic algorithm is designed for the TDM mode wireless multi-hop networks by minimizing the discrepancy between the expected network cost and the optimal one in each timeslot. At last, the source–destination session rate and network utility are evaluated in a dedicated wireless multi-hop network scenario. The numerical results demonstrate that the session rates convergence and the network utility is improved by our proposed scheme.     

MIMO多跳无线网络

综述了多跳无线网络MIMO(multiple-input multiple-output)技术的研究进展,分析了MIMO技术的引入对多跳无线网络各层及整体设计的影响.以跨层协议设计为重点,详细介绍了当前典型的基于MIMO的多跳无线网络协议算法的核心机制,并比较分析了这些算法的特点和性能差异与存在的缺陷.最后,结合本领域内的研究现状,指出了基于MIMO的多跳无线网络走向实际工程应用环境所亟待解决的关键问题,指出了基于MIMO技术设计自适应调整、高性能多跳无线网络跨层模型及协议的重要性.     

Real-time video streaming over multipath in multi-hop wireless networks

Given the limited wireless link throughput, high loss rate, and varying end-to-end delay, supporting video applications in multi-hop wireless networks becomes a challenging task. Path diversity exploits multiple routes for each session simultaneously, which achieves higher aggregated bandwidth and potentially decreases delay and packet loss. Unfortunately, for TCP-based video streaming, naive load splitting often results in inaccurate estimation of round trip time (RTT) and packet reordering. As a result, it can suffer from significant instability or even throughput reduction, which is also validated by our analysis and simulation in multi-hop wireless networks. To make real-time TCP-based streaming viable over multi-hop wireless networks, we propose a novel cross-layer design with a smart traffic split scheme, namely, multiple path retransmission (MPR). MPR differentiates the original data packets and the retransmitted packets and works with a novel QoS-aware multi-path routing protocol, QAOMDV, to distribute them separately. MPR does not suffer from the RTT underestimation and extra packet reordering, which ensures stable throughput improvement over single-path routing. Through extensive simulations, we further demonstrate that, as compared with state-of-the-art multi-path protocols, our MPR with QAOMDV noticeably enhances the TCP streaming throughput and reduces bandwidth fluctuation, with no obvious impact to fairness.     

Optimal adaptive channel scheduling for scalable video broadcasting over MIMO wireless networks

Video broadcasting is an efficient way to deliver video content to multiple receivers. However, due to heterogeneous channel conditions in MIMO wireless networks, it is challenging for video broadcasting to map scalable video layers to proper MIMO transmit antennas to minimize the average overall video transmission distortion. In this paper, we investigate the channel scheduling problem for broadcasting scalable video content over MIMO wireless networks. An adaptive channel scheduling based unequal error protection (UEP) video broadcasting scheme is proposed. In the scheme, video layers are protected unequally by being mapped to appropriate antennas, and the average overall distortion of all receivers is minimized. We formulate this scheme into a non-linear combinatorial optimization problem. It is not practical to solve the problem by an exhaustive search method with heavy computational complexity. Instead, an efficient branch-and-bound based channel scheduling algorithm, named TBCS, is developed. TBCS finds the global optimal solution with much lower complexity. The complexity is further reduced by relaxing the termination condition of TBCS, which produces a (1 − ε)-optimal solution. Experimental results demonstrate both the effectiveness and efficiency of our proposed scheme and algorithm. As compared with some existing channel scheduling methods, TBCS improves the quality of video broadcasting across all receivers significantly.     

Intelligent multicast routing for multimedia over cognitive radio networks: a probabilistic approach

Cognitive radio (CR) technology has been demonstrated as one of the key technologies that can provide the needed spectrum bands for supporting the emerging spectrum-hungry multimedia applications and services in next-generation wireless networks. Multicast routing technique plays a significant role in most of wireless networks that require multimedia data dissemination to a group of destinations through single-hop or multi-hop communication. Performing multimedia multicasting over CR networks can significantly improve the quality of multimedia transmissions by effectively exploiting the available spectrum, reducing network traffic and minimizing communication cost. An important challenge in this domain is how to perform a multi-cast transmissions over multiple hops in a dynamically varying CR environment while maintaining high-quality received video streaming to all multi-case CR receivers without affecting the performance of legacy primary radio networks (PRNs). In this paper, we investigate the problem of multicast multimedia streaming in multi-hop CR networks (CRNs). Specifically, we propose an intelligent multicast routing protocol for multi-hop ad hoc CRNs that can effectively support multimedia streaming. The proposed protocol consists of path selection and channel assignment phases for the different multi-cast receivers. It is based on the shortest path tree (SPT) that implements the expected transmission count metric (ETX). The channel selection is based on the ETX, which is a function of the probability of success (POS) over the different channels that depends on the channel-quality and availability. Simulation results verify the significant improvement achieved by the proposed protocol compared to other existing multicast routing protocols under different network conditions.

     

Joint rate and cooperative MIMO scheme optimization for uniform energy distribution in Wireless Sensor Networks

An energy efficient adaptive rate cooperative MIMO selection scheme is proposed for uniform load distribution in the cluster based wireless sensor networks. The intrinsic data flow direction in multi-hop cluster based sensor networks causes uneven load distribution in the network. The transit clusters and the clusters near the base station carry more network traffic than the other clusters. Cooperative MIMO can artistically reduce the per bit energy consumption, Space–Time Block Codes are designed to achieve maximum diversity for a given number of transmit and receive antennas with very simple decoding algorithm. In radio fading channel, STBC require less transmission energy than SISO technique for the same Bit Error Rate and can be employed practically in Wireless Sensor Networks by using the cooperative MIMO scheme. Considering Alamouti and Tarokh Space–Time Block Codes, the number of antennas at both the transmission and the reception sides are selected with respect to the cluster load. The crude energy consumption per cluster then refined through adaptive rate transmission. It has been shown that the load based joint adaptive selection of rate and cooperative nodes in clusters renders uniform energy consumption in the network.