多信道节点分布式协作MAC协议的研究

当前协作通信是现实条件下实现分集增益的关键技术,单天线节点通过相互协作传输信息实现空间分集可有效提高系统的整体性能。在协作通信研究中,协作节点的选择非常重要,选中好的协作节点可以极大地提高数据传输速率与效率,但是针对完全分布式无线网络多信道数据传输情况下,考虑到系统整体性能最优的协作节点分配和选择问题,并没有得到很好的研究。由此本文提出了一种基于协作增量值（CIV）的协作MAC协议（命名为CIV-MAC）。在CIV-MAC中,备选协作节点通过侦听多路信道控制帧获得信道状态信息（CSI）,并计算自身CIV;根据节点的CIV,协议会实行协作节点分配和选择机制并选出最优的协作节点,同时通过采用最小功率控制算法来降低系统能量消耗。最后,以网络实际有效吞吐量和能量效率两个参数为网络性能指标,通过两个不同场景的仿真实验结果得到,相对于RBAR协议和CRBAR协议,CIV-MAC可以极大地提升系统性能。     

基于部分失真定理的信道最优矢量量化器设计

提出了一个使用进化算法，引入部分失真定理（渐进划分理论）的信道最优矢量量化器（COVQ）的设计算法，采用该算法，在给定信道状态模型和存在的信道噪声的情况下，可有效地提高矢量量化器的性能，实现了COVQ的设计，该算法利用进化策略调整各码矢所确定区域的子误差，从而进一步改善期望误差，与常用的码书设计算法相比较，该算法能较好地调整各区域的子误差，获得比传统算法更高的性能增益。     

基于I/R/D协议的光命名数据网络性能分析

光命名数据网络（ONDN）是近年来提出的一种架构于光传输网上的命名数据网络（NDN）架构方案,是NDN面向未来高速宽带互联网发展的重要举措.基于I/R/D协议的ONDN数据交互思想未从实验量化分析角度给出性能结果,针对此问题,给出了基于光电转换（O/E）的I/R/D协议包转发过程.以I/R/D协议为基础,充分考虑基于光波分复用（WDM）技术的光传输技术,对波长数量、偏置时间、Interest包请求速率及Data包大小等因素入手,综合分析了在可能发生信道竞争而冲突的情况下ONDN的性能,为ONDN的未来具体架构提供一定参考.     

基于压缩感知的联合协作频谱感知算法

基于压缩感知的联合协作频谱感知方法实现动态频谱感知,通过融合各次用户(SU)采集的感知数据,寻找超参数,并与判决门限值进行比较,以获得最终的频谱判决结果.基于压缩感知的联合协作频谱感知算法减少了单个SU对压缩感知数据的不确定性,归一化均方误差（MSE）性能较好,并且该算法能够有效利用SU压缩感知数据信息,与其他典型算法相比,能获得更高的正确检测概率和较小的虚警概率.     

一种提高有线电视宽带网数据业务性能的算法

现代有线电视网正逐步向光纤同轴电缆混合(hybrid fiber/coax,HFC）网发展，HFC网以其频带宽和用户覆盖面广等优势成为为家庭用户提供宽带接入的重要手段之一。非对称宽带数据业务（如高速Web浏览和FTP文件下载等）是目前有线电视宽带网提供的主要服务，其性能的优劣将决定用户对有线电视宽带网的满意度，从而影响有线电视宽带网的普及和发展。概述了HFC网上行信道的数据传输机制，分析了其对数据业务性能造成的影响，对数据业务及其所采用的TCP协议在HFC网络环境中的性能进行了研究，并从HFC网上行信道带宽分配算法入手，对提高有线电视宽带网数据业务性能的方法进行了研究，提出了基于下行数据速率跟踪／上行带宽邓分配的上行信道带宽分配算法优化方案。     

PCN中信道的指配及计算机模拟

在ＰＣＮ中，应用时分多址方式（ＴＤＭＡ）和动态信道指配（ＤＣＡ）可提高频谱利用率，增大系统容量，由于同道干扰对系统性能影响很大，信道（包括载波与时隙）必须仔细地加以分配，本文应用离散随机事件的方法模拟了多路同时进行的链路，讨论了３种不同的信道分配方法并分析了系统性能。     

无线Mesh网络中基于信道状态的动态信道分配算法研究

对多信道无线Mesh网络中的信道分配算法进行了分析,提出了一种基于信道状态的动态信道分配策略（channel-state-based dynamic channel assignment,CSDCA）。该算法利用控制信道交互的信息,通过Hello消息的交换、发送请求（request-to-send,RTS）和允许发送（clear-to-send,CTS）的信道协商、数据传输3个阶段实现信道的动态分配,并通过仿真分析验证了该算法对多信道无线Mesh网络（multichannel wireless mesh networks,MWMN）性能的提高。     

协作多小区MISO干扰消除自适应比特分配算法

针对两小区MISO有限反馈系统中的小区间干扰消除问题,分析了部分信道状态信息下最大化信漏噪比和迫零波束形成在不同比特分配算法下的系统性能.通过使用两个独立的随机矢量量化(RVQ)码本分别量化期望信道和干扰信道,计算单用户下由量化误差导致的速率损失,再把速率损失限定在一定的范围内,进而对比特在期望基站和干扰基站之间的分配提出了一种新的自适应分配算法.仿真的结果表明与等比特分配算法相比该算法能够获得更优的系统性能.     

DCA协议的饱和吞吐量分析与最优带宽分配

动态信道分配(dynamic channel assignment,DCA)协议是一种经典的基于公用控制信道的多接口多信道无线网介质访问控制(medium access control,MAC)协议。为更全面地评估DCA协议的饱和吞吐量性能,首先通过分析DCA协议在控制信道和数据信道上的传输特性,建立了DCA协议饱和吞吐量的理论模型;然后,基于ns2网络仿真平台进行仿真实验,验证了模型的准确性以及对饱和转移临界条件的预测能力;基于该理论模型,进一步设计了信道最优带宽分配策略。理论计算以及仿真实验均表明:该信道分配策略能够有效地提高信道利用效率,改善网络吞吐量性能。     

基于组群结构的HFC MAC协议信道接入机制的性能分析

利用周期查询式限是队系统的有关研究成果，对基于组群结构的ＨＦＣ（混合光纤同轴）网络ＭＡＣ（媒质访问控制）协议中申请信息接入信道的机制进行了性能分析，结果表明，在一定条件下，系统的平均排队队长和平均等待时间都具有较好的性能。     

Consensus-based decentralized clustering for cooperative spectrum sensing in cognitive radio networks

A large number of previous works have demonstrated that cooperative spectrum sensing (CSS) among multiple users can greatly improve detection performance. However, when the number of secondary users (SUs; i.e., spectrum sensors) is large, the sensing overheads (e.g., time and energy consumption) will likely be intolerable if all SUs participate in CSS. In this paper, we proposed a fully decentralized CSS scheme based on recent advances in consensus theory and unsupervised learning technology. Relying only on iteratively information exchanges among one-hop neighbors, the SUs with potentially best detection performance form a cluster in an ad hoc manner. These SUs take charge of CSS according to an average consensus protocol and other SUs outside the cluster simply overhear the sensing outcomes. For comparison, we also provide a decentralized implementation of the existing centralized optimal soft combination (OSC) scheme. Numerical results show that the proposed scheme has detection performance comparable to that of the OSC scheme and outperforms the equal gain combination scheme and location-awareness scheme. Meanwhile, compared with the OSC scheme, the proposed scheme significantly reduces the sensing overheads and does not require a priori knowledge of the local received signal-to-noise ratio at each SU.     

Delay performance analysis and access strategy design for a multichannel cognitive radio network

For a hierarchical cognitive radio network (CRN), the secondary users (SUs) may access the licensed spectrum opportunistically, whenever it is not occupied by the primary users (PUs). An important issue for this kind of CRN is the achievable quality-of-service (QoS) performance, such as traffic transmission delay, which is critical to the SUs?? traffic experience. In this paper, we focus on the delay performance analysis of the SU system and the design of the corresponding optimal access strategy for the case of SUs sharing multiple licensed channels. In our analysis, the transmission of PU and SU traffic is modeled as M/G/1 queues. By merging the PU and SU traffic, we propose the model of a priority virtual queue on the licensed channels. Based on this model, we obtain the expected system delay expression for SU traffic through M/G/1 preemptive repeat priority queuing analysis. For the case of multiple licensed channel access, the access strategy is further investigated with respect to the expected system delay for SU traffic. By minimizing the expected transmission delay, the optimal access strategy is modeled as a nonlinear programming problem, which can be resolved by means of the classic Genetic Algorithm (GA). Numerical results validate our analysis and design of an optimal access strategy. Meanwhile, by considering the time taken by the GA approach, we can also adopt the inverse proportional access strategy to obtain near-optimal results in practice.     

Traffic sensitive spectrum access scheme for cognitive radio networks

A traffic sensitive spectrum access scheme is proposed to satisfy the traffic load requirement of secondary users （SUs）. In the proposed design, SU only accesses available channels which can meet the traffic demand. To achieve this, the expected transmission time （E3W） of the SU is calcu- lated first based on the delivery ratio. Then, the channel idle time is estimated based on the activity of primary users （PUs）. Therefore, available channels with estimated idle time longer than ETr could be chosen. With high probability, the SU can finish transmission on these channels without disruption, thereby satisfying the traffic load demand of the SU. Finally, our method is extended to the multi-channel scenario where each SU can access multiple channels simultaneously. Performance analysis shows that our method satisfies the requirement of SUs while effectively improving the throughput.     

Cooperative Compressive Spectrum Sensing in Cognitive Underw ater Acoustic Communication Networks

Because of the specific of underwater acoustic channel,spectrum sensing entails many difficulties in cognitive underwater acoustic communication( CUAC) networks, such as severe frequency-dependent attenuation and low signal-to-noise ratios. To overcome these problems, two cooperative compressive spectrum sensing( CCSS) schemes are proposed for different scenarios( with and without channel state information). To strengthen collaboration among secondary users( SUs),cognitive central node( CCN) is provided to collect data from SUs. Thus,the proposed schemes can obtain spatial diversity gains and exploit joint sparse structure to improve the performance of spectrum sensing. Since the channel occupancy is sparse,we formulate the spectrum sensing problems into sparse vector recovery problems,and then present two CCSS algorithms based on path-wise coordinate optimization( PCO) and multi-task Bayesian compressive sensing( MT-BCS),respectively.Simulation results corroborate the effectiveness of the proposed methods in detecting the spectrum holes in underwater acoustic environment.     

Consensus-based decentralized clustering for cooperative spectrum sensing in cognitive radio networks

A large number of previous works have demonstrated that cooperative spectrum sensing(CSS) among multiple users can greatly improve detection performance.However,when the number of secondary users(SUs;i.e.,spectrum sensors) is large,the sensing overheads(e.g.,time and energy consumption) will likely be intolerable if all SUs participate in CSS.In this paper,we proposed a fully decentralized CSS scheme based on recent advances in consensus theory and unsupervised learning technology.Relying only on iteratively information exchanges among one-hop neighbors,the SUs with potentially best detection performance form a cluster in an ad hoc manner.These SUs take charge of CSS according to an average consensus protocol and other SUs outside the cluster simply overhear the sensing outcomes.For comparison,we also provide a decentralized implementation of the existing centralized optimal soft combination(OSC) scheme.Numerical results show that the proposed scheme has detection performance comparable to that of the OSC scheme and outperforms the equal gain combination scheme and location-awareness scheme.Meanwhile,compared with the OSC scheme,the proposed scheme significantly reduces the sensing overheads and does not require a priori knowledge of the local received signal-to-noise ratio at each SU.     

基于超模博弈的认知无线Ad hoc网络分布式功率控制技术

考虑一种交织(Interweave)模式下的单跳认知无线Ad hoc网络(CRAHN)应用场景,针对次用户(SU)组成的Ad hoc网络提出一种分布式功率控制技术,以最大化提高次网络容量.SU网络通过频谱感知来探测主用户(PU)所在授权频段的使用情况.一旦授权频段空闲,次网络中的SU将利用授权频谱进行并发通信,目标是通过优化各SU的发射功率,以达到次网络频谱效率最大化.首先根据应用场景给出了网络容量优化近似模型,为了解决该非凸问题,将网络容量优化模型建立为等效博弈模型,并在不同的SINR条件下证明了Nash均衡的存在性和唯一性,最终提出基于Gradient Play的分布式功率控制算法来实现资源最优分配.仿真结果表明,该算法可在保证收敛性的同时、支持一定的并发通信用户数、提高该网络系统的频谱效率.     

多信道认知网络的直观信道感知策略

为了提高频谱利用率,认知无线电技术可使非授权用户在不影响授权用户正常通信的情况下,利用瞬时的频谱空穴满足自身通信需求。如何通过感知频谱及时有效地发现频谱空穴是一个至关重要的问题,尤其是对于多信道认知无线电网络。针对多信道认知无线电网络,该文在连续时间Markov链的信道占用模型基础上,根据信道状态可能发生变化的概率,提出了一个动态的直观信道感知策略,并考虑了感知周期的影响。仿真结果表明:在感知周期合适的情况下,该策略能够有效地发现并利用频谱空穴,并且比周期感知和随机感知策略消耗更少的能量用于感知。     

认知无线传感器网络中基于网络特性的单天线媒体接入控制协议

提出了一种基于网络特性的单天线媒体接入控制(STNC-MAC)协议用于认知无线传感器网络.该协议能使作为次用户的无线传感器节点有效地对主用户使用信道进行机会接入.STNC-MAC充分考虑了主用户和次用户的网络特性,通过定义数据传输单元和最大信道占用时间,设计出适用于STNC-MAC的数据传输方案和可用信道列表管理机制,克服多信道隐藏终端问题和“盲”状态问题;同时,在不对主用户造成严重干扰的情况下,实现了不同主用户信道利用率的数据信道支持不同长度数据包传输的功能.NS2仿真结果表明,STNC-MAC在吞吐量和平均时延方面比STDCA MAC和原始的IEEE 802.11 MAC更好地提高了网络性能.     

基于机会调度的上行认知中继蜂窝网络中断性能研究

对基于机会调度的上行两跳认知放大中继蜂窝网络的中断性能进行研究,导出了该系统的中断概率封闭表达式和高信噪比下的中断概率近似表达式。该系统中有多个源节点,研究表明,通过选择最优的次用户进行信息传输,系统中断性能可得到改善。仿真验证了理论推导的正确性。     

基于OFDM的认知无线电系统联合资源分配

为充分利用现有无线电频谱资源, 研究了基于正交频分复用的认知无线电系统, 以填充和下垫联合方式进行分配资源的问题, 提出了新的子载波分配算法和最优功率分配算法。该算法在保证总功率和每个子载波所受干扰在一定阈值内的前提下, 采用最优功率分配算法最大化次用户传输速率。同时, 为降低算法的复杂度, 将置零子载波功率算法应用到资源分配中。最后, 基于Worst-case 方法, 对次用户和主用户间的信道不确定性进行鲁棒性分析。仿真结果表明, 在相同条件下, 该资源分配最优算法和次优算法都优于单独的填充式或下垫式资源分配算法。