基于OFDM认知无线电网络的最优路径算法

针对基于正交频分复用的分布式认知无线电网络,在考虑频谱移动特性的同时,为保证认知用户数据传输的可靠性,提出一种最优路径的基于OFDM认知无线电网络路由算法.该算法首先通过建立认知无线电网络的模型计算信道的期望传输时间和信道干扰,结合类似于按需路由的基本流程得到所有可能的路径.最后,根据最小累积期望传输时间和路径平均吞吐量的指标来选择最优路径.仿真的结果表明,OROCR算法可以明显地减少平均端到端时延,大大地提高平均端到端吞吐量.     

认知无线电网络中最稳定频谱分配算法

认知无线电网络中,主用户和认知用户的行为均会给认知节点间的频谱分配带来重大影响。在考虑认知用户间相互干扰时,提出了认知用户可用信道的潜在竞争节点数这一概念。在此基础上,将主用户对认知用户的影响考虑进去,定义了信道稳定度并将其作为衡量频谱质量的一个新的度量衡,以及给出了最稳定信道分配算法。性能评估的结果表明,最稳定信道分配算法可以有效的降低端到端平均时延以及显著的提高端到端吞吐量。     

认知无线网络中基于主用户行为的联合路由和信道分配算法

针对认知无线网络中主用户行为将导致频谱瞬时变化而影响路由稳定性的问题,提出了一种基于主用户行为的路由和信道联合分配算法。该算法通过采用呼叫模型对主用户行为建模,并根据动态源路由协议的路由寻找机制,在目的节点等待多个路由请求分组后选择受主用户行为影响最小的路由,然后沿着所选定路径的反方向传送路由回复分组并完成信道分配。理论分析证明了算法中的链路平均持续时间期望与主用户活动概率成反比且具有与网络节点数成正比的计算复杂度。仿真结果表明,该算法具有比Gymkhana路由方案更高的分组投递率和更低的平均分组时延。     

认知无线电网络的分布式路由协议的研究

分布式路由算法广泛应用于认知无线电网络(CRNs)。为此,分析多跳CRNs的路由问题,利用无中心的Markov决策过程(DEC-POMDP)建立问题模型,并确保次级用户对主级用户的干扰少于预定阈值,进而控制端到端时延。最后引用多智能体学习算法解决此问题模型,进而形成基于多智能体学习的路由(MALR)。实验结果表明,提出的路由能够控制时延,并降低了干扰率。     

认知无线Ad Hoc网络中的路由尺度和算法设计

在认知无线Ad Hoc网络中,路由问题面临巨大挑战。由于各认知节点可用频谱的时变性、多样性和差异性,传统的路由尺度不再适用于认知无线Ad Hoc网络。本文在自组织认知网络环境下,应用主用户信道的使用模型,同时考虑次用户之间的干扰情况,提出了两类路由尺度和算法,仿真结果表明,这两类路由尺度都能很好地反映端到端性能。     

基于HWMP的先应树状路由算法研究

无线网状网是一种新兴的宽带无线网络接入技术,支持不同应用场景的无线接入。IEEE802.11s标准定义了一种默认的路由选择算法,称为混合无线网状网协议(HWMP)。HWMP将把树状路由为基础的先应路由模式和按需路由模式相结合。对先应路由模式进行改进,以减小网络开销,增强网络性能。从仿真结果可以看出,改进后的算法在数据包到达率、平均端到端时延和吞吐量指标上达到了更佳的性能。     

认知无线电网络中基于强化学习的智能信道选择算法

认知无线电系统不仅要具有自适应性,更应具备一定的智能性。该文将强化学习理论引入到认知无线电系统中,用于解决次用户在频谱感知过程中的信道选择问题,提出了一种基于强化学习的信道选择算法。该算法在未知主用户占用规律和动态特性的前提下,仅通过不断与环境进行交互学习,便能够引导次用户选择“较好”信道优先进行感知,使次用户吞吐量得到提高。仿真结果表明,相对于现有信道选择算法,所提算法可有效提高次用户的吞吐量,并且在主用户使用规律发生变化时,能够自动实现二次收敛,可作为认知无线电系统迈向智能化的一种尝试。      

水声通信网中一种低时延低开销路由算法

水声通信网在军事、环境、能源、自然灾害预防和处理等方面均具有巨大的应用潜力。针对当前水声通信网背景噪声大及传播速度慢,从而导致控制开销大和平均时延大的问题,提出了旨在改善水声网整体性能的NHMLDR算法。该算法采用了时延代价度量的RREQ和去除HELLO消息的新机制。仿真结果表明,与HCR算法相比,NHMLDR算法使系统的归一化控制开销最大降低约40.88%;分组平均端到端时延减小约8.93%~51.88%;数据分组丢失率降低约0.01%~0.3%;网络吞吐量提升了约10.1%~23.7%。因此,NHMLDR算法明显改善了系统的整体性能。     

一种超低时延FEC实时视频编码算法

为满足5G实时视频传输的可靠性和低时延需求,提出一种面向低时延实时视频前向纠错（Forward Error Correction,FEC）传输控制算法。该算法根据实时视频帧到达情况和当前网络状况,建模FEC编码、缓冲区数据包与端到端时延之间的关系,优化当前时间段FEC编码器的最佳参数。实验结果证明,该算法能够使得98%的视频数据时延控制在100 ms之内,相较于静态前向纠错机制,时延平均减少了30 ms,且用户平均接收视频数据的有效损失率降低约2%。     

太赫兹超高速无线通信系统网络层算法探索

为解决现有无线网络的网络层无法匹配太赫兹超高速物理层(PHY)和媒体访问控制层(MAC)的问题,提出了一种新的太赫兹超高速无线网络层算法(PCNT)。PCNT算法通过跨层信息交互,实现了数据的聚合,加快了端到端数据的传输,从而获得更高的网络端到端吞吐量。通过仿真结果表明,采用新算法可以实现约12.6 Gbps的端到端吞吐量,而未采用新算法时仅为5.7 Gbps;同时,在端到端平均时延以及丢包率的性能上也有较大提升。PCNT新算法的提出为将来太赫兹超高速无线网络的网络层协议算法的进一步研究提供了有力的支持。     

Design of optimum criterion for opportunistic multi-hop routing in cognitive radio networks

The instability of operational channels on cognitive radio networks (CRNs), which is due to the stochastic behavior of primary users (PUs), has increased the complexity of the design of the optimal routing criterion (ORC) in CRNs. The exploitation of available opportunities in CRNs, such as the channel diversity, as well as alternative routes provided by the intermediate nodes belonging to routes (internal backup routes) in the route-cost (or weight) determination, complicate the ORC design. In this paper, to cover the channel diversity, the CRN is modeled as a multigraph in which the weight of each edge is determined according to the behavior of PU senders and the protection of PU receivers. Then, an ORC for CRNs, which is referred to as the stability probability of communication between the source node and the destination node (SPC_SD), is proposed. SPC_SD, which is based on the obtained model, internal backup routes, and probability theory, calculates the precise probability of communication stability between the source and destination. The performance evaluation is conducted using simulations, and the results show that the end-to-end performance improved significantly.     

Efficient ZF-WF strategy for sum-rate maximization of MU-MISO cognitive radio networks

This article presents an efficient quasi-optimal sum rate (SR) maximization technique based on zero-forcing water-filling (ZFWF) algorithm directly applied to cognitive radio networks (CRNs). We have defined the non-convexity nature of the optimization problem in the context of CRNs while we have offered all necessary conditions to solve the related SR maximization problem, which considers power limit at cognitive transmitter and interference levels at primary users (PUs) and secondary users (SUs). A general expression capable to determine the optimal number of users as a function of the main system parameters, namely the signal-to-interference-plus-noise ratio (SINR) and the number of BS antennas is proposed. Our numerical results for the CRN performance are analyzed in terms of both BER and sum-capacity for the proposed ZF-WF precoding technique, and compared to the classical minimum mean square error (MMSE), corroborating the effectiveness of the proposed technique operating in multi user multiple input single output (MU-MISO) CRNs.     

认知无线网络中基于Stackelberg博弈的功率控制新算法

针对认知无线网络中存在的干扰问题和功率消耗过大问题,提出了一种新的基于斯坦克尔伯格(Stackelberg)博弈的功率控制算法。建立了主次用户双层网络模型,将主用户设置为领导者,次用户设置为追随者,并对次用户产生的总干扰进行定量分析。在次用户多次博弈的过程中,动态地调整主用户单位干扰价格,在保证主用户自身正常通信前提下,尽量使得收益最大化,提高主用户的参与积极性。仿真实验表明,该算法在保证主次用户的服务质量（QoS）前提下,有效地减小了次用户的发射功率,而且能获得更高的系统容量。     

Primary user supported routing protocol for cognitive radio ad hoc networks in search of higher throughput

A routing protocol for cognitive radio ad hoc networks (CRAHNs), namely, primary user supported routing (PSR) is demonstrated in this research. Unlike existing routing protocols for CRAHN, where routing of cognitive users (CUs) is accomplished within CUs, in this proposed protocol, some of the primary users (PUs) support CUs to communicate, by forwarding CU packets. This service provided by PU is of voluntary nature. However, such assistance shall be provided by the PUs, only when they are idle, thereby, preserving the principles of cognitive radio networks (CRNs), which indicates that the operation of PU should not be disturbed by the CU activities. The proposed work is compared with cognitive ad hoc on-demand distance vector (CAODV) protocol. The performance parameters considered are routing overhead, rate of loss of packets, and e2e packet delay. PSR outperforms CAODV in all these performance parameters. There has been on average 26.25% improvement in routing overhead, 34.12% decrease in loss, and 27.01% improvement in e2e delivery in the proposed PSR.     

Optimal power allocation for multi-user OFDM and distributed antenna cognitive radio with RoF

In cognitive radio (CR), power allocation plays an important role in protecting primary user from disturbance of secondary user. Some existing studies about power allocation in CR utilize 'interference temperature' to achieve this protection, which might not be suitable for the OFDM-based CR. Thus in this paper, power allocation problem in multi-user orthogonal frequency division multiplexing (OFDM) and distributed antenna cognitive radio with radio over fiber (RoF) is firstly modeled as an optimization problem, where the limitation on secondary user is not 'interference temperature', but that total throughput of primary user in all the resource units (RUs) must be beyond the given threshold. Moreover, based on the theorem about maximizing the total throughput of secondary user, equal power allocation algorithm is introduced. Furthermore, as the optimization problem for power allocation is not convex, it is transformed to be a convex one with geometric programming, where the solution can be obtained using duality and Karush-Kuhn-Tucker (KKT) conditions to form the optimal power allocation algorithm. Finally, extensive simulation results illustrate the significant performance improvement of the optimal algorithm compared to the existing algorithm and equal power allocation algorithm.     

Distributed cross‐layer optimization for wireless regional area network‐based cognitive radio networks

This paper presents a study of a cross‐layer design through joint optimization of spectrum allocation and power control for cognitive radio networks (CRNs). The spectrum of interest is divided into independent channels licensed to a set of primary users (PUs). The secondary users are activated only if the transmissions do not cause excessive interference to PUs. In particular, this paper studies the downlink channel assignment and power control in a CRN with the coexistence of PUs and secondary users. The objective was to maximize the total throughput of a CRN. A mathematical model is presented and subsequently formulated as a binary integer programming problem, which belongs to the class of non‐deterministic polynomial‐time hard problems. Subsequently, we develop a distributed algorithm to obtain sub‐optimal results with lower computational complexity. The distributed algorithm iteratively improves the network throughput, which consists of several modules including maximum power calculation, excluded channel sets recording, base station throughput estimation, base station sorting, and channel usage implementation. Through investigating the impacts of the different parameters, simulation results demonstrates that the distributed algorithm can achieve a better performance than two other schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

基于用户分簇的认知超密集网络资源分配

针对5G时代小基站的密集部署带来的复杂干扰问题,对下行的认知无线电超密集网络下的资源分配进行了研究。为减小网络干扰,提高次用户吞吐量,提出了一种改进的基于用户分簇的资源分配算法。基于基站的覆盖范围,选出用户的强干扰基站,以用户-基站干扰关系建立用户-用户干扰图,按用户受到的平均弱干扰划分优先级对用户分簇,再为簇集群预分配频段,为每个簇分配对应频段中效用最大的信道。该资源分配算法能准确反映用户间的干扰关系,保障资源分配公平性。仿真结果表明,当用户密度与基站密度均较大时,与相同场景的已有算法相比,该改进算法有较好的抗干扰能力,能有效提高次用户的吞吐量。     

Throughput of cognitive radio networks with improved energy detector under security threats

Spectrum sensing in cognitive radio networks (CRNs) is subjected to some security threats such as primary user emulation (PUE) attack and spectrum sensing data falsification (SSDF) attack. In PUE attack, a malicious user (MU_PUE) transmits an emulated primary signal throughout the spectrum sensing interval to secondary users (SUs) to forestall them from accessing the primary user (PU) spectrum bands. In SSDF attack, malicious users (MU_SSDF) intentionally report false sensing decisions to the fusion center (FC) to influence the overall decision. While most of the existing literatures have studied the effects of these 2 types of attacks separately, the present paper evaluates the secondary network performance in terms of throughput under both the PUE and SSDF attacks with improved energy detectors (IEDs) where SU's spectrum access is hybrid, ie, either in overlay or in underlay mode. An analytical expression on throughput of SU under the simultaneous influence of both of these attacks is developed. Impact of several parameters such as IED parameter, attacker probabilities, and attacker strength on the throughput of SU is investigated. Performance of the present scheme is also compared with only PUE and only SSDF attacks. A simulation test bed is developed in MATLAB to validate our analytical results.