认知无线电网络组播路由算法和协议综述

认知无线电网络（CRN）在实现更好的无线带宽利用率和提高无线应用质量方面发挥着至关重要的作用。由于认知用户可用频谱机会的动态特性,认知无线电网络中的组播是一个具有挑战性的问题。研究者们已经提出了多种在认知无线电网络中进行有效组播的方案,包括基于优化理论、网络编码、机器学习、博弈论的方案等。总结了解决组播问题有效的算法和技术,并对已有的无线电网络中的组播协议进行了全面的综述,最后给出了未来的研究方向。     

混合共享认知无线网络信道分配算法

混合频谱共享是适应认知用户不同地理分布的有效频谱共享模式。信道分配是无线通信网络中关键的问题之一,近年来得到了广泛研究。集中式信道分配算法是最常用的算法形式,但在认知无线电网络这种分布式系统中,集中式算法不易实现。将混合共享认知无线网络的信道分配问题构建为一对一的匹配博弈,提出了分布式用户-信道匹配算法。该算法数学复杂度低,且能够达到稳定匹配。仿真结果表明,算法收敛时间短,稳定匹配状态下的平均传输速率与使用匈牙利算法的最优分配算法所获得传输速率相接近,远优于随机分配算法的传输速率。     

基于严格位势博弈的动态预留信道选择

由于认知无线电网络中可用频谱存在时变特性,以往频谱切换中静态式的信道预留方式显然不能满足实际要求。为解决这一问题,在讨论认知无线电交互模型与博弈论的基础上,提出了基于严格位势博弈的动态预留信道选择方法,该方法将认知网络作为一种干扰减小网络,利用博弈交互原理实现动态参数的调整。在802.11h平台下给出了性能仿真分析。结果表明,该方法能够在增加少量网络总干扰的情况下实现动态预留信道选择,并且所预留的信道不受环境影响,从而适用于所有网络覆盖范围。     

Multi-leader multi-follower Stackelberg model for cognitive radio spectrum sharing scheme

Radio spectrum is one of the most scarce and variable resources for wireless communications. Therefore, the proliferation of devices and rapid growth of wireless services continue to strain the limited radio spectrum resource. Cognitive Radio (CR) paradigm is a promising technology to solve the problem of spectrum scarcity. In this paper, a new fair-efficient spectrum sharing scheme is proposed for cognitive radio networks. Based on the multiple-leader multiple-follower Stackelberg game model, the proposed scheme increases opportunistic use of the licensed radio spectrum. To adaptively use the spectrum resource, control decisions are coupled with one another; the result of the each user’s decisions is the input back to the other user’s decision process. Under widely diverse network environments, this adaptive feedback process approach can provide an effective way of finding a suitable solution. The simulation results demonstrate that the proposed scheme has excellent network performance, while other schemes cannot offer such an attractive performance balance.     

大规模认知无线电网络的时延分析

时延作为无线网络的最基本的性能之一,对网络信息分发、路由协议设计、节点部署等都具有重要意义。与传统的无线网络不同,认知无线电网络的频谱资源具有动态变化性,该特性会对网络时延产生极大的影响。因此,如何对动态频谱环境下的大规模认知无线电网络进行时延分析,是一项很具挑战性的课题。为此,首先对动态频谱环境进行建模,将认知用户的频谱接入过程建模为一个连续时间的马尔可夫链,并建立认知用户的生存函数来量化授权用户活动以及信道数量对频谱环境的影响;其次,将上述模型与首次通过渗流理论结合起来,研究了大规模认知无线电网络时延的伸缩规律,并获取了更为精确的时延与距离比的上限值。理论分析及仿真结果表明,动态频谱环境与密度一样会对时延产生极大影响。研究结论对认知无线电网络的设计具有重要的指导意义。     

认知Wi-Fi 2.0 无线网络多用户动态分层功率控制算法

具有认知性、自主性和适变性等特点的认知Wi-Fi 2.0无线网络技术,作为提高无线网络容量的重要技术不断引起学术界、标准组织和工业界的关注.针对现有功率控制技术不能刻画多个认知节点存在分层决策的现象,提出一种认知Wi-Fi 2.0无线网络中多用户动态分层功率控制算法.基于提出的斯坦科尔伯格(Stackelberg)容量最大化博弈模型,为认知Wi-Fi 2.0无线网络中感知信息不对称的多用户分别设计了分布式功率控制方法,实现领导者用户和跟随者用户的多阶段动态交互在保证个体效用的同时实现网络整体性能.该算法根据当前认知Wi-Fi 2.0无线网络中多个认知节点接入频谱顺序的不同,确定领导者用户和跟随者用户;然后,对于领导者和跟随者分别采用不同的功率控制策略,并多次交互实现多用户分层算法的动态交互收敛.蒙特卡洛仿真验证了算法的有效性.     

RAC: Range Adaptive Cognitive Radio Networks

In recent years, cognitive radio has received a great attention due to tremendous potential to improve the utilization of the radio spectrum by efficiently reusing and sharing the licensed spectrum bands, as long as the interference power inflicted on the primary users of the band remains below a predefined threshold level. Cognitive radio allows the secondary users in the cognitive radio network to access the licensed spectrum of the primary users opportunistically. In this paper, an autonomous distributed adaptive transmission range control scheme for cognitive radio networks which is called the RAC is proposed. The RAC considers the QoS requirements of both the primary and the secondary users simultaneously. The cognitive user's maximization of its achievable throughput without interfering the primary user by adapting transmission range of the secondary users dynamically is the key feature of the RAC. One of the advantages of using the proposed scheme is its implementation simplicity. The RAC is compared to other cognitive radio schemes in a simulation environment by using ns2. Simulations indicate that, the RAC can well fit into the mobile cognitive radio ad hoc networks and improve the network performance. Having compared to the other schemes utilizing contemporary cognitive radio technology, the RAC provides better adaptability to the environment and maximizes throughput and minimizes data delivery latency.     

认知无线电网络非协作博弈功率分配算法研究

发现干扰节点,并将功率适当地分配至各个可用频谱上,以提高节点数据率和网络吞吐量,是认知无线电网络当前的研究热点.本文提出一种基于非协作博弈功率分配方法(PANG),以提高认知无线网络系统吞吐量.PANG将认知网络节点功率分配问题转化为非协作博弈问题,并采用线性代价因子的方法抑制功率分配时的盲目性.理论分析表明,PANG存在纳什均衡点,具有帕累托最优解.本文使用Matlab对PANG算法进行仿真,仿真结果表明,PANG算法能够比PIWF算法更加合理的进行功率分配,并有效的提高系统吞吐量.     

Cognitive radio network security: A survey

Recent advancements in wireless communication are creating a spectrum shortage problem on a daily basis. Recently, Cognitive Radio (CR), a novel technology, has attempted to minimize this problem by dynamically using the free spectrum in wireless communications and mobile computing. Cognitive radio networks (CRNs) can be formed using cognitive radios by extending the radio link features to network layer functions. The objective of CRN architecture is to improve the whole network operation to fulfil the user's demands anytime and anywhere, through accessing CRNs in a more efficient way, rather than by just linking spectral efficiency. CRNs are more flexible and exposed to wireless networks compared with other traditional radio networks. Hence, there are many security threats to CRNs, more so than other traditional radio environments. The unique characteristics of CRNs make security more challenging. Several crucial issues have not yet been investigated in the area of security for CRNs. A typical public key infrastructure (PKI) scheme which achieves secure routing and other purposes in typical ad hoc networks is not enough to guarantee the security of CRNs under limited communication and computation resources. However, there has been increasing research attention on security threats caused specifically by CR techniques and special characteristics of CR in CRNs. Therefore, in this research, a survey of CRNs and their architectures and security issues has been carried out in a broad way in this paper.     

认知无线电在医疗无线网络中的应用研究

认知无线电是允许未授权用户可以机会式接入使用授权用户的电磁频谱的一种技术．这一新兴技术的目的是为了提高无线资源的使用率。在医疗环境中。认知无线电具有很大的潜力。可以解决分配给医疗应用的频谱的稀缺性所造成的干扰问题。介绍一些医疗无线网络的认知无线电技术应用的相关研究及所面临的挑战和发展趋势。     

Reinforcement learning for context awareness and intelligence in wireless networks: Review, new features and open issues

In wireless networks, context awareness and intelligence are capabilities that enable each host to observe, learn, and respond to its complex and dynamic operating environment in an efficient manner. These capabilities contrast with traditional approaches where each host adheres to a predefined set of rules, and responds accordingly. In recent years, context awareness and intelligence have gained tremendous popularity due to the substantial network-wide performance enhancement they have to offer. In this article, we advocate the use of reinforcement learning (RL) to achieve context awareness and intelligence. The RL approach has been applied in a variety of schemes such as routing, resource management and dynamic channel selection in wireless networks. Examples of wireless networks are mobile ad hoc networks, wireless sensor networks, cellular networks and cognitive radio networks. This article presents an overview of classical RL and three extensions, including events, rules and agent interaction and coordination, to wireless networks. We discuss how several wireless network schemes have been approached using RL to provide network performance enhancement, and also open issues associated with this approach. Throughout the paper, discussions are presented in a tutorial manner, and are related to existing work in order to establish a foundation for further research in this field, specifically, for the improvement of the RL approach in the context of wireless networking, for the improvement of the RL approach through the use of the extensions in existing schemes, as well as for the design and implementation of RL in new schemes.     

认知无线电中基于博弈论的频谱分配算法*

利用博弈论分析了认知无线电网络中动态频谱分配问题,构建了基于博弈论的认知无线电频谱分配问题模型,提出了基于潜在博弈论的分布式频谱分配算法,并得到了相应博弈过程的纳什均衡。仿真结果表明,该算法能在较短时间内收敛到稳定状态,潜在函数取值达到最大值、系统总干扰水平降到最小、用户的SIR水平得到明显改善,达到了潜在博弈下信道分配的纳什均衡,实现了提高频谱利用率的目的。     

认知无线Mesh网络中基于概率的贪婪频谱决策技术研究

认知无线电网络传统的频谱决策方法中次用户根据不同的判据选择信道,会引起信道竞争和拥塞。针对认知无线Mesh网络中基于概率的频谱决策方法,提出一种贪婪信道选择算法,当发生频谱切换时,其结合改进的抢占优先(相似文献   

Stochastic characterization of the spectrum sharing game in ad-hoc networks

This work focuses on infrastructure-less ad hoc wireless networks where multiple transmitter/receiver pairs share the same radio resources (spectrum); transmitters have to choose how to split a total power budget across orthogonal spectrum bands with the goal to maximize their sum rate under cumulative interference from concurrent transmissions. We start off by introducing and characterizing the non-cooperative game among transmitter/receiver pairs when the network topology is deterministically given. The corresponding Nash equilibria are derived, highlighting their dependency on the topological parameters (distances between wireless nodes, propagation model, and background noise power). The analysis is then extended to the case of random network topologies drawn from a given spatial stochastic process. Tools of stochastic geometry are leveraged to derive a statistical characterization of the equilibria of the spectrum sharing game. Finally, a distributed algorithm is proposed to let the players of the spectrum sharing game converge to equilibria conditions. Numerical simulations show that the proposed algorithm drives the users to stable points that are close to the equilibria of the game requiring limited information exchange among nodes.     

基于多次博弈的认知无线电频谱动态分配算法

针对认知无线电网络的复杂性以及动态性,通过单次博弈很难找到最佳平衡点的问题,提出了一种基于多次博弈的动态频谱分配算法,并通过博弈论的相关原理对该算法中纳什均衡的存在性和唯一性进行了验证。仿真结果表明,该算法收敛性优于传统算法,经过4~6次迭代即可收敛于稳定状态,不仅提高了收敛速度,满足了通信系统对实时性的要求,同时也能够在系统中所有认知用户都满足信干比阈值要求的基础上进一步降低发射功率,达到了降低系统总干扰水平的目标,系统性能明显提高。     

认知无线电网络双天线多信道MAC协议

在认知无线电网络中,媒体接入控制(MAC)协议的主要功能包括信道感知、选择和接入控制,其中感知时间和传输时间的长度对网络的性能有着重要的影响。在动态无线网络环境下,如何合理分配感知时间和传输时间是个挑战性问题。提出了一种双天线多信道分布式认知无线电MAC（TM-MAC）协议,不需要在传输之前对信道进行感知。节点可以在其它节点传输数据的同时对频谱资源进行检测,然后利用空闲的频谱资源通信。建立了数学模型分析在饱和网络状况下MAC协议的吞吐量。仿真分析表明TM-MAC协议能够有效提高网络的吞吐量。     

认知无线电网络安全路由问题研究

认知无线电是一种智能频谱共享技术,可显著提高频谱的利用率。根据认知无线电在国内外的研究现状以及该技术的应用发展趋势,给出了认知无线电网络中安全路由的一个研究体系。该体系以一种混合式的网络结构为基础,将身份认证,密钥分配,组播树的创建,对当前空闲频谱信息进行合理定价,递减式组播模式以及跨层设计路由等问题结合在一起,形成了一个较为完备的认知无线电网络安全路由问题体系,为未来认知无线电安全路由的研究开拓了一条新路。     

An Effective Secure MAC Protocol for Cognitive Radio Networks

The vast revolution in networking is increasing rapidly along with technology advancements, which requires more effort from all cyberspace professionals to cope with the challenges that come with advanced technology privileges and services. Hence, Cognitive Radio Network is one of the promising approaches that permit a dynamic type of smart network for improving the utilization of idle spectrum portions of wireless communications. However, it is vulnerable to security threats and attacks and demands security mechanisms to preserve and protect the cognitive radio networks for ensuring a secure communication environment. This paper presents an effective secure MAC protocol for cognitive radio networks, significantly enhancing the security level of the existing DSMCRN and SSMCRN protocols by eliminating the authentication server’s necessity, which can be a single point of failure to compromise the entire network communication. The proposed protocol has proven to be effective and reliable since it does not rely on a centralized entity for providing the required security for a single pair of cognitive users. The protocol also improves the performance in the context of fast switching to data channels leading to higher throughput is achieved compared to the benchmark protocols.     

Outage and energy-efficiency analysis of cognitive radio networks: A stochastic approach to transmit antenna selection

Cognitive radio networks have recently attracted significant research attention owing to their promise for application in future cellular communication. In this light, given the intense power consumption of wireless networks, considerable research is now being directed at designing random cognitive radio networks with enhanced energy efficiency. In this study, we investigate the outage probability and energy efficiency in a cognitive radio network, modeling the locations of the primary users and cognitive users as a Poisson point process. We derive closed-form expressions for the outage probability and energy efficiency with consideration of the probabilities of unoccupied (not utilized by the primary users) channel selection and successful transmission for imperfect detection in an interference-limited environment of cognitive radio network. Furthermore, we propose a transmit antenna selection method for the cognitive transmitter in such networks and accordingly develop closed-form expressions for the outage probability and energy efficiency. The study reported here highlights the importance of combining the capabilities of unoccupied channel selection and successful transmission in cognitive radio networks to achieve optimal performance regarding outage probability and energy efficiency. In terms of energy efficiency, there is an optimal threshold that maximizes the energy efficiency. For implementation in transmit antenna selection, the outage probability can be significantly decreased by increasing the number of transmit antennas, even though the energy efficiency is maximized at the target outage probability.     

An analysis on decentralized adaptive MAC protocols for cognitive radio networks

The scarcity of bandwidth in the radio spectrum has become more vital since the demand for more and more wireless applications has increased. Most of the spectrum bands have been allocated although many studies have shown that these bands are significantly underutilized most of the time. The problem of unavailability of spectrum and inefficiency in its utilization has been smartly addressed by the cognitive radio (CR) technology which is an opportunistic network that senses the environment, observes the network changes, and then uses knowledge gained from the prior interaction with the network to make intelligent decisions by dynamically adapting their transmission characteristics. In this paper, some of the decentralized adaptive medium access control (MAC) protocols for CR networks have been critically analyzed, and a novel adaptive MAC protocol for CR networks, decentralized non-global MAC (DNG-MAC), has been proposed. The results show the DNG-MAC outperforms other CR-MAC protocols in terms of time and energy efficiency.