Cognitive Radios： A Survey On Spectrum Sensing, Security and Spectrum Handoff

Pervasive wireless computing and communication have created an ever-increasing demand for more radio spectrum. Since, most of the spectrum is underutilized, it motivated the introduction of the concept of cognitive radios, a dynamic spectrum access enabling technology. The first stage of cognitive radio is to sense the environment and determine which parts of the spectrum are available. This is achieved through spectrum sensing. However, spectrum sensing poses the most fundamental challenge in cognitive radios. Moreover, cognitive radios suffer from many vulnerabilities and the security attacks can severely degrade the performance of cognitive radios. This paper surveys state-of-theart research on spectrum sensing and security threats in cognitive radios. Lastly, we also consider the analysis of issues related to spectrum handoffs in cognitive radios.

SPECTRUM HANDOFF IN COGNITIVE RADIO WITH FUZZY LOGIC CONTROL

The secondary usage of spectrum has been investigated in Cognitive Radio(CR) network to resolving the spectrum scarcity issue in wireless communication.When Primary Users(PU) who own the spectrum appear,spectrum handoff is needed to maintain the communications of Secondary Users.But the decision making of spectrum handoff is a challenge issue for CR network,because the input of decision making,which obtain through spectrum sensing,is heterogeneous and inexact.In this paper we will use fuzzy logic control theory to solve this issue and make use of new information for handoff operation:the probability of PU's occupancy at a certain channel.Our new algorithm can make more intelligent decision compared to simple traditional spectrum handoff decision making and reduce the probability of spectrum handoff,also the performance of SU's communication can be enhanced.

Energy-Efficient Target Channel Sequence Design for Spectrum Handoffs in Cognitive Radio Networks

Cognitive radio is considered as an efficient way to improve the spectrum efficiency. As one of its key technologies,spectrum handoff can guarantee the transmission continuity of secondary users(SUs). In this paper,we address a new and more generalized spectrum handoff problem in cognitive radio networks(CRNs),by considering simultaneously energy efficiency,multiple spectrum handoffs and multiple channels. Furthermore,effects of the primary users'(PUs')arrival and service rate on the target channel sequence selection are also considered. In order to obtain the energy-efficient target channel sequence,we firstly analyze the energy consumption and the number of delivered bits per hertz in the spectrum handoff process,and formulate a ratio-type energy efficiency optimization problem,which can be transformed into a parametric problem by utilizing fractional programming. Then,we propose an algorithm combining dynamic programming with bisection(DPB)algorithm to solve the energy efficiency optimization problem. Our simulation results verify that the designed target channel sequence has better performance than the existing algorithms in terms of energy efficiency.

Spectrum handoff scheme with multiple attributes decision making for optimal network selection in cognitive radio networks

It is envisaged that in future Cognitive Radio （CR） networks deployment, multiple radio access networks may coexist. The networks may have different characteristics in terms of multiple attributes. CRs will have choices of selecting the optimal network out of the available networks. Optimal network selection is a challenging task that can be performed by spectrum handoff with Multiple Attribute Decision Making （MADM）. The spectrum handoff decision with MADM provides wider and optimal choice with quality of service. This motivates the development of a spectrum handoff scheme with MADM methods such as simple additive weighting, a technique for order preference by similarity to the ideal solution, a grey relational analysis and a cost function based method, which is the objective of this study. The CR preferences are based on voice, video and data services, called triple play services. The numerical results show that all MADM methods are effective for selecting the optimal network for spectrum handoff with a reduced complexity for the spectrum handoff decision. The paper shows that the proposed spectrum handoff scheme can be effectively implemented to select the optimal network according to triple play services in CR networks.

Analysis of cumulative handoff delay for graded secondary users in cognitive radio networks

According to the fact that the secondary users＇ delay requirements for data transmission are not unitary in cognitive radio networks, the secondary users are divided into two classes, denoted by SU1 and SU2, respectively. It is assumed that SU1 has a higher priority to occupy the primary users＇ unutilized channels than SU2. A preemptive resume priority M/G/1 queuing network is used to model the multiple spectrum handoffs processing. By using a state transition probability matrix and a cost matrix, the average cumulative delays of SU1 and SU2 are calculated, respectively. Numerical results show that the more the primary user＇s traffic load, the more rapidly the SU2＇s cumulative handoff delay grows. Compared with the networks where secondary users are unitary, the lower the SUI＇s arrival rate, the more obviously both SUI＇s and SU2＇s handoff delays decrease. The admission access regions limited by the maximum tolerable delay can also facilitate the design of admission control rules for graded secondary users.

Evolution Handoff Strategy for Real-Time Video Transmission over Practical Cognitive Radio Networks

The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.

Performance Evaluation of Spectrum Detection in Cognitive Radio Network

In mobility management, detection of spectrum hole plays very important role for doing spectrum handoff mechanism. Operation of the cognitive radio depends on the spectrum sensing which is the most important task in case of cognitive radio network. Detection of spectrum holes (underutilized sub-bands of the radio spectrum) estimates average power, throughput and utilized time for each spectrum hole. But in case of reactive spectrum handoff mechanism, spectrum handoff delay becomes tedious task. So in order to make spectrum handoff mechanism efficient our scheme proposed spectrum handoff mechanism with negligible spectrum handoff delay. In this paper we had real time experimental setup with the spectrum handoff mechanism. We investigate algorithm for spectrum handoff mechanism which strongly minimizes spectrum handoff delay of cognitive radio network using spectrum detection method for sensing spectrum holes.

认知无线网络中频谱切换算法研究综述

无线频谱资源的匮乏和多用户争用环境,导致认知无线网络中频谱切换研究面临严峻挑战.本文阐述了频谱切换的基本原理,包括频谱切换的概念和特征、频谱切换的主动决策和被动决策分类、频谱切换过程及建模抽象的方法等几个方面.其次,重点以数学建模工具为主线,综述了基于概率论、马尔可夫过程、排队论、模糊逻辑、模糊神经网络等5类代表性的频谱切换算法,评述了学术界在各类频谱切换算法上的重要研究成果;最后,基于对已有算法和研究成果的分析,总结了当前研究中存在的非理想频谱检测、目标信道选择、空闲信道动态性等主要问题,预测了频谱切换的未来研究方向.

认知无线网络中基于混合频谱切换的最优目标信道选择算法

在主动频谱切换中,预先确定目标信道存在高失效风险,从而增加切换时延的问题。该文提出一种基于混合主被动频谱切换的最优目标信道选择算法。该算法结合主动频谱切换和被动频谱切换的优点,引入最小累积切换时延评价标准,综合考虑次用户的多次中断、主用户的到达率和非理想频谱检测对次用户累积切换时延的影响,并详细分析和推导了非理想检测下次用户的累积切换时延。仿真表明,相较于主动和被动频谱切换中目标信道选择策略,在信道状态变化频繁或业务量较大等极端情况下,该算法的性能优势尤为明显。

认知无线电频谱切换目标信道访问机制

针对认知无线电先应式决策频谱切换,该文提出按照信道平均空闲时间递减的顺序对目标信道进行访问的机制,证明了该机制在主用户信道空闲时间服从均匀分布、Rayleigh分布以及Weibull分布下均能够保证频谱切换失败概率最小。仿真结果表明所提机制得到的频谱切换失败概率要远远小于随机访问机制的切换失败概率。另外,当能够获得数十次信道空闲时间观测样本情况下,虽然存在估计误差,但所得频谱切换失败概率与理想最优频谱切换失败概率非常接近。

认知无线电中一种频谱聚合的切换策略

针对认知无线电频谱聚合系统下降低频谱切换延迟、减少频谱切换次数的问题,提出一种主动式频谱切换策略。该策略在频谱聚合跨度的限制下,根据认知用户工作状态转移概率,制定其频谱切换的规则,以达到认知用户在利用频谱聚合技术的同时,实现平滑切换并避免与主用户发生碰撞的目的。另外,在此基础上提出了一种基于切换概率的候选信道选择方法,用来进一步降低频谱切换延迟和频谱切换次数。仿真结果显示当主用户到达的平均时间间隔高于50时隙,并且认知用户子信道的平均服务保持时间小于100时隙时,频谱聚合切换策略能将切换次数稳定在5次以下,同时将切换延迟降低到30时隙以下。仿真结果表明该策略既保证良好的实时性又尽量的减少由切换次数带来的系统开销,从而提高系统效率。

认知无线网络中基于信道感知排序的频谱切换

在认知无线网络中,一旦主用户出现,正在使用该频段的认知用户需退出该频段,寻找另外一个空闲的频段继续未完成的传输,这就是认知无线网络中的频谱切换。评价认知用户频谱切换性能有两个重要的参数:切换时延和切换次数。本文提出了一种基于信道感知排序的频谱切换方法,以同时减少切换时延和切换次数。在进行信道感知排序时,本文使用的方法同时考虑了切换发生时信道空闲概率以及使用该信道时不再发生切换的概率。仿真结果表明,与传统信道排序方法相比,本方法的切换时延可以达到与传统方法一样的性能,然而切换次数却大大地减少了。

基于分级的频谱切换技术研究

为解决认知无线电网络中频谱切换机制问题,以提高连接保持概率和频谱利用率,降低频谱切换延迟,综合考虑了频谱质量和次用户的业务差异性,将可用频谱资源进行分类并建立起两种使用模型;结合主用户出现概率、信道选择机制和冲突避免算法等因素,提出了一个完整的基于分级的频谱切换机制。仿真结果表明,该机制使得用户在切换时能够快速且无冲突地找到目标信道,有效地保证了主用户和次用户的服务质量。

认知无线电主动切换的延时优化

在认知无线电通信系统中,当主用户出现在授权频谱时,认知用户必须及时空出该频段,这个过程称作频谱切换。衡量频谱切换算法的一项重要指标是切换延时,切换延时越短,认知用户越能快速顺利地进行数据传输。在分析切换机制分类的基础上,提出了一种基于信道空闲概率排序的频谱切换算法,并且通过仿真验证了其理论上的有效性。针对实际的信道模型,对该算法进行了改进,比较了改进前后的切换延时,仿真结果表明,改进后的算法对缩短切换延时效果显著。

基于信道预测的认知无线电混合频谱切换算法

针对认知无线电网络,提出了一种将被动式频谱切换与主动式频谱切换相结合的混合频谱切换算法。该算法基于主用户信道的连续时间马尔可夫链模型,预测出信道的未来状态信息,根据该预测结果周期性地对正在通信的认知用户执行主动式频谱切换。该算法对于由于碰撞而退出信道的认知用户执行被动式频谱切换。仿真结果表明,相对于被动频谱切换算法,混合频谱切换算法在保持认知用户阻塞概率和中断概率不变的前提下可显著减少认知用户和主用户间的碰撞次数,能够提高认知无线电网络的频谱利用率。

基于隐马尔可夫模型的认知无线频谱切换方法

认知无线网络(cognitive radio network,CRN)中,为降低认知用户对授权用户干扰,需尽可能的减少频谱切换次数。提出了一种基于预测信道空时间(prediction of the channel idle time,PCIT)的认知无线动态频谱切换方法。该方法基于已知状态序列的隐马尔可夫模型(known-state sequence hidden Markov model,KSS-HMM),利用信道状态的历史信息预测信道未来空闲时间期望及传输数据包的数量,并给出了备选信道的选择方法,通过比较每个备选信道的传输数据量来选择最佳信道进行数据传输。仿真结果表明,与随机信道选择和传统选择方法相比,该方法能明显减少信道切换次数,同时提高了认知用户的吞吐量。

机会频谱接入系统的切换请求排队机制及性能分析

针对非实时业务的特点,该文提出了机会频谱接入系统的两种切换请求排队方案,并采用二维Markov模型对其性能进行了建模分析,得到了呼叫阻塞率、强制中断率、信道利用率等系统性能关键参数的解析结果。数值结果分析表明,提出的两种切换请求排队方案是降低系统强制中断率的有效方法,且可克服切换信道预留机制阻塞率高、信道利用率低的缺点,信道利用率最多可提高26%。仿真实验验证了理论分析的正确性。

基于预留信道机制的CR频谱切换描述及改进

利用IEEE802.22标准草案中的预留信道机制,分析和描述认知无线电的3种基本频谱切换方案。针对预留信道机制以牺牲新呼阻塞率换取较低切换阻塞率的不足,提出对新呼用户进行排队缓冲的方法,并利用二维马尔可夫模型和排队理论,给出其状态转移图。仿真结果表明,该方法在保证切换性能的条件下,能有效降低新呼阻塞率,并使GoA值大幅下降。

基于时间预测的多跳频谱切换算法研究

针对集中控制认知无线网络,在考虑频谱异构特性的同时,为保证频谱切换业务的服务质量,提出了一种多跳频谱切换算法。通过建立用户移动模型来预测分配信道的可使用时间;设计出路径中不同类型节点的路由处理方法;认知基站根据预测最短路径时间和路由请求包中的时间戳来选择最优路径。仿真结果表明,提出的多跳频谱切换算法能够大大降低切换阻塞概率,提高信道利用率;用户移动对信道可使用时间有着显著的影响。

一种结合信道性能的频谱分配算法

在认知无线电网络中,由于授权信道的时变性,各可用信道的性能相差较大。为避免过多使用忙闲交替频繁的信道,首先用ON-OFF模型建模授权信道的使用情况,并推导了认知用户切换概率,提出了一种用信道状态变化率衡量信道性能的方法。在此基础上提出了一种结合信道性能的频谱分配算法,在网络吞吐量相同或相近情况下优先分配性能较好的信道。仿真分析表明,这种结合信道性能的频谱分配算法在降低切换概率的同时提高了实际总效益。