摘要
随着无线通信技术的高速发展以及无线用户的急剧增长，频谱资源的匮乏已经成为一个严峻的问题。认知无线电基于软件无线电，是一种有效地提高频谱资源利用率的智能无线电技术。它能够持续地感知外界的频谱环境，使用已经分配给授权用户但是暂时未被使用的空闲频谱，以实现频谱资源的最大化利用。频谱感知作为认知无线电的核心技术需要迅速、准确地识别空闲频谱。由于单用户的频谱感知会产生隐终端问题，分布式联合频谱感知会增加终端的设计复杂度，因此本文主要对认知无线电的集中式联合频谱感知进行了研究。通过采用门限优化、分簇、加权和双门限等方法提高了联合频谱感知算法的性能；通过对周期性联合频谱感知机制进行优化，使得联合频谱感知算法能够有效地应用到实际场景中。
集中式联合频谱感知有硬判决和软判决两种决策方式。硬判决中参与合作的每个认知用户向融合中心发送1比特的决策信息，虽然开销小，但是由于融合中心获得的关于授权用户的信息较少，不能够为合并提供足够的信息量，因此检测性能受到了一定的限制。软判决中，每个认知用户将对授权用户的观测值发送给融合中心，融合中心的合并算法集中了授权用户的充足信息，因此具有较好的检测性能，但是认知用户发送的信息量较大。
本文分别对认知无线电在硬判决和软判决下的联合频谱感知算法进行了详细的分析和研究，充分考虑了检测门限、信道状态和单用户检测对联合频谱感知性能的影响，主要围绕感知算法的设计、感知性能的分析和仿真来展开。此外，为了将提出的感知算法进一步应用到实际场景中，本文还提出了周期性联合频谱感知机制，并对感知周期、本地感知时间、合作用户数和搜索时间等感知机制参数进行了优化分析。
首先，针对认知无线电频谱感知的类型，包括发射端频谱感知和接收端频谱感知，对现有的单用户频谱感知方法进行了分析和比较。本文详细地阐述了各种频谱感知方法实现的原理，并对各种方法的优缺点进行了比较。本文进一步分析了单用户频谱感知可能产生的隐终端问题，并对克服隐终端问题的联合频谱感知方法进行了详细的介绍。
其次，针对硬判决联合频谱感知，提出了“AND准则”，“OR准则”和“K-OUT-N准则”等不同融合准则下，联合频谱感知门限的优化算法。该算法中各认知用户根据自身的接收信噪比和噪声方差采用局部最优门限，仿真表明：相比传统的所有用户采用相同门限的联合频谱感知算法，虽然当各用户的接收信噪比和噪声方差相同时，提出算法的性能略有降低，但是当各用户的接收信噪比和噪声方差不同时，提出算法的性能会有显著地提高。针对信道衰落会降低联合频谱感知的性能，提出了分簇联合频谱感知算法，算法中认知用户被分成若干个簇，离融合中心较近的簇头节点向融合中心发送本簇的判决信息，并由融合中心做出最终决策。仿真表明：相比传统的“OR准则”联合频谱感知算法，在理想信道下，提出算法的检测概率基本保持不变，但是在瑞利衰落信道下，提出算法的检测概率会有所提高。
再次，针对软判决联合频谱感知中各用户的判决结果对融合决策的影响不同，提出了基于加权的软判决联合频谱感知算法，算法通过为认知用户分配不同的权重来表现每个用户对融合决策所作的贡献。针对军用和民用两个不同的场景，分别提出了最大化吞吐量加权和最小化干扰容量加权两种权重分配算法，此外本文还将算法推广到宽带联合频谱感知中，提出了基于加权的宽带联合频谱感知算法。仿真表明：提出的算法能够获得较大的吞吐量和对授权用户产生较小的干扰，并且受信道衰落的影响较小。为了在认知用户发送的信息量和联合频谱感知的检测性能之间获得折中，本文提出了基于加权的双门限联合频谱感知算法，该算法采用硬判决和软判决相结合的方式，检测性能介于硬判决和软判决之间。仿真表明：提出算法的检测概率比硬判决的要高，发送的信息量比软判决的要少。
最后，为了将联合频谱感知算法更好地应用于实际场景中，提出了周期性单信道联合频谱感知机制。该机制中，认知无线电的通信过程被分为若干个周期，每个周期内认知用户先感知授权用户，如果检测到授权用户不存在，认知用户在本周期接下来的时间才进行数据传输；否则如果检测到授权用户存在，认知用户需要搜索新的空闲信道。为了提高频谱感知机制的性能，本文对感知周期、本地感知时间、合作用户数和搜索时间等感知机制参数进行了优化。仿真结果表明：通过对感知机制进行优化，认知无线电能够减少对授权用户的干扰，提高自身的吞吐量以及降低空闲信道的搜索时间。本文进一步将周期性联合频谱感知机制推广到宽带联合频谱感知中，提出了周期性宽带多时隙联合频谱感知机制，通过对感知时隙数和合作用户数的联合优化，宽带认知无线电的吞吐量随着子信道数的增加能够获得显著地提高。
With the high-speed development of wireless communication technologies andrapid increasing of wireless users, the scarcity of spectrum resources has been aserious problem. Cognitive radio based on software radio, is an intelligent wirelesstechnology which can improve the spectrum utilization effectively. In order to makefull use of the spectrum resources, cognitive radio can use the idle spectrum whichhas been allocated to the authorized user but not temporarily used throughcontinually sensing the external spectrum environment. Spectrum sensing as thecore of cognitive radio needs to identify the idle spectrum quickly and accurately.Since the single-user spectrum sensing will bring hidden terminal problem and thedistributed cooperative spectrum sensing will increase the designed complexity ofterminal, the centralized cooperative spectrum sensing is investigated in thisdissertation. Through the methods of threshold optimization, clustering, weighing,and double thresholds, the performance of cooperative spectrum sensing can beimproved. Through the optimization of periodic cooperative spectrum sensingmechanism, the sensing algorithms can be used in the actual scene effectively.
Centralized cooperative spectrum sensing has two decision fashions: harddecision and soft decision. In hard decision, each cooperative cognitive user sends1-bit decision information to the fusion centre. The overhead of hard decision islittle, but since the fusion centre may acquire less information of authorized userand the combination cannot obtain enough information capacity, the detectedperformance of hard decision is restricted. In soft decision, each cognitive usersends the observed value of authorized user to the fusion centre, and since thecombination algorithm of the fusion center collects enough information ofauthorized user, the detected performance of soft decision is preferable, but theinformation capacity sent by each cognitive user is large.
This dissertation respectively analyzes and investigates the algorithms of thecooperative spectrum sensing based on hard decision and soft decision in detail.After a full account of the influence of detected threshold, channel state, andsingle-user detection on cooperative spectrum sensing, the dissertation mainlyfocuses on the designing of the sensing algorithms, and the analysis and simulationof the sensing performance. In addition, in order to further apply the proposedsensing algorithm in the actual scene, the dissertation proposes the mechanism ofperiodic cooperative spectrum sensing, and the parameters of the sensingmechanism such as sensing period, local sensing time, number of cooperative users and search time etc, are respectively optimized and analyzed.
Firstly, according to the type of spectrum sensing for cognitive radio includingtransmitter spectrum sensing and receiver spectrum sensing, the existing methods ofsingle-user spectrum sensing are analyzed and compared. The dissertation explainsthe implemental principle of each sensing method in detail, and compares theadvantages and disadvantages of these methods. The dissertation further analyzesthe hidden terminal problem brought by the single-user spectrum sensing, andintroduces the cooperative spectrum sensing which is used to conquer the hiddenterminal problem in detail.
Secondly, in allusion to the spectrum sensing based on hard decision, thethreshold optimization algorithm of cooperative spectrum sensing by “AND Rule”,“OR Rule”, and “K-OUT-N Rule” is proposed. In this algorithm, each cognitiveuser adopts the local optimal threshold according to its received SNR and noisevariance, and the simulation shows that compared with the traditional cooperativespectrum sensing algorithm in which all the cognitive users adopt the uniformthreshold, when the received SNR and noise variance of each user is uniform, theperformance of the proposed algorithm slightly decreases, however, when thereceived SNR and noise variance of each user is different, the performance of theproposed algorithm can increase observably. Since the channel fading may decreasethe performance of cooperative spectrum sensing, the clustering cooperativespectrum sensing algorithm is proposed. In this algorithm, cognitive users aredivided into several clusters, and the cluster heads near the fusion centre send thedecision information of their local clusters to the fusion centre. The simulationshows that compared with the traditional cooperative spectrum sensing by “ORRule”, the detection probability of the proposed algorithm keeps invariable inperfect channel but increases in fading channel.
Thirdly, according to the different influence of the decision result of each useron the combination decision of cooperative spectrum sensing based on soft decision,the algorithm of weighed cooperative spectrum sensing based on soft decision isproposed, and the algorithm represents the contribution of each user to thecombination decision through allocating the different weights to the cognitive users.In allusion to the military scene and civil scene, the dissertation respectivelyproposes the two algorithms of weight allocation including weighing based onmaximizing throughput and weighing based on minimizing interference capacity. Inaddition, the dissertation extends the algorithm to the wideband cooperativespectrum sensing, and proposes the weighed wideband cooperative spectrumsensing algorithm. The simulation shows that the proposed algorithm can achieve larger throughput, produce less interference to the authorized user, and get lessinfluence of the channel fading. In order to obtain the tradeoff between theinformation capacity sent by cognitive user and the detected performance ofcooperative spectrum sensing, the dissertation proposes the weigheddouble-threshold cooperative spectrum sensing algorithm. This algorithm combineshard decision and soft decision, and its sensing performance is between those ofhard decision and soft decision. The simulation shows that the detection probabilityof the proposed algorithm is higher than that of hard decision, while the sentinformation capacity of the proposed algorithm is less than that of soft decision.
Lastly, in order to apply the cooperative spectrum sensing algorithms to theactual scene better, the mechanism of periodic single-channel cooperative spectrumsensing is proposed. In this mechanism, the communication process of cognitiveradio is divided into several periods, and in each period the cognitive user firstlysenses the authorized user. If the absence of the authorized user is detected, thecognitive user can transmit data during the following time of this period, otherwiseif the presence of the authorized user is detected, the cognitive user needs to searchfor another idle channel. In order to improve the performance of the spectrumsensing mechanism, the parameters of the sensing mechanism such as sensingperiod, local sensing time, number of cooperative users, and search time arerespectively optimized. The simulation shows that through the optimization of thesensing mechanism, cognitive radio can decrease the interference to the authorizeduser, improve the throughput, and decrease the search time. The dissertationexpands the periodic cooperative spectrum sensing mechanism to the widebandcooperative spectrum sensing, and the periodic wideband multi-slot cooperativespectrum sensing mechanism is proposed. Through the joint optimization of thenumbers of the sensing slots and cooperative users, the throughput of widebandcognitive radio can be improved observably with the increasing of the number ofthe sub-channels.
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