认知无线电是缓解当前频谱分配不均和利用不充分的重要技术手段，主要通过感知无线通信环境中的频谱使用情况实现频谱管理，以此提升频谱利用率。在认知无线电系统中，可靠的频谱感知是实现频谱管理的先决条件，合理的频谱共享技术可以使认知用户在不影响主用户通信的前提下接入空闲频谱，保证用户的传输质量。     

针对单节点信号感知易受路径损耗、阴影效应及多径衰落影响的问题，提出了改进的基于功率谱的频谱感知算法。改进算法利用功率谱密度的正交基不易受其他干扰而改变的特性，解决了特征向量因噪声影响而无法精准指向主用户信号方向的问题。算法得到信号在经过正交展开后的自相关函数，经傅里叶变换求得信号功率谱，利用功率谱极值之差与功率谱几何平均之比作为统计量，并推导出改进算法的检测概率和虚警概率，证明了算法性能不受噪声功率影响。实验结果表明在相同的虚警概率或信噪比条件下改进算法的检测概率更高，验证了算法的有效性。

基于可靠的频谱感知结果，提出一种基于契约论的部分用户协作的频谱共享算法。算法主要解决不同信息场景中无线通信系统的契约设计问题和有限预算下认知用户选择问题。该算法以多个认知用户可提供功率的平均值为阈值，选择一个或一组认知用户作为中继节点转发主用户信号，认知用户根据提供的转发功率来获取相应的时间激励，根据激励在授权频谱上完成自身信号传输。通过实验对比不同情形下的系统性能，表明所提算法的用户效益更高，传输速率更好。

Cognitive radio is an important technical means to alleviate the current uneven spectrum allocation and underutilization, mainly through sensing the spectrum usage in the wireless communication environment and accessing the idle spectrum for communication, so as to improve the spectrum utilization rate. In cognitive radio systems, reliable spectrum sensing is the prerequisite for spectrum management, and reasonable spectrum sharing technology can enable cognitive users to access the idle spectrum without affecting the communication of the primary user, and ensure the transmission quality of users.

In view of the problem that single-node signal perception is susceptible to path loss, shadow effect and multipath fading, An improved spectrum sensing algorithm based on power spectrum is proposed. The algorithm makes use of the characteristic that the orthogonal basis of power spectral density is not easily changed by other interference, and solves the eigenvector cannot point to the direction of the primary user signal precisely because of the influence of noise. Firstly, the autocorrelation function of the signal after orthogonal expansion is obtained, and the power spectrum of the signal is further obtained by Fourier transform, and the ratio of the difference between the extreme value of the power spectrum and the geometric average of the power spectrum is used as a statistic. Then deduce the detection probability and false alarm probability of the algorithm, which proves that the performance of the algorithm is not affected by noise power. Experimental results show that the improved algorithm has higher detection probability under the same false alarm probability or signal-to-noise ratio, which verifies the effectiveness of the algorithm.

Based on reliable spectrum sensing results, a partial-user cooperative spectrum sharing algorithm based on contract theory is proposed. The algorithm mainly solves the contract design problem of wireless communication system in different information scenarios and secondary user selection problem under limited budget. The algorithm takes the average of the power provided by multiple secondary users as the threshold, selects one or a group of secondary users as the relay node to forward the signal of the primary user, and the secondary users obtain the corresponding time excitation according to the provided forwarding power, and complete the signal transmission on the authorized spectrum according to the excitation. By comparing the system performance under different conditions, it shows that the algorithm has higher user benefit and better transmission rate.

[1]王超,陈少刚,武明川.认知无线电下的频谱管理建议[J].中国科技信息,2014(22):202-203.

[2]徐达,徐湘莹,王世祺.频谱感知技术在无线电中运用的探讨[J].中国信息化,2021(11):56-57.

[3]杨春,潘兆平.认知无线电技术在电磁频谱管理中的应用探讨[J].电子制作,2018(22):62-63+61.

[4]赵永基.基于无线电监测技术的认知无线电频谱监测研究[J].信息记录材料,2021,22(03):126-127

[5]张俊强.浅析认知无线电的频谱感知技术[J].现代信息科技,2018,2(05):64-65+67.

[6]T. Yucek and H. Arslan, "A survey of spectrum sensing algorithms for cognitive radio applications," in IEEE Communications Surveys & Tutorials, 2009,11(01):116-130.

[7]Cabric D, Mishra S M, Willkomm D, et al. A cognitive radio for usage of virtual unlicensed spectrum[C]//14th IST mobile and communications summit, 2005:285-286.

[8]Leaves P, Moessner K, Tafazolli R, et al. Dynamic spectrum allocation in compositereconfigurable wireless networks[J]. IEEE Communications Magazine, 2004, 42(5):72-81.

[9]Cordeiro C . IEEE 802.22: the first worldwide wireless standard based on cognitive radios[C]//First IEEE international symposium on new frontiers in dynamic spectrum access network, 2005:328-337.

[10]Zheng H . Distributed spectrum allocation via local bargaining[C]//Sensor and Ad Hoc Communications and Networks, 2005 Second Annual IEEE Communications Society Conference on. IEEE, 2005.

[11]D.Damodaram. MIMO Based Cooperative Communication and Joint Maximum-Likelihood Detection for Cognitive Radio System[J]. International Journal of Recent Technology and Engineering (IJRTE),2021,10(1):

[12]Reznik A, S Verdú. On the Transport Capacity of a Broadcast Gaussian Channel[J]. Communications in Information and Systems, 2002, 2(2):183-216.

[13]Laneman J N, Wornell G W. Distributed space-time-coded protocols for exploiting cooperative diversity in wireless networks[J]. IEEE Transactions on InformationTheory, 2003, 49(10):2415-2425.

[14]Alias D M. Cognitive radio networks: A survey[C]//Wireless Communications, Signal Processing and Networking (WiSPNET), International Conference on. IEEE, 2016: 1981-1986.

[15]Upadhyay S, Deshmukh S. Blind parameterestimation based matched filter detection for cognitive radio networks[C]//2015 International Conference on Communications and Signal Processing (ICCSP)，2015:904-908.

[16]Rani R, Kumar K, Kumar R, et al. Evaluation of spectrum sensing process through energy detection technique[C]// 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN).2017:348-351.

[17]Ilyas I, Paul S, Rahman A, et al. Comparative evaluation of cyclostationary detection based cognitive spectrum sensing[C]// 2016 IEEE 7th Annual UbiquitousComputing, Electronics & Mobile Communication Conference (UEMCON). IEEE, 2016:1-7.

[18]Ganesan G, Li Y. Cooperative spectrum sensing in cognitive radio networks[C]// IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks. IEEE, 2005.

[19]姜赖赢. 认知无线电中协作频谱感知算法的研究[D].重庆邮电大学,2017.

[20]Weiss T, Hillenbrand J, Krohn A, et al. Efficient signaling of spectral resources in pooling systems[J]. Symposium on Communications&Vehicular Technology 2003:1-11.

[21]Guo C, Zhang T, Zeng Z, et al. Investigation on spectrum sharing technology based on cognitive radio[C]//2006 First International Conference on Communications and Networking in China. IEEE, 2006: 1-5.

[22]Prieto G, Andrade Á G, Martínez D M, et al. On the evaluation of an entropy-based spectrum sensing strategy applied to cognitive radio networks[J]. IEEE Access, 2018, 6: 64828-64835.

[23]李一兵，常国彬，叶方.基于指数熵的认知无线电频谱感知算法[J].吉林大学学报，2013:1506-1511.

[24]Wang Y, Zhang Z, Li H . Universal Quickest Sensing of Spectrum Change in Millimeter Wave Communications: A Data Driven Approach[C]// GLOBECOM 2017 - 2017 IEEE Global Communications Conference. IEEE, 2017: 1-6.

[25]弥寅，卢光跃，关璐.特征值类频谱感知算法的仿真分析[J].西安邮电大学学报，2014, (5):27-33.

[26]刘宁，史浩山，杨博等.基于最大特征值和能量之差的频谱感知方法[J].测控技术，2016,35(06):125-128.

[27]Yang X, Lei K, Peng S, et al. Blind Detection for Primary User Based on the Sample Covariance Matrix in Cognitive Radio[J]. IEEE Communications Letters, 2013, 15(1):40-42.

[28]Charan C, Pandey R. A reliable spectrum sensing scheme using sample covariance matrix for cognitive radio[C]//2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT). IEEE, 2016: 17-20.

[29]赵知劲,胡伟康,王海泉.基于双特征值极限分布的合作频谱感知算法[J].电信科学,2014,30(04):82-87.

[30]Wael C B A, Armi N, Rohman B P A. Spectrum sensing for low SNR environment using maximum-minimum eigenvalue (MME) detection[C]//2016 International Seminar on Intelligent Technology and Its Applications (ISITIA). IEEE, 2016: 435-438.

[31]徐家品,杨智.基于随机矩阵特征值比的频谱感知改进算法[J].电波科学学报,2015,30(02):282-288.

[32]卢光跃,叶迎晖,孙宇,弥寅.克服噪声不确定度的拟合优度检验频谱感知算法[J].电讯技术,2016,56(01):26-31.

[33]叶迎晖,卢光跃.采用相关系数和拟合优度的频谱盲检测[J].信号处理,2016,32(11):1363-1368.

[34]钟强,梁俊杰,胡宗进,秦绪栋.基于拟合优度检验的认知无线电频谱检测技术[J].电声技术,2016,40(08):44-46.

[35]岳文静,瞿耀庭,陈志.基于信号能量分布拟合优度的长短时记忆网络频谱感知算法研究[J].信号处理,2020,36(07):1065-1074.

[36]齐佩汉,司江勃,李赞,高锐.基于功率谱分段对消频谱感知算法研究及性能分析[J].电子与信息学报,2014,36(04):769-774.

[37]孙哲,特征值频谱感知算法的研究及改进[D].西安电子科技大学,2014

[38]吕曦,认知无线电中频谱感知算法的研究[D].杭州电子科技大学,2017.

[39]毛翊君,赵知劲,吕曦.利用功率谱最大最小平均比的频谱感知算法[J].信号处理,2018,34(04):409-416.

[40]Goldsmith A, Jafar S A, Maric I, et al. Breaking spectrum gridlock with cognitive radios: An information theoretic perspective[J]. Proceedings of the IEEE, 2009, 97(5): 894-914.

[41]Zhao H, Tan Y, Pan G, et al. Secrecy Outage on Transmit Antenna Selection/MaximalRatio Combining in MIMO Cognitive Radio Networks[J]. IEEE Transactions on Vehicular Technology, 2016, 65(12):10236-10242.

[42]Hamza D, Aïssa S, Aniba G. Equal gain combining for cooperative spectrum sensing in cognitive radio networks[J]. IEEE Transactions on wireless communications, 2014, 13(8): 4334-4345.

[43]Talwar S, Jing Y, Shanbazpanahi S. Joint Relay Selection and Power Allocation for Two-Way Relay Networks[J]. IEEE Signal Processing Letters, 2011, 18(2):91-94.

[44]Wang X, Zhang H, Fan L, et al. Performance of Distributed Switch-and-Stay Combining for Cognitive Relay Networks with Primary Transceiver[J]. Wireless Personal Communications,2017, 35(5):1-12.

[45]Zhai T, Liu D D, Liu X Y, et al. Optimal Energy Efficient Strategy for Cooperative Spectrum Sharing Networks[C]// International Conference on Information and Communications Technologies. 2014: 1-5.

[46]Sharma P K and Upadhyay P K. Performance of Two-Way Overlay Spectrum Sharing Systems in the Presence of Co-Channel Interference[C]// IEEE Wireless Communications and Networking Conference (WCNC), Doha, Qatar, 2016: 1-6.

[47]Su W, Matyjas J D, Batalama S. Active cooperation between primary users and cognitive radio users in heterogeneous ad-hoc networks[J]. IEEE Transactions on Signal Processing, 2012, 60(4): 1796-1805.

[48]Wang M Y, Lu W D, He D, et al. An Anti-Interference Spectrum Sharing Protocol with Secondary User Selection[C]// 10th International Conference on Communications and Networking in China (ChinaCom), Shanghai, P. R. China, 2015:661-665.

[49]Lu W, He C, Wu J, et al. Anti-interference cooperative spectrum sharing based on fairness secondary user selection[C]//2016 International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, 2016: 942-947.

[50]Manna R F, Al-Qahtani F S, Zummo S A. A full diversity cooperative spectrum sharing scheme for cognitive radio networks[J]. IEEE Access, 2017, 5: 17722-17732.

[51]Ustunbas S, Basar E, Aygolu U. Performance analysis of cooperative spectrum sharing for cognitive radio networks using spatial modulation at secondary users[C]//2016 IEEE 83rd Vehicular technology conference (VTC Spring). IEEE, 2016: 1-5.

[52]Sharma P K, Upadhyay P K. Performance analysis of cooperative spectrum sharing with multiuser two-way relaying over fading channels[J]. IEEE Transactions on Vehicular Technology, 2016, 66(2): 1324-1333.

[53]赵庆平，陈得宝，姜恩华，李素文.MIMO认知无线电系统中协作频谱共享方案[Jl.计算机应用研究.2014, 31(6): 1775-1778.

[54]Tang J, Bournaka G, Lambotharan S. Sum rate maximization for spectrum sharing multiuser MIMO network under Rayleigh fading[C]//2012 IEEE International Conference on Communication, Networks and Satellite (ComNetSat). IEEE, 2012: 30-34.

[55]Deng J H, Chen S H, Ku M L. Multiuser MIMO precoders with proactive primary interference cancelation and link quality enhancement for cognitive radio relay systems[J]. IEEE Access, 2017, 5: 17701-17712.

[56]Nguyen V D, Tran L N, Duong T Q, et al. An efficient precoder design for multiuser MIMO cognitive radio networks with interference constraints[J]. IEEE Transactions on Vehicular Technology, 2016, 66(5): 3991-4004.

[57]何晨昕. 基于契约理论的无线频谱共享方法研究[D].浙江工业大学,2018