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认知无线电系统中的多中继分布式波束成形方法
引用本文:王群欢,;王慧明,;殷勤业.认知无线电系统中的多中继分布式波束成形方法[J].中国科学:信息科学,2014(8):980-992.
作者姓名:王群欢  ;王慧明  ;殷勤业
作者单位:[1]西安交通大学电子与信息工程学院,西安710049; [2]东南大学移动通信国家重点实验室,南京210096; [3]智能网络与网络安全教育部重点实验室,西安710049
基金项目:国家自然科学基金(批准号:61102081,61071216)、教育部博士点基金(批准号:20110201120013)、教育部新世纪优秀人才支持计划(批准号:NCET-13-0458)、陕西省工业攻关项目(批准号:2012GY2-28)、东南大学移动通信国家重点实验室开放研宄基金(批准号:2012D09)和中央高校基本科研业务费(批准号:2013jdgz11)资助项目
摘    要:本文考虑认知无线电系统中一对认知源目的节点在一组认知中继节点协助下与一对授权发射机和接收机共存的场景,研究了多个单天线认知中继节点在授权接收机处平均干扰功率门限约束及自身独立的平均发射功率约束下,最大化认知目的节点处信干噪比(SINR)的分布式波束成形,从而开发"空谱空洞"的问题.提出了两种波束成形方案:1)最大化SINR的最优策略;2)基于迫零准则的次优策略.最优策略将分布式的波束成形系数求解问题通过半定松弛转化为准凸的优化问题,从而利用二分法及内点法求解;并证明了求得的最优半定松弛解即为原优化问题的最优解.次优策略直接迫零对授权接收机造成干扰,并将来自授权发射机的干扰信号抑制为零.该方法对应的优化问题没有迭代运算,且约束函数简单,算法复杂度低.最后通过数值仿真分析了中继数、认知节点最大的发射功率和授权接收机的干扰功率门限等因素对两类算法平均传输速率的影响,并且通过对比实验验证了考虑授权发射机干扰信号影响带来的性能增益.

关 键 词:认知无线电  空谱空洞  协作通信  分布式波束成形  凸优化  半正定松弛  迫零

Distributed beamforming for multi-relay cognitive radio systems
Institution:WANG QunHuan WANG HuiMing& YIN QinYe( School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China; 2 National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China; 3 Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an 710049, China)
Abstract:In this paper, the cognitive scenario where a source-destination pair of secondary users coexists with a licensed transmitter-receiver pair with the help of a group of cognitive relay nodes is considered. To exploit the "spatial spectrum holes", we study the distributed beamforming of multiple cognitive relay nodes each equipped with a single antenna for the maximization of signal-to-interference-plus-noise ratio (SINR) at the cognitive destination, while keeping the interference power at the licenced receiver below a certain threshold and satisfying the individual power constraint. Two beamforming schemes are proposed: 1) the optimal scheme maximizing SINR; and 2) a suboptimal zero-forcing scheme. The optimal beamforming problem can be reformulated as a quasi-convex optimization problem using semidefinite relaxation (SDR), then the bisection and interior point methods can be used to solve this problem. It can also be proved that SDR yields the optimal solution to the original problem. The suboptimal zero-forcing scheme eliminates the interference at the licensed receiver as well as the signals from the licensed transmitter. It has a low complexity without iterations and simple constraint functions. Numerical results are presented to show the impacts of the number of relay nodes, the maximum transmit power of cognitive nodes, and the threshold of power of interferences at the licenced receiver to the average achievable rates of the two schemes. Furthermore, the performance will be improved if the impact of signals from licenced transmitter is taken into account, which is verified through simulation experiments.
Keywords:cognitive radio  spatial spectrum holes  cooperative communication  distributed beamforming  convex optimization  semi-definite relaxation  zero-forcing
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