基于极大似然比频谱检测的认知无线电子载波分配算法

在认知无线电多载波调制系统中,子载波分配是实现主用户与认知用户频谱共享的前提.研究了认知OFDM中基于极大似然比检测(MLD)的子载波分配算法,认知用户采用MLD模型对主用户频谱使用情况进行分布式检测,利用频谱检测信息动态分配子载波,通过认知基站对认知用户子载波频谱感知信息进行融合判决.推导了MLD模型的判决区域上下界阈值、检测概率与虚警概率,并与能量检测进行性能比较.仿真结果表明,相对于能量检测,MLD判决阈值与子载波平均接收信噪比(SNR)有关,检测性能自适应信道变化.MLD用于CR多载波调制中的子载波分配,可明显提高认知OFDM子载波频谱感知性能,从而达到高效利用频谱资源,实现"绿色通信".

Sub-carrier allocation algorithm based on maximum likelihood ratio spectrum detection in cognitive radio

In cognitive radio (CR) systems with multi-carrier modulation, sub-carrier allocation is the premise for the realization of spectrum sharing for Primary Users (Pus) and Secondary Users (Sus). A sub-carrier allocation algorithm based on maximum likelihood ratio detection (MLD) in cognitive OFDM is introduced and studied. Sus detect the occurrence and spectrum gap of PU signals with MLD model in a distributive way, while the system allocates sub-carriers to Sus dynamically. Cognitive base station (CBS) makes the final decision by combining each sub-carrier's local sensing result with special fusion rule. The upper and lower bound of the decision region, detection probability and false alarm probability of the MLD model are derived, and a performance comparison between MLD and energy detection (ED) is presented. Simulation results indicate that, compared with ED, the decision threshold of MLD is related to the average received SNR at the sub-carrier, and that the detection performance adapts to channel variation. Therefore, applied to sub-carrier allocation in CR multi-carrier modulation, MLD can enhance the cognitive OFDM sub-carrier spectrum sensing performance significantly and realize the utilization of limited spectrum resource efficiently, thus, meeting the requirements of "green communication" could be achieved effectively.