认知无线电网络中基于最大似然准则的协同频谱检测算法研究

Cooperative Spectrum Sensing in Cognitive Radio Networks Based on Maximum Likelihood Criterion

提出一种集中式频谱协同检测算法。各认知节点采用能量检测算法,然后使用最大似然准则进行本地判决,且把似然比作为本地判决可靠性的度量;中心节点基于可信度对接收到的认知节点本地检测数据进行数据融合。仿真结果显示,文中提出的认知节点协同频谱检测方案能够减少误检概率。特别是当信道处于深衰落时,少量节点参与协同就能获得较好的检测性能。

This paper proposes a new centralized cooperative spectrum sensing method, in which energy detection is used for local spectrum sensing, and make a local decision based on maximum likelihood criterion, and uses the likelihood ratio as a measure of the reliability of the local decision. The fusion center makes data fusion based on the reliability of local decisions. Simulation results show that the proposed sensing scheme can reduce the error probability of spectrum sensing. Especially when the channel is in deep fading, a small number of cognitive users participating in a cooperative spectrum sensing will be able to obtain better performance.