An LLR based cooperative spectrum sensing with hard-soft combining for cognitive radio networks
Seemanti Saha, Abhishek Kumar, Priyanka Priyanka, Rajarishi Bhattacharya · 2017
In cognitive radio networks, cooperative spectrum sensing schemes improve the reliability of the detection by exploiting decisions made locally by several secondary users (SUs). Soft energy combining schemes provide optimal detection performance by combining the actual sensed information from the SUs, resulting in high cooperation overhead in terms of time, computational complexity, and bandwidth. Alternatively, hard energy combining schemes offer lower cooperation overhead, but provides sub-optimal detection performance. In this paper, a log-likelihood ratio (LLR) based cooperative spectrum sensing scheme with hard-soft combining at fusion centre (FC)is proposed, where the SUs perform a local LLR based detection employing two thresholds. If the locally sensed informations falls in between the two threshold values, then the actual sensed information is reported to the FC and weighted soft combining is performed at FC, else the local binary decisions are reported to FC and hard combining is performed. Further, a second stage hard combining employing AND/OR rule is performed at FC considering the previous decisions. The performance evaluation through simulation shows that the proposed scheme gives the near optimal performance with a slight increase in cooperation overhead.