Weighted soft decision for cooperative sensing in cognitive radio networks

Enhancing the current services or deploying new services operating in RF spectrum requires more licensed spectrum which may not be provided by the regulatory bodies because of spectrum scarcity. On the contrary, recent studies suggest that many portions of the licensed spectrum remains unused or underused for significant period of time raising the issue of spectrum access without license in an opportunistic manner. Among all the spectrum accessing techniques, sensing based methods are considered optimal for their simplicity and cost effectiveness. In this paper, we introduce a new cooperative spectrum sensing technique which considers the spatial variation of secondary (unlicensed) users and each user's contribution is weighted by a factor that depends on received power and path loss. Compared to existing techniques, the proposed one increases the sensing ability and spectrum utilization, and offers greater robustness to noise uncertainty. Moreover, this cooperative technique uses very simple energy detector as its building block thereby reduces the cost and operational complexity

A Weighted Linear Combining Scheme for Cooperative Spectrum Sensing

AbstractCooperative spectrum sensing exploits spatial diversity of secondary-users (SUs), to reliably detect the availability of a spectrum. Soft energy combining schemes have optimal detection performance at the cost of high cooperation overhead, since actual sensed data is required at the fusion center. To reduce cooperation overhead, in hard combining only local decisions are shared; however the detection performance is suboptimal due to the loss of information. In this paper, a weighted linear combining scheme is proposed in which a SU performs a local sensing test based on two threshold levels. If local test result lies between the two thresholds then the SU report neither its local decision nor sequentially estimated unknown SNR parameter values, to the fusion center. Thereby, uncertain decisions about the presence/absence of the primary-user signal are suppressed. Simulation results suggest that the detection performance of the proposed scheme is close to optimal soft combining schemes yet its overhead is similar to hard combining techniques