Improved Channel Occupancy Rate Estimation

Channel occupancy rate (COR) is the fraction of the time that a channel is occupied, i.e., contains signal(s) in addition to noise. Estimation of COR is important, e.g., in cognitive radio systems, which can use this information for intelligently adapting their spectrum use to the operating environment. For COR estimation, both the ability to operate with weak signals (sensitivity) and closeness of the estimate to the true COR value (accuracy) are important. In this paper, an improved COR estimation (iCOR) method is proposed enabling the use of high false alarm probabilities to improve sensitivity without the overestimation usually associated with high false alarm probabilities. The iCOR method is compared with the conventional method in terms of worst-case root-mean-square error (RMSE), which refers to the RMSE for the COR level yielding the maximum RMSE. To fairly compare different COR estimation methods, it is required that the RMSE for strong signals equals a target value and the considered methods are compared by their RMSE for weaker signals. Comprehensive theoretical analysis is performed and both exact results and approximations are derived. Experimental results verify the theoretical analysis and show significant sensitivity gains from the iCOR method (around 5 dB).