Joint optimization approach for improving spectrum utilization in CRN with perfect and imperfect sensing

Abstract

With the extensive use of intelligent wireless applications, the spectrum allocation strategies and quality of service provided in the 5G era cannot support the growing demand. In this regard, cognitive radio has been incorporated into 6G networks as an intelligent wireless paradigm for solving the spectrum underutilization problem by opportunistically giving dynamic spectrum access to utilize the licensed band. From an implementation perspective, better utilization of available spectrum holes requires fast and reliable spectrum sensing techniques. The spectrum sensing performance in cognitive radio depends on selecting an appropriate decision threshold and sensing duration. However, selecting a decision threshold is a critical factor, and it is observed that a fixed decision threshold approach employs poor detection performance and takes a longer sensing duration. Based on the above shortcomings, a dynamic decision threshold-based energy detection approach is proposed to improve the detection performance and sensing ability even in low SNR regions. Moreover, a PU’s state transition model with SU’s possible data transmission cases is investigated and further analyzed through perfect and imperfect sensing scenarios for effective spectrum utilization. Two critical parameters, decision threshold and sensing duration, are jointly optimized to maximize spectrum utilization efficiency. Simulation results demonstrate that the proposed approach has achieved better spectrum utilization efficiency, up to 24% over existing approaches.