Probabilistic and partial edge caching based cooperative spectrum sharing in large-scale cognitive radio networks

In this work, we propose a cooperative spectrum sharing scheme based on probabilistic and partial edge caching in cognitive radio networks. The primary system contains primary users (PUs) and base stations (BSs), and the secondary system contains secondary transmitters (STs), secondary receivers (SRs), and secondary helpers (SHs). Each PU is associated with the nearest BS and owns the licensed spectrum. SHs cache the required files of PUs with certain probabilities and ratios, and actively assist the transmission to PUs in exchange for spectrum resources for SUs. In each cell, an SH adaptively cooperates with BS to transfer the requested file contents to the PU; thereby, the communication performance of the primary system can be more easily satisfied. As a reward, spectrum can be released to the secondary system in frequency and time domains. An optimization problem is formulated to maximize the area throughput of the secondary system while satisfying the performance requirement of the primary system. An algorithm is proposed to jointly determine file caching probabilities and ratios, and spectrum sharing time and bandwidth. Numerical results show that, compared with the most popular and uniform content placement schemes, our proposed scheme can greatly improve the system area throughput.