Cooperative Cognitive Radio for Wireless Opportunistic Networks

With the advent of smarter technologies in cellular networks, often the bands used for lower versions remain unoccupied. To utilize that, in this work, a new paradigm of cognitive radio has been proposed, where the nodes of a self-organized opportunistic ad hoc network act as the secondary users (SU) to use the white spaces of the existing cellular network. Each SU can freely move around, and in a self-organized fashion may collaborate with other neighboring SUs to gather information of the channels of the primary network for cognitive use of the licensed spectrum. The proposed distributed techniques of collaboration among SU's for channel allocation, eliminate the necessity of any centralized control, and at the same time improve the channel utilization and throughput. To improve the spectrum latency, we further apply reinforcement learning technique for better channel estimation. Simulation studies show that our proposed approaches significantly improve the call drop/block rate, and also result better QoS compared to the other existing approaches, at the cost of negligible additional message overhead.