M. Shamim Kaiser

Relay Selection & Resource Allocation in Cognitive Cooperative Network: a Neuro-fuzzy Based Approach M. Shamim Kaiser

Cooperative relaying in a cognitive radio network (CRN) has been used to achieve diversity gain and energy efficiency through the relay node. This dissertation investigates the Neuro-Fuzzy (NF) based relay selection, fair resource allocation for cooperative relay network. The main idea is to increase the data transmission rate and spectrum utilization efficiency while decreasing the outage probability and complexity of the system. The outage probability and BER expressions have been derived. Simulation results depict close consensus between analytical results and simulations. NF selection algorithm provides better performance improvement over conventional algorithms. The complexity analysis shows that the proposed algorithm requires less time to select the best relay. We also investigate opportunistic spectrum access and spectrum hand-off (HO) for RCRN using intelligent NF based approach. The main aim is to increase the average throughput of the RCRN while reducing the number of HO decisions. Performance evaluations also reveal that the outage probability is reduced and the system's capacity is increased.