Bio-Inspired AI Optimization Techniques to Evaluate Data Rate and Minimize Interference in Cognitive Cellular Network

摘要

The concept of Cognitive Cellular Network (CCN) resolves spectrum availability crises arising from increasing demand of data rate, which is restricted in cellular network. The traffic demand is growing extensively consequently allocating the channels optimally in CCN is the purpose of this work. The CCN accommodate cellular (primary) and cognitive (secondary) users. The cognitive users occupy the cellular band avoiding interference among them. The AI-heuristic techniques Bee colony Optimization (BCO) and Teaching learning based optimization (TLBO) is applied to find optimal solution to channel allocation in CCN. The data rate is evaluated after discovering the interference associated, to cope-up with network capacity. The obtained solution is found to be better than reported work.