Cognitive radio testbed: further details and testing of a distributed genetic algorithm based cognitive engine for programmable radios

This paper provides details of a distributed genetic algorithm (GA) based cognitive radio engine model for disaster communications and its implementation in a cognitive radio test bed using programmable radios. Future applications include tactical and covert communications. The cognitive system monitor (CSM) module presented here permits cross layer cognition and adaptation of a programmable radio by classifying the observed channel, matching channel behavior with operational goals, and passing these goals to a wireless system genetic algorithm (WSGA) adaptive controller module to evolve and optimize radio operation. The CSM module algorithm provides for parallel distributed operation and includes a learning classifier and meta-GA functions that work from a knowledge base (which may be distributed) in long term memory to synthesize matched channels and operational goals that are retained in short term memory. Experimental results show that the cognitive engine finds the best tradeoff between a host radio's operational parameters in changing wireless conditions, while the baseline adaptive controller only increases or decreases its data rate based on a threshold, often wasting usable bandwidth or excess power when it is not needed due its inability to learn.