Proficient Resource Allocation to Secondary User Using Nature Inspired Technique in Cognitive Radio Network

In this paper, a new resource allocation paradigm is designed whereby a new SU is allowed to gain access to the spectrum of licensed PU. Appropriate bandwidth and power are the resources allocated to the SU during the inactivity of PU if the interference is below the maximum allowable IT limit of the channel. An efficient algorithm is developed for reconfiguration of SU's parameters using nature inspired computational intelligence technique named ADALINE i.e. Adaptive Linear Neuron. A demand supply based feedback mechanism is proposed to meet the data rate requirements of new unlicensed user. A scenario is considered wherein a single SU transmitter is able to initially coexist with the PU and then, is able to adapt its transmission parameters (bandwidth and signal strength) dynamically as per spectral availability and the demand of its receiving unit. The feedback system developed reduces difference from allowable IT limit and difference from the achievable capacity during each iteration, rendering efficient channel utilization and achieves user's data rate satisfaction.