Optimal power allocation technique using genetic algorithm for maximization of Ergodic capacity under different fading channel approaches in Cognitive Radio Network

The main challenges in any wireless communication system is how to increase the Ergodic capacity in fading environments. Trying to solve this problem in Underlay Cognitive Radio Networks (UCRN). In this paper, proposed technique will be suggested under using genetic algorithm for optimization of power allocation strategies to enhance power performance and maximize the Ergodic capacity. This technique studies how to maximize Secondary User (SU) Ergodic capacity considering some constraints such as maximum transmit power of SU, interference threshold at Primary User (PU) and interference on SU. Moreover, this proposed technique investigates the Ergodic capacity gains offered under using different fading models and Additive White Gaussian Noise (AWGN). Further, SU Ergodic capacity under different levels of PU transmit power will be studied. Also, comparisons between this proposed technique and other optimized power allocation technique will be discussed. Finally, SU Ergodic capacity under peak, average transmit and interference power constraints will be investigated.