Optimal resource allocation strategies for cognitive femtocell networks with efficient access and backhaul management

Abstract

Recent days have witnessed an unprecedent growth in wireless newlineservices because of the increase of billions of users, users, and connections newlinehave necessitated the transition from 4G to high performing 5G cellular newlinenetworks. Exploring and leveraging the enormous pieces of Wave spectrum newlinewith the frequency range of 30 GHz and 300 GHz have greater potential to newlinerender gigabit rate services to the devices which is the futuristic to alleviate newlinethe current spectral scarcity crisis. It is well known fact that development of a newlinenew exclusive spectrum to combat the resource demands is highly newlinechallenging. The introduction of cognitive radio technology to provide mobile newlineservices to the users through Femtocells, that are layered on the top of the newlineexisting macrocell network augmented with spectrums sharing is unleased as newlinea solution to serve more devices. However, this concurrent reuse of spectral newlineresources by the FC from Femto networks creates a destructive interference newlineon the existing macro networks, which deteriorates the network QoS. Also, newlinethe power of backhaul network which connects the core network with the newlinefronthaul is left unexplored. newlineThis research work proposed a novel yet optimal channel newlineallocation model that integrates the prowess of the Opposition Based newlineLearning (OBL) to develop an Oppositional Beetle Swarm Optimization newlineAlgorithm (OBSOA) to efficiently allocate the channels to the requesting newlinenodes without interference. The selection of optimal channels is done from newlinethe generated oppositional as well as normal candidates. newline