Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks

Dipak P Patil,Vijay M Wadhai,Vishal A Wankhede

doi:10.4236/wet.2015.64009

Dipak P Patil, Vijay M Wadhai + Show 1 more

Open Access

https://doi.org/10.4236/wet.2015.64009

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Abstract

In this paper, an adaptive subcarrier allocation scheme with reconfiguration of operating parameters for Cognitive Radio Networks (CRN) is presented. A QoS-conscious spectrum decision frame work is projected, where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. The novel subcarrier allocation algorithm is developed to fulfill different performance objective as a solution for subcarrier allocation and power allocation problem for Cognitive Radio (CR) users in CRNs. It employs operating frequency parameter modification using Proportional Resource Algorithm and Genetic Algorithm (GA). The multi objective optimization problem with equality and inequality constraint is considered. Moreover, a dynamic subcarrier allocations scheme is developed based on GA to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. The proposed algorithm targets to achieve maximum data rate for each subcarrier, maximize the overall network throughput and maximize the number of satisfied user under the constraints of bandwidth and guarantee Quality of Service (QoS) requirement from dynamic spectrum management (DSM) perspective. Moreover, it determines the best available channel.

Highlights

The wireless frequency spectrum has been materialized as one of the most challenged civic goods in recent years
The Genetic Algorithm (GA) parameter settings considered for implementation is as data rate (DR) set to value of 265 kbps, PWR is 15 dBm and bit error rate (BER) is 10−5
The proposed scheme addresses the major functions for Cognitive Radio (CR) user from spectrum decision perspective in Cognitive Radio Networks (CRN)

Summary

Introduction

The wireless frequency spectrum has been materialized as one of the most challenged civic goods in recent years. It uses the methodology from the environment and adjusts its internal states to statistical variations in the incoming RF stimuli by making analogous changes in operating parameters, avoiding interference with licensed or unlicensed users These capabilities can be realized by dynamic spectrum management functionalities. In [8], the authors proposed a combined strategy to allocate channels and power with the QoSsupported objective to get maximum data rate to each user in cognitive networks, but this algorithm has high complexity To deal with such disruptive scenarios, a new model is presented in [9] [10]. Numerous channel selection methods using the adjustment of operating parameters like power, bit error rate (BER), bandwidth (BW) as the basic genes In these schemes, the objective function meets to the optimal value and termination condition is achieved based on the desired criteria.

Problem Formulation

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Conclusion