IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Special Issue: 15 | Dec-2014 | IWCPS-2014, Available @ http://www.ijret.org 14 RATE ADAPTIVE RESOURCE ALLOCATION IN OFDMA USING BEES ALGORITHM Archana C 1 , Rejith K.N 2 1 PG Scholar, ECE Department, MES College of Engineering, Kerala, India 2 Assoc. Professor, ECE Department, MES College of Engineering, Kerala, India Abstract Orthogonal Frequency Division Multiple Access (OFDMA) is the promising access technique for future networks which allows multiple users to transmit simultaneously. The problem of allocating resources (subcarriers, bit and power) among the communicating users in multiuser orthogonal frequency division multiplexing (OFDM) system is a constraint optimization problem. Bio-inspired Networking represents an emerging area to obtain optimal solutions for handling various challenges in the networking scenario. Nature is our mother and an inspiration from nature always gives the best. Bio-inspired algorithms are known for their efficiency in solving NP hard problems. This paper focusses on realizing the rate adaptive resource allocation problem in OFDM systems using bio-inspired approach. The resource allocation problem using Genetic Algorithm, algorithms based on foraging behavior in ants and flocking behavior in birds have already been modelled. The paper suggests the application of Bees Algorithm for resource allocation in OFDMA with the goal of maximizing the data rate of each user. Keywords: OFDMA, Bees Algorithm, Resource allocation, and PSO --------------------------------------------------------------------***---------------------------------------------------------------------- 1. INTRODUCTION Due to the fast development of digital signal processing and very large scale integrated circuits, wireless communication systems have been experiencing an explosive growth in the past decades. Next generation wireless networks are expected to handle large number of subscribers, while at the same time deal with the different service requirements of each user. Thus Orthogonal Frequency Division Multiple Access (OFDMA) forms the radio resource allocation scheme for the existing and envisioned networks to support the increasing number of users with the limited spectrum level. OFDMA allows several users to transmit simultaneously at lower data rates. The available spectrum band is divided into a number of sub-channels and each user is provided with a disjoint set of subcarriers. After the subcarrier allocation is determined, the bit and power allocation algorithm can be applied to each user on its allocated subcarriers. The user can transmit his data in the allocated subcarriers. A major challenge in OFDMA is that for a given number of users and subcarriers, how to allocate a disjoint set of subcarriers among the users. The classical approaches for the problem are complex and NP hard. Researchers have turned their attention towards applying the nature inspired computational approach for solving the challenges in networking scenario [1]. Bio-inspired approach implies transferring knowledge from the natural systems to the engineering system. The future networks ranging from nano- scale communication to Inter-planetary Internet are facing challenges in the communication and managing aspects. The inherent property of the biological organisms to self-organize, learn and evolve has inspired the researchers to address the significant issues in computer networking. Bio-inspired Algorithms that mimics the behavior of biological organisms have been used to optimize complex problems [2] [3]. This paper studies the effect of applying Bees Algorithm (BA) for rate adaptive resource allocation in an OFDMA system. The problem of resource allocation in OFDMA can be handled in two ways: Rate Adaptive (RA) method and Margin adaptive (MA) method. In rate adaptive method the resource allocation is optimized by maximizing the data rate of each user while keeping the power consumption of each user below an acceptable level. Margin adaptive method minimizes the maximum power consumption of each user maintaining a rate constraint. The use of Bees algorithm for RA based allocation strategy is studied in a single cell scenario. 2. RELATED WORKS Genetic algorithm (GA) was the first bio-inspired algorithm used to study the problem of resource allocation in OFDMA [4] [5]. But GA can give only sub-optimal results and includes iterative process. Ant Colony optimization (ACO) technique has been widely used to address the problem. In [6], ACO was applied for subcarrier and bit allocation for margin adaptive problem which provided better performance in terms of less transmit power consumption and faster convergence. ACO was compared with GA and other conventional algorithms for adaptive resource allocation in OFDMA [7]. But ACO requires more memory space for computation and a reduction in number of iterations are required.