Research On Adaptive Resource Allocation Algorithm For Ofdma Systems

The next-generation of wireless communication systems need to support high data rate wireless multimedia services. Due to the scarcity of radio resource, It is the key research point in the field of mobile communications that how to use the radio resource efficiently. Currently, researches of radio resource management have mainly focus on three aspects, namely, resource control, resource allocation and resource scheduling. This paper aims at the problem of resource allocation and intending to increase the system performance through improving the algorithm of resource allocation in the orthogonal frequency division multiple access (OFDMA) systems. In the next-generation wireless communication systems, the consumption of energy is increasing with the increment of traffic, so it is important to improve the efficiency of the systems and decrease the overall energy consumption for green operation. This paper attempts to maximize the energy efficiency via executing adaptive resource allocation algorithm.The current research works in adaptive resource allocation of OFDMA systems usually adopt optimal algorithm with high complexity. This paper proposes a low complexity sub-optimal algorithm which allocates the sub-carrier and bit simultaneously, and formulates the optimal goal as to minimize the overall transmit power. The proposed algorithm has no limit for the number of sub-carriers and the sub-carrier set of every user. Firstly, we introduce the minimum data rate requirement as the user demand factor. The bigger the user demand factor is, the larger the requirement degree of user for sub-carrier and bit is. We allocate one sub-carrier and one bit to each user according to the user demand factor. Then, we use the ratio of the minimum data rate requirement and the instant rate as the user demand factor. Similarly, the bigger the user demand factor is, the larger the requirement degree of user for sub-carrier and bit is. We allocate the sub-carriers and bits to users according the sequence of user demand factor, until the minimum data rate requirements of all users are satisfied or all sub-carrier and bits are exhausted. Note that the user demand factor is dynamic during the process of allocation. We compare the performance of the proposed algorithm with BABS-RCG algorithm and BABS-ACG algorithm by matlab simulation. Simulation results indicate that the system power and the computational complexity of the proposed algorithm are significantly improved.In addition, this paper addresses the adaptive resource allocation problem based on optimization of energy efficiency. We introduce the idea of sub-carrier allocation firstly and bit allocation secondly to maximize the energy efficiency. Since the problem of adaptive bit-power allocation with the goal of energy efficiency optimization is a nonlinear problem, it is impossible to solve the problem by ordinal iterative addition among users. This paper uses the Particle Swarm Optimization (PSO) to solve the adaptive bit-power allocation problem. We adopt the bit allocation scheme of multi-user as particle, and evaluate the fitness degree of every particle by computing the energy efficiency of system. In order to obtain optimal bit allocation scheme, we execute continuous iteration. We compare the performance of the proposed algorithm with Genetic Algorithm (GA) by matlab simulation. Simulation results show that both the seeking optimization ability and the convergence performance of PSO are better than GA. Furthermore, it will reach the optimization point of energy efficiency only when the data rate requirements of each user are just meet.