A considerable work has been conducted to cope with orthogonal frequency division multiple access (OFDMA) resource allocation with using different algorithms and methods. However, most of the available studies deal with optimizing the system for one or two parameters with simple practical condition/constraints. This paper presents analyses and simulation of dynamic OFDMA resource allocation implementation with Modified Multi-Dimension Genetic Algorithm (MDGA) which is an extension for the standard algorithm. MDGA models the resource allocation problem to find the optimal or near optimal solution for both subcarrier and power allocation for OFDMA. It takes into account the power and subcarrier constrains, channel and noise distributions, distance between user's equipment (UE) and base stations (BS), user priority weight – to approximate the most effective parameters that encounter in OFDMA systems. In the same time multi dimension genetic algorithm is used to allow exploring the solution space of resource allocation problem effectively with its different evolutionary operators: multi dimension crossover, multi dimension mutation. Four important cases are addressed and analyzed for resource allocation of OFDMA system under specific operation scenarios to meet the standard specifications for different advanced communication systems. The obtained results demonstrate that MDGA is an effective algorithm in finding the optimal or near optimal solution for both of subcarrier and power allocation of OFDMA resource allocation.
The necessity for an efficient algorithm for resource allocation is highly urgent because of increased demand for utilizing the available spectrum of the wireless communication systems. This paper proposes an Enhanced Bundle-based Particle Collision Algorithm (EB-PCA) to get the optimal or near optimal values. It applied to the Orthogonal Frequency Division Multiple Access (OFDMA) to evaluate allocations for the power and subcarrier. The analyses take into consideration the power, subcarrier allocations constrain, channel and noise distributions, as well as the distance between user's equipment and the base station. Four main cases are simulated and analyzed under specific operation scenarios to meet the standard specifications of different advanced communication systems. The sum rate results are compared to that achieved with employing another exist algorithm, Bat Pack Algorithm (BPA). The achieved results show that the proposed EB-PAC for OFDMA system is an efficient algorithm in terms of estimating the optimal or near optimal values for both subcarrier and power allocation.