Computationally Efficient Resource Allocation in OFDM Systems: Genetic Algorithm Approach

Authors:
Y. B. Reddy;N. Gajendar;Portia Taylor;Damian Madden
Affiliations:
Grambling State University, LA;Grambling State University, LA;Grambling State University, LA;Grambling State University, LA
Venue:
ITNG '07 Proceedings of the International Conference on Information Technology
Year:
2007

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Abstract

In this paper subcarrier and power allocation to each user at base-station maximizes the user data rates, subject to constraints on total power and bit error rate. First, each subchannel is assigned to the user with best channel-to-noise ratio for the channel, with random power distributed by water filling algorithm. The Gao's [25] subcarrier allocation algorithm was used to calculate the power for each population in of Genetic Algorithm model. With the goal of minimize the overall transmit power while ensuring the fulfillment of each user's data rate and bit Error Rate (BER), the needed allocation is proposed through genetic search. The proposed genetic search helps fast convergence and can handle large allocations of subcarriers to users without performance degradation. The simulation results show that genetic algorithm approach will be used where complex computations are involved and near optimal solution are acceptable for optimum resource allocation.