Low complexity mean enhanced greedy algorithms for dynamic subcarrier allocation in uplink LTE

This paper proposes two lower complexity mean enhanced greedy (MEG) algorithms for dynamic subcarrier allocation (DSA) in uplink Long Term Evolution (LTE) systems. The computational savings are achieved by eliminating some of the iterative steps in the existing MEG algorithm. We also investigate the effect of different optimization criteria on DSA. Simulation results show that the proposed lower complexity algorithms, have near optimal uncoded bit error rate (BER) and capacity performances when the minimum BER optimization criterion is employed. This is in contrast to the poorer average BER performances achieved using maximum capacity or maximum channel gains as optimization criteria.