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Multiuser Orthogonal frequency division multiplexing (MUOFDM) is one of the promising techniques for future cellular and wireless networks for achieving high downlink capacities. The objective of the next generation cellular and wireless networks, which are based on (MU-OFDM) is to increase the network efficiency by maximizing the total throughput of the system and minimizing the overall transmit power for a given quality of service (QOS). The sum capacity of MU-OFDM is maximized when each subchannel is assigned to the user with the best channel-tonoise ratio for that subchannel. Ever increasing demand for high throughput, low delay and low Outage probability can be met by using Adaptive Resource Allocation in OFDM Technology. In optimal resource allocation algorithms the subcarrier and power allocation should be done simultaneously but it is computationally complex. In order to reduce the complexity of resource allocation algorithms the subcarrier and power allocation is done separately and this is called sub-optimal subcarrier allocation and sub-optimal power allocation. Z. Shen et al. in [9] has given both suboptimal subcarrier allocation and sub-optimal power allocation algorithms. In this paper we have proposed two methods of subcarrier allocation based on subcarrier allocation method in [9], and compared them with subcarrier allocation algorithm of [9]. Comparison is made between subcarrier allocation algorithms only by considering equal power distribution among subcarriers instead of sub-optimal power allocation scheme given in [9]. The simulation results show the improvement in the sum capacity (total data rate achieved) with the proposed methods of subcarrier allocation over the subcarrier allocation in [9]. General Terms Adaptive radio resource allocation, Rate adaptive radio resource allocation algorithm, Subcarrier allocation algorithm.

Fairness based Improved Subcarrier Allocation Algorithms for OFDMA based Next Generation Networks