Adaptive Single-Cell OFDMA Resource Allocation for Heterogeneous Data Traffic

Adaptive radio resource allocation mechanisms exploiting the inherent frequency selectivity of the wireless medium as well as the multi-user effect are expected to play a key role in emerging next generation OFDMA-based wireless networks. Although a plethora of studies concerning either constant/guaranteed bit rate (CBR/GBR) or variable bit rate/best effort (VBR/BE) traffic has been published to date, limited amount of work has been devoted to the mixed OFDMA-centric GBR-BE data traffic problem. In this paper we attempt to deal with the specific heterogeneous allocation problem, which mathematically is formulated as a large-scale combinatorial optimization problem, in the context of the downlink of a SISO-OFDMA single-cell network. The contribution of our work is twofold: first, the fundamental trade-off of power and subcarriers utilization regarding the GBR-class users is thoroughly examined through a multi-objective evolutionary optimization framework. Secondly, an approximated yet effective resource allocation algorithm is devised that solves the mixed traffic problem utilizing zeroth-order methods from classical optimization theory. The presented concepts are accompanied by several simulation results.