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Adaptive Radio Resource Allocation is essential for guaranteeing high bandwidth and power utilization as well as satisfying heterogeneous Quality-of-Service requests regarding next generation broadband multicarrier wireless access networks like LTE and Mobile WiMAX. A downlink OFDMA single-cell scenario is considered where heterogeneous Constant-Bit-Rate and Best-Effort QoS profiles coexist and the power is uniformly spread over the system bandwidth utilizing a Uniform Power Loading (UPL) scenario. We express this particular QoS provision scenario in mathematical terms, as a variation of the well-known generalized assignment problem answered in the combinatorial optimization field. Based on this concept, we propose two heuristic search algorithms for dynamically allocating subchannels to the competing QoS classes and users which are executed under polynomially-bounded cost. We also propose an Integer Linear Programming model for optimally solving and acquiring a performance upper bound for the same problem at reasonable yet high execution times. Through extensive simulation results we show that the proposed algorithms exhibit high close-to-optimal performance, thus comprising attractive candidates for implementation in modern OFDMA-based systems.

Radio resource allocation algorithms for multi-service OFDMA networks: the uniform power loading scenario