Radio Resource Allocation Algorithms for Multi-Service OFDMA Networks: The Uniform Power Loading Scenario

TL;DR

This paper addresses radio resource allocation in multi-service OFDMA networks with uniform power loading, proposing heuristic algorithms and an ILP model to optimize subchannel distribution among heterogeneous QoS classes.

Contribution

It introduces two heuristic algorithms and an ILP model for resource allocation in OFDMA networks with uniform power loading, balancing performance and computational complexity.

Findings

Heuristic algorithms achieve near-optimal performance.

Proposed methods are computationally efficient.

Algorithms are suitable for real-time implementation.

Abstract

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.