Queue-Aware Subchannel and Power Allocation for Downlink OFDM-Based Cognitive Radio Networks

Abstract

We investigate downlink resource allocation for OFDM-based cognitive radio networks. It is assumed that secondary users are allowed to transmit on all subchannels as long as the interference they create for primary users remains below a critical threshold. We consider a practical setting where secondary users have finite queue backlogs and a total power constraint at the base station and we perform resource allocation either over one or multiple time slots. Specifically, secondary users with small queue backlogs are only allocated sufficient rates to support their traffic demands and the remaining radio resources are shared among highly backlogged users. Under this setting, we formulate the joint subchannel and power problem with max-min fairness for highly backlogged users. Then, we propose an iterative procedure to find an optimal resource allocation solution using an integer program solver. For online implementation, we develop several heuristics of increasing complexity and performance. Numerical results show that the proposed heuristics achieve very good performance compared to the optimal solutions and that taking queue backlogs into account does not make the heuristics much slower while making the system more responsive to users' need.