Fair resource allocation in downlink OFDM-based cognitive radio networks

This work investigates the downlink resource allocation (RA) problem in orthogonal frequency division multiplexing (OFDM)-based cognitive radio networks. The objective of this work is to develop a fair RA-algorithm that maximizes the capacity of secondary users (SUs) and in the same time limits the interference caused to the primary users. The fairness condition is formulated as a minimal data condition at SUs. A relaxed version of the RA-problem is first reviewed without adopting the fairness and then a heuristic algorithm is proposed based on the results obtained for the relaxed problem. Computer simulation results illustrate that the proposed heuristic algorithm can achieve near-optimal performance.