A low-complexity resource allocation algorithm for OFDMA cognitive networks

For the power-limited orthogonal frequency division multiple access(OFDMA) cognitive networks, a low-complexity resource allocation algorithm is proposed, including subcarrier allocation and power allocation. In the subcarrier allocation, the algorithm assigns the subcarriers with the worst channel quality to the users at a higher priority. Then, the remaining subcarriers are sorted in descending order according to the variance of channel quality and assigned to the users. Thus, the remaining subcarriers will not be allocated to the users with the worst channel quality. In the power allocation, the judgment of the anti-interference threshold of the primary user is introduced into the traditional linear water-filling algorithm. This algorithm can maximize the throughput of secondary users and improve the anti-interference ability of the primary user simultaneously. The simulation results show that, compared with the existing algorithms, the proposed algorithm can effectively improve the channel quality for the subcarriers allocated to users. The throughput of secondary users is very close to the theoretical upper bound. The proposed algorithm has an acceptable fairness for primary users and low computational complexity.