基于AF中继的OFDM认知系统的 功率分配和子载波配对算法

建立基于放大转发(AF)中继的正交频分复用（OFDM）的认知无线电系统模型,并推导出该系统中在对从用户的源节点和中继节点的总功率限制和对主用户的干扰限制条件下的联合最优功率分配和子载波配对算法.采用拉格朗日对偶分解法和次梯度法推导出最优功率分配算法,并将基于Hopcroft-Karp算法的子载波配对方法融合到功率分配的过程中,得到联合最优算法.根据系统总功率和干扰限制的特点,提出一种低复杂度的次优功率预分配算法.分别对最优功率分配算法和次优功率分配算法、Hopcroft-Karp子载波配对算法和源节点、中继节点采用相同子载波传输的固定子载波配对算法进行仿真比较.结果表明：采用功率分配和子载波配对的联合优化技术能够大大提高系统的频谱效率,具有一定的可行性.

Power allocation and subcarrier pairing for AF-OFDM based cognitive radio systems

An OFDM based cognitive radio（CR） system with amplify-and-forward relay was established. Optimal subcarrier pairing and power allocation algorithms for the system were investigated, while the total power of CR user was under the constraint and the interference introduced to the primary user remained within a tolerable range. The Lagrange dual method and subgradient method were employed to design the optimal power allocation algorithm, and the Hopcroft Karp algorithm for subcarrier pairing was studied with power allocation algorithm. Besides, a suboptimal power allocation algorithm with regard to total system power and interference constraint was proposed, which has low computational complexity. Then the optimal power allocation algorithm was compared with the suboptimal power allocation algorithm, and the Hopcroft Karp subcarrier pairing algorithm was compared with the fixed subcarrier pairing algorithm, which indicates that the signal transmitted by the source on one subcarrier is forwarded on the same subcarrier by a relay to the destination. Finally, simulation results verify the optimization of combining power allocation with subcarrier pairing can effectively improve the system spectrum efficiency, and is feasible for practical system.