CAJ | 학술논문

针对各态历经信道下多用户OFDM资源分配的用户速率加权和最大化问题，提出了一种新注水方法，能够快速和准确地得到最优子载波分配和最优功率分配；根据Karush－Kuhn－Tucker （ KKT）最优性条件，采用粒子群算法对速率阈值乘子进行调整，最大化了满足用户速率阈值限制的用户速率加权和。通过对所提算法与随机对偶梯度算法的分析比较发现，所提算法能够更好地满足KKT最优性条件，从而有利于找到最优解。仿真结果表明，本算法所得到的用户速率加权和高于随机对偶梯度算法。
침대각태력경신도하다용호OFDM자원분배적용호속솔가권화최대화문제，제출료일충신주수방법，능구쾌속화준학지득도최우자재파분배화최우공솔분배；근거Karush－Kuhn－Tucker （ KKT）최우성조건，채용입자군산법대속솔역치승자진행조정，최대화료만족용호속솔역치한제적용호속솔가권화。통과대소제산법여수궤대우제도산법적분석비교발현，소제산법능구경호지만족KKT최우성조건，종이유리우조도최우해。방진결과표명，본산법소득도적용호속솔가권화고우수궤대우제도산법。
Aiming at the problem of maximizing the weighted sum of user rate in the multi-user OFDM resource allocation with ergodic channel, a novel water-filling method was pro-posed, which could obtain the optimal sub-carrier allocation and the optimal power alloca-tion quickly and accurately.Then particle swarm algorithm was used to adjust Lagrange mul-tipliers of user rate thresholds based on the Karush–Kuhn–Tucker ( KKT) condition to maximize the weighted sum of user rate which satisfies user rate thresholds.The analysis and comparison between the proposed algorithm and the stochastic dual-gradient algorithm sug-gest that the proposed algorithm was better to meet the KKT condition.The simulation results showed that the weighted sum of user rate obtained by the proposed algorithm was superior to that obtained by the stochastic dual-gradient algorithm.