摘要
为满足干扰温度和总发送功率限制,并最大化用户的传输速率,提出一种上行认知无线电正交频分复用(OFDM)系统的最优功率分配算法.该算法首先在认知用户总功率限制下使用置零迭代注水算法进行功率分配,然后将超过干扰功率限的子载波功率调整为干扰功率限,将剩余功率在剩余子载波上重新进行迭代注水分配,直至获得最优功率分配.数学推导证明该算法具有最优性,仿真结果验证了该结论,同时表明该算法在所需迭代次数最多的情况下计算量仍比梯度方法减少50%以上.
In order to satisfy the limitation of interference temperature and total transmission power and to maximize users＇ transmission rate, an optimal power allocation algorithm adaptive to uplink cognitive radio OFDM （Orthogonal Frequency Division Multiplexing） system is proposed. In this algorithm, first, the zero-setting iterative waterfilling algorithm under the constraints of total power of the cognitive user is applied to the power allocation. Then, the subcarrier power exceeding the interference power limit is set as the new interference power limit. Finally, the residual power is allocated to the residual subcarriers by the iterative water-filling algorithm until the optimal power allocation is achieved. Both the mathematical derivation and the simulation results prove that its proposed algorithm is optimal, and that its computation amount reduces by over 50%, as compared with the gradient method even at the highest iterative times.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第5期18-23,共6页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(61001113)
华南理工大学中央高校基本科研业务费资助项目(2009ZM0071)
粤港关键领域重点突破项目(20060104-2)
关键词
认知无线电
功率分配
干扰温度
注水算法
cognitive radio
power allocation
interference temperature
water-filling algorithm
