基于认知OFDM的子载波功率分配改进算法

在认知无线网络中，建立了基于认知OFDM多载波资源分配数学模型，在授权用户干扰受限条件下，以最大化传输速率为目标进行认知用户的子载波功率分配。传统注水法被证明是最优的单用户子载波功率分配算法，在传统注水法功率分配基础上，提出了两种可行的子载波功率分配改进算法，改进算法一是通过对水面值的粗略估计快速确定不分配功率子载波，改进算法二不需要通过迭代计算水面值，只通过线性计算就可以直接确定不分配功率的子载波，且对授权用户不产生干扰。仿真结果表明，在改进的两种子载波功率分配算法下，认知用户的数据传输速率优于传统注水法功率分配时认知用户的数据速率，所提改进算法具有自适应特性且计算复杂度大大降低。 

Improved Algorithms of Sub-carrier Power Allocation in Cognitive OFDM

Mathematical model of multi-carrier resource allocation in cognitive OFDM is constructed in Cognitive Radio Networks (CRN). Multi-carrier power allocation with the target of maximizing the transmit capacity of cognitive user is proposed under the condition of primary user’s interference constraint. Traditional water-filling algorithm is regarded as the optimal sub-carrier power allocation algorithm for single user. In this paper, two improved multi carrier power allocation algorithms based on water-filling are proposed. One of the improved algorithms can quickly determine the sub-carriers that do not require power injection by rough estimation of water level. The other one can directly determine the sub-carriers that do not require power injection by linear calculation. And there is no need for this algorithm to calculate the value of water level though iterative method. Meanwhile, all of them do not make any interference to primary user, which shows they are practical and feasible in CRN. Numerical results indicate that, the transmit capacity with the proposed power allocation algorithms are superior to that with traditional water-filling scheme for secondary user. However, the proposed sub-carrier power allocation algorithms could reduce the system computational complexity greatly and has some adaptive features.