一种基于FBMC-OQAM干扰抑制的功率资源分配新算法

A New Power-Resource Allocation Algorithm with Interference Restraining Based on FBMC-OQAM

基于FBMC-OQAM(filter bank multicarrier-offset quadrature amplitude modulation)的多用户频谱共享的认知无线电网络中的资源分配问题,在此提出了一种干扰抑制的功率资源分配算法(powerresource allocation algorithm,PAA).引入跨层干扰限制来保护网络中的次用户免受过多的干扰.引入虚拟队列的概念,将多用户争用信道资源导致的额外分组时延转化为在信道对应的虚拟队列中的排队时延.该算法以系统能效为目标函数、以时延和传输功率为约束条件,提出一个非线性约束下的非线性分式规划问题.设计了一种迭代算法,先通过一些变换将分式目标函数变为多项式形式,降低其实现难度后迭代求其全局最优解.此外设计了一种次优算法,以部分性能换取更低的计算复杂度.经实验仿真对比,最优算法具有高性能,次优算法在低计算复杂度的基础上具有较高性能,2种算法均具有很好的实用价值.

By taking the energy efficiency as the objective function,a nonlinear programming problem with nonlinear constraints is studied under the constraints of time delay and transmission power.That is to say,a kind of new power-resource allocation algorithm(PAA)with interference restraining based on FBMC-OQAM(filter bank multicarrier-offset quadrature amplitude modulation)has been presented in this paper,which can improve the energy efficiency of entire network resource and protect small-cell user(SU)in the network from too much interference while virtual queue is used to transform the extra packet delay caused by the contention for channel of multi-user into the queuing delay in the virtual queue.An iterative algorithm for PAA to solve the problem is used.The fractional objective function is transformed into polynomial form,and the global optimal solution is obtained by iteration after reducing the computational complexity.At the same time,a sub-optimal method is developed to reduce computational complexity and some performance.The simulation results show that the optimal algorithm has higher performance and the sub-optimal method has lower computational complexity.The designed algorithm has important value for the practical applications,such as the Internet of things,Internet of vehicles,signal processing,artificial intelligence,and so on.Now,it has been used in our project on cognitive radio network(CRN)to solve the problem of power resource allocation.