认知无线网络中准入控制和功率控制联合优化

提出了一种基于离散的粒子群算法和单纯形法的优化机制来实现准入控制和功率控制的联合优化方案。在主用户干扰温度门限和次用户QoS的约束下,将准入控制建模成0/1组合优化问题,并将功率控制建模成线性约束问题,由于准入控制是NP难,该方案将准入控制和功率控制进行加权规划进行优化,同时,为降低计算复杂度,提出一种针对准入控制组合优化的可行性验证方法。并且针对离散的粒子群算法的收敛性进行了证明。仿真与分析表明,该方案具有收敛性,相比其他优化方案,能更有效地提高用户准入量并降低用户功率消耗,提高网络性能。

Joint optimization of admission control and power control in cognitive radio networks

A scheme is proposed based on the discrete particle swarm optimization and simplex method to realize the joint optimization of admission control and power control. Under the constraint of the interference temperature and the QoS requirement of secondary users, the admission control is modeled as 0/1 the combinatorial optimization problem and the power control is transformed into a linear constraint problem. The admission control is NP-hard, the admission control and power control is solved by weighted programming. In order to reduce the complexity, a feasibility verification method of combined optimization of admission control is proposed. The convergence of the discrete particle swarm optimization algorithm is proved. The simulation results and analysis show that the proposed scheme is convergent. Compared with the existing optimization methods, the proposed scheme can effectively increase the number of admitted secondary users and reduce power consumption, and improve the performance of network optimization.