一种公平的认知无线电系统下行频谱分配策略

Downlink spectrum allocation strategy for cognitive radio system with fairness consideration

目前关于认知无线电频谱分配的研究大多以最大化系统容量为目标,很少考虑认知用户的QoS需求,频谱分配方案设计缺乏公平性。针对主用户干扰限制和保障认知用户QoS需求,结合OFDM技术,研究了认知无线电场景中下行多用户分配算法。该算法构建不等式约束下的目标函数以最大化系统容量,通过拉格朗日(Lagrange)对偶优化法给出近似最优解。仿真结果表明,所提算法在牺牲系统和容量的前提下充分保证了次用户的QoS需求,提高了系统的公平性。

Present researches on the spectrum allocation for cognitive radio system mostly focus on maximizing the network throughput, while the secondary users QoS demand is rarely considered, which makes the spectrum allocation scheme lack fairness. With consider- ation of primary users interference temperature constraint and secondary users QoS demand, downlink spectrum allocation algorithm for OFDM-based cognitive radio system is studied. The proposed algorithm constructs objective function subject to inequality constraint to maximize the network throughput. The approximate optimal solution is obtained by Lagrange dual method. Simulation result shows that the QoS demand of secondary users can be guaranteed at the cost of network throughput loss, which improves the system fairness.