认知无线电网络在提高频谱利用率的同时,带来了通信能耗增大的问题。在满足用户体验质量的前提下,引入绿色通信的理念,面向基站提出一种新型节能策略。通过构建具有抢占式优先服务和单重工作休假机制的二维离散时间马尔可夫随机模型,运用矩阵几何解方法,从系统节能率、信道利用率、认知用户平均延迟及认知用户中断率等方面评估节能策略的系统性能,并综合理论分析结果和仿真统计结果,验证节能策略的有效性。从经济学角度出发,构造收益函数,设计非线性智能优化算法,研究认知用户数据分组的纳什均衡与社会最优行为,面向认知用户制定授权频谱的定价方案。针对不同的系统参数,进行系统实验,验证定价方案的合理性。
Spectrum utilization can be improved in cognitive radio network(CRN), however, the problem of increasing communication energy consumption was also brought. Under the premise of ensuring the experience quality of system users, the concept of green communication in CRN was introduced, and a novel energy saving strategy for base station was proposed. Accordingly, a two-dimensional discrete time Markov stochastic model with preemptive priority service and single working vacation was established. Using the method of a matrix geometric solution, the system performance of the energy saving strategy was evaluated in terms of energy saving rate, channel utilization, average delay of secondary users and interruption of secondary users. The theoretical analysis results and the simulation results verify the effectiveness of the energy saving strategy. From the perspective of economics, a profit function was constructed and a nonlinear optimization algorithm was designed to investigate the Nash equilibrium and the socially optimal behavior of the secondary user packets, then a pricing policy of licensed spectrum for secondary users was formulated. In view of different system parameters, the system experiment was carried out to validate the rationality of the pricing policy.