认知网络中基于数据冲突的帧结构优化
Frame structure optimization of cognitive radios based on data collisions
姬国庆 1杨士亮 2朱洪波3
作者信息
- 1. 南京邮电大学江苏省无线通信重点实验室,江苏南京210003;徐州空军勤务学院,江苏徐州221006
- 2. 徐州空军勤务学院,江苏徐州221006
- 3. 南京邮电大学江苏省无线通信重点实验室,江苏南京210003
- 折叠
摘要
在主用户数据流量的指数分布模型基础上,考虑认知用户和主用户之间必然存在的数据冲突的影响,基于认知网络有效数据吞吐量的最大化准则,建立了认知网络帧结构参数中感知周期与检测时间的联合优化模型.鉴于理论证明的困境,通过基于Armijo非精确线搜索的最速下降算法求得了优化模型的全局最优解,结果验证了优化模型的有效性,实现了认知网络的数据吞吐量与帧结构的折衷优化.搜索算法的结果与同时给出的理论数值仿真是一致的.
Abstract
Due to the on/off freedom of the primary users and the "transmit after listen" rule of the second users,there exist inevitable data collisions between them.The trade-off between the cognitive radios network achievable throughput and the cognitive network frame structure is modeled as a joint optimization of sensing period and detection time.Considering the theoretical difficulty of the proof,the steepest descent method algorithm based on Armijo line search rule is applied to solve the optimization problem.The solutions prove that there exists a unique global optimal solution of our optimization model.Consequently,the optimization model is valid.The numerical solutions of the optimization problem are also provided and show the consistency to the search algorithm.The optimal cognitive frame structure and the trade-off to the cognitive data throughput are achieved.
关键词
认知无线电/帧结构/联合优化/数据冲突/吞吐量折衷Key words
cognitive radios/frame structure/joint optimization/data collisions/throughput trade-off引用本文复制引用
基金项目
国家重点基础研究发展规划(973计划)(2007CB310607)
国家重大科技专项项目(2009ZX03003-002)
国家重大科技专项项目(2009ZX03007-003)
出版年
2013
NETL
NSTL
维普
万方数据