协作认知网络中基于用户密度与感知时间的吞吐量优化

The throughput optimization based on user density and sensing time in cooperation cognitive networks

在协作认知网络中,增加协作的认知用户数,可以减少本地感知时间,但同时会增加通知时间,所以在优化感知性能时需要权衡考虑认知用户的数量.在考虑通知时间的情况下建立了协作认知网络吞吐量优化模型,在保护主用户的前提下,联合优化用户密度和感知时间使吞吐量最大.仿真结果表明:用户密度较大时,通知时间限制了吞吐量的提高,选择合适的协作用户数才能使吞吐量最优.

In cooperation cognitive network,the local sensing time is reduced by increasing the number of cognitive user for cooperation,but the reporting time is increased.So it＇s necessary to choose proper cognitive user number for cooperation to get the optimal perception performance.The optimization throughput model of cooperation cognitive network was established considering the reporting time.Under the premise of protection the primary users,the joint optimization of user density and sensing time maximize throughput.Simulation results showed that when the user density is large,the reporting time limits the improvement of throughput, select the appropriate number of concurrent users can make optimal throughput.