动态主用户流量模型的跨层优化设计

Cross-layer optimization design of dynamic primary users traffic model

为适应主用户流量变化较快的场景,在不完美频谱感知的情况下最大化认知用户的吞吐量,提出了一种基于集中式Overlay认知无线网络中感知时间与资源分配跨层优化算法。将优化目标分解为信道分配和检测时间同功率分配联合优化两个子问题,通过子算法迭代,最终得到感知时间与资源分配的联合最优解。仿真结果表明,相对于仅考虑频谱感知或资源分配的单层优化算法,该算法可在兼顾公平的前提下使次用户吞吐量得到有效提升。

In order to adapt to the scene of primary users traffic's rapid change and maximize throughput of cognitive users in the case of imperfect spectrum sensing, a cross-layer optimization algorithm of sensing time and source allocation based on centralized Overlay cognitive radio networks is proposed. The optimization objective is decomposed into two sub problems: channel allocation and the joint optimization of sensing time and power allocation. The two sub algorithms are iterative and the optimal solution is obtained. Simulation results indicate that the proposed algorithm is better than single-layer optimal schemes which only consider either spectrum sensing or source allocation and effectively improve the throughput of second users under the premise of fairness.