认知无线电网络中基于跨层设计的能效优化算法

为提高认知无线电网络中次用户节点的能量有效性，该文基于连续时间马尔科夫理论对次用户的频谱感知和接入过程进行联合建模，对影响次用户传输能效的主要因素进行了分析，提出了一种基于跨层设计的能量有效优化算法。该算法可有效减小主用户非时隙返回信道对次用户能量有效性的影响，并通过联合优化感知时间和接入概率，使次用户在感知性能和传输能效间实现了有效折衷。仿真结果表明，本文算法相对于仅考虑频谱感知或接入策略的单层优化算法，可使次用户的能量有效性得到较大提高。 

An Energy-Efficient Optimization Algorithm Based on Cross-layer Design for Cognitive Radio Networks

In order to increase the energy efficiency of secondary users in cognitive radio networks, the processes of spectrum sensing and access of secondary users are modeled by continuous-time Markov theory. Based on the analysis of the main factors affecting the energy efficiency of secondary users, an energy-efficient algorithm based on cross-layer design is proposed. The algorithm can decrease communication interruption probability of secondary users caused by unslotted access of primary users, and a tradeoff between sensing performance and energy effi-ciency is gained by setting proper sensing time and access probability. Simulation results indicate that the proposed algorithm is better than single-layer optimal schemes which only consider either spectrum sensing or access strategy for it provides the secondary users with more energy efficiency.