基于多频段传感器辅助认知无线电网络的高能效传感器调度算法

在传感器协助认知无线电网络中,传统的高能效传感器调度问题只考虑了一个频段。多频段的传感器调度问题有许多新的研究领域。建立了一种多频段传感器调度问题的模型,提出了一种用于提高认知网络通信容量的基于遗传算法的高能效调度算法。模型考虑了传感器切换频段的能量消耗。在问题模型中,认知基站基于提高能效的目标为每个频段分配一组传感器进行协作感知。基于遗传算法的高能效调度算法通过优化传感器的调度使认知网络达到最大的通信容量,从而达到高能效的目标。仿真结果表明,本文的算法可以比贪心算法以及其他算法取得更高的网络通信容量。

An energy-efficient sensor scheduling algorithm basedon multi-band sensor-aided cognitive radio networks

Traditional energy-efficient sensor scheduling problems only consider single frequency band in sensor-aided cognitive radio networks. Multi-band energy-efficient sensor scheduling problems have many novel research fields. We formulate a multi-band sensor scheduling problem and propose a genetic algorithm based energy-efficient scheduling algorithm to improve the throughput. We take account of the energy consumption of the sensor when switching frequency bands. In the model, the cognitive base station assigns a set of sensors for each frequency to improve energy efficiency. The genetic algorithm based energy-efficient scheduling algorithm optimally schedules the activities of the sensors to increase the overall secondary system throughput and achieve the goal of energy efficiency. Simulation results show that our algorithm achieves higher network throughput than the greedy algorithm and other algorithms.