能量收集通信系统中发送功率与传输速率的在线控制算法

Online Control Algorithm of Power and Rate in Energy Harvesting Communication Systems

该文针对发送端由能量收集(EH)设备供电的无线通信系统,研究在能量收集和信道状态先验信息未知的条件下,以最大化实际可达传输速率为目标的发送功率、调制方式和信道编码码率的联合优化问题。基于Lyapunov优化框架,将能量使用的长期约束转换为能量虚队列的稳定性要求,将能量使用约束下的长期时间平均实际可达传输速率最大化问题转化为单时隙的、仅依赖于当前信道状态和电池状态的“漂移加惩罚”项上界的最小化问题。优化问题通过一个高效的数值方法求解。另外还给出了基于滑动窗口的K-means聚类方法的“漂移加惩罚”中权重和电池电量虚队列偏移量两个参数的自适应调整算法。在不同能量到达随机模型下与对比算法进行了性能的仿真对比,结果表明,该文所提算法在各种能量到达模型下都能获得更高的长期平均实际可达传输速率。另外,通过与参数固定为最优情况下算法性能的对比,证明参数自适应调整算法正确、有效。

In this paper,the joint optimization of transmission power,modulation mode and the rate of channel codes is studied in wireless communication systems with Energy Harvesting(EH)when the prior information of energy harvesting and channel state is unknown.The target of the optimization is to maximize the actual achievable transmission rate.Based on the Lyapunov optimization framework,the long-term constraint of energy is transformed into the stability requirement of energy virtual queue,and the maximization of the longterm average achievable transmission rate is transformed to the minimization of the upper bound on the“drift-plus-penalty”at each time slot that only depends on the current system state such as channel fading and battery power level.The optimization is solved by using an efficient numerical algorithm.In addition,an adaptive adjustment method for the two parameters,that is,weight and virtual queue offset in“drift-pluspenalty”based on sliding window K-means clustering is given.The performance of the proposed algorithm is compared with that of the comparison algorithms under different energy arrival stochastic models by computer simulation.The results show that the proposed algorithm can achieve a higher long-term average rate under various energy arrival models.The correctness and effectiveness of the adaptive adjustment of the two parameters are verified by the performance comparing between the algorithm with the optimal parameters and with the adaptive adjusted parameters.