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

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 long-term 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-plus-penalty” 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.