In this paper,the online power control and rate adaptation for a wireless communication system with energy harvesting(EH)are investigated,in which soft decision decoding is adopted by the receiver.To efficiently utili...In this paper,the online power control and rate adaptation for a wireless communication system with energy harvesting(EH)are investigated,in which soft decision decoding is adopted by the receiver.To efficiently utilize the harvested energy and maximize the actual achievable transmission rate under the constraints of the available channel codes and modulation schemes,the transmit power,code rate and modulation order are jointly optimized.The Lyapunov framework is used to transform the long-term optimization problem into a per time slot optimization problem.Since there is no theoretical formula for the error rate of soft decision decoding,the optimization problem cannot be solved analytically.A table to find the optimal modulation order and code rate under the different values of signal-to-noise ratio(SNR)is built first,and then a numerical algorithm to find the solution to the optimization problem is given.The feasibility and performance of the proposed algorithm are demonstrated by simulation.The simulation results show that compared with the algorithms to maximize the theoretical channel capacity,the proposed algorithm can achieve a higher actual transmission rate.展开更多
基金National Nature Science Foundation of China(61971080).
文摘In this paper,the online power control and rate adaptation for a wireless communication system with energy harvesting(EH)are investigated,in which soft decision decoding is adopted by the receiver.To efficiently utilize the harvested energy and maximize the actual achievable transmission rate under the constraints of the available channel codes and modulation schemes,the transmit power,code rate and modulation order are jointly optimized.The Lyapunov framework is used to transform the long-term optimization problem into a per time slot optimization problem.Since there is no theoretical formula for the error rate of soft decision decoding,the optimization problem cannot be solved analytically.A table to find the optimal modulation order and code rate under the different values of signal-to-noise ratio(SNR)is built first,and then a numerical algorithm to find the solution to the optimization problem is given.The feasibility and performance of the proposed algorithm are demonstrated by simulation.The simulation results show that compared with the algorithms to maximize the theoretical channel capacity,the proposed algorithm can achieve a higher actual transmission rate.