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Battery-Level-Triggered Transmit Power Control for Energy Harvesting Communications

机译:电池级触发的能量收集通信发射功率控制

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We consider a continuous-time energy harvesting (EH) communication system consisting of an EH transmitter with random lifetime and a receiver. We assume that neither the fading channel state nor the EH state is available to the transmitter and the transmitter can only observe its battery level, based on which it adjusts its transmit power. Specifically, we quantize the battery capacity of the transmitter into a number of levels, and whenever the energy in the battery hits a certain level, the EH transmitter updates its transmit power. Our main objective is to find the optimal battery-level-triggered (BLT) control policy to maximize the expected total throughput of the transmitter in its lifetime. We model the system as an extended two-dimensional stochastic fluid model (2D-SFM), and derive the Laplace-Stieltjes Transform (LST) matrices of the imbedded process on the decision time sequence, based on which, we formulate the power control problem as a Markov decision process (MDP). We obtain the BLT control policy and the maximum expected throughput by solving the 2D-SFM induced MDP. We evaluate the performance of the BLT policy by comparing it with the conventional uniform-in-time control policies, and results show that the proposed BLT power control policy provides significantly higher expected throughput under the same total energy consumption and the same average control frequency.
机译:我们考虑由具有随机寿命和接收器的EH发射器组成的连续时间能量收集(EH)通信系统。我们假设发射器的衰落信道状态和EH状态都没有可用,并且发射器只能遵守其电池电量,基于其调节其发射功率。具体地,我们将发射机的电池容量量化为多个级别,并且只要电池中的能量击中一定级别,EH发射机就会更新其发射功率。我们的主要目标是找到最佳的电池级触发(BLT)控制策略,以最大限度地提高发射机在其寿命中的预期总吞吐量。我们将系统塑造为扩展的二维随机流体模型(2D-SFM),并在决策时间序列中导出嵌入式过程的Laplace-Stieltjes变换(LST)矩阵,基于该序列,我们制定了功率控制问题作为马尔可夫决策过程(MDP)。通过求解2D-SFM诱导MDP,我们获得了BLT控制策略和最大预期吞吐量。通过将其与传统的统一控制策略进行比较,我们评估了BLT政策的性能,结果表明,所提出的BLT功率控制策略在相同的总能耗和相同的平均控制频率下提供明显更高的预期吞吐量。

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