Unary Coding Design for Simultaneous Wireless Information and Power Transfer with Practical M-QAM

Relying on the propagation of modulated radio-frequency (RF) signals, we can achieve simultaneous wireless information and power transfer (SWIPT) to support low-power communication devices. In this paper, we proposed a unary coding based SWIPT encoder by considering a practical M-QAM. Markov chains are exploited for characterising coherent binary information source and for modelling the generation process of modulated symbols. Therefore, both mutual information and the average energy harvesting performance at the SWIPT receiver are analysed in semi-closed-form. With the aid of the genetic algorithm, the sub-optimal codeword distribution of the coded information source is obtained by maximising the average energy harvesting performance, while satisfying the requirement of the mutual information. Simulation results demonstrate the advantage of the SWIPT encoder. Moreover, a higher-level unary code and a lower-order M-QAM results in higher WPT performance, when the maximum transmit power of the modulated symbol is fixed

Unary Coding Design for Simultaneous Wireless Information and Power Transfer With Practical M-QAM

Relying on the propagation of modulated radio-frequency (RF) signals, we can achieve simultaneous wireless information and power transfer (SWIPT) to support low-power communication devices. In this paper, we proposed a unary coding based SWIPT encoder by considering a practical M-QAM. Markov chains are exploited for characterising coherent binary information source and for modelling the generation process of modulated symbols. Therefore, both mutual information and the average energy harvesting performance at the SWIPT receiver are analysed in semi-closed-form. With the aid of the genetic algorithm, the sub-optimal codeword distribution of the coded information source is obtained by maximising the average energy harvesting performance, while satisfying the requirement of the mutual information. Simulation results demonstrate the advantage of the SWIPT encoder. Moreover, a higher-level unary code and a lower-order M-QAM results in higher WPT performance, when the maximum transmit power of the modulated symbol is fixed

Optimal finite horizon sensing for wirelessly powered devices

We are witnessing a significant advancements in the sensor technologies which has enabled a broad spectrum of applications. Often, the resolution of the produced data by the sensors significantly affects the output quality of an application. We study a sensing resolution optimization problem for a wireless powered device (WPD) that is powered by wireless power transfer (WPT) from an access point (AP). We study a class of harvest-first-transmit-later type of WPT policy, where an access point (AP) first employs RF power to recharge the WPD in the down-link, and then, collects the data from the WPD in the up-link. The WPD optimizes the sensing resolution, WPT duration and dynamic power control in the up-link to maximize an application dependant utility at the AP. The utility of a transmitted packet is only achieved if the data is delivered successfully within a finite time. Thus, we first study a finite horizon throughput maximization problem by jointly optimizing the WPT duration and power control. We prove that the optimal WPT duration obeys a time-dependent threshold form depending on the energy state of the WPD. In the subsequent data transmission stage, the optimal transmit power allocations for the WPD is shown to posses a channel-dependent fractional structure. Then, we optimize the sensing resolution of the WPD by using a Bayesian inference based multi armed bandit problem with fast convergence property to strike a balance between the quality of the sensed data and the probability of successfully delivering it