Unified Simultaneous Wireless Information and Power Transfer for IoT: Signaling and Architecture with Deep Learning Adaptive Control

TL;DR

This paper introduces a unified SWIPT system with a novel receiver architecture and an adaptive control algorithm using deep learning, enhancing wireless information and power transfer efficiency for low-power IoT devices.

Contribution

It proposes a unified signaling scheme and a low-power receiver architecture, along with an adaptive control algorithm based on TCN for optimized mode switching in SWIPT systems.

Findings

Improved achievable rate for low-power IoT devices.

Effective mode switching via deep learning-based adaptive control.

Low-power, unified SWIPT system suitable for IoT deployments.

Abstract

In this paper, we propose a unified SWIPT signal and its architecture design in order to take advantage of both single tone and multi-tone signaling by adjusting only the power allocation ratio of a unified signal. For this, we design a novel unified and integrated receiver architecture for the proposed unified SWIPT signaling, which consumes low power with an envelope detection. To relieve the computational complexity of the receiver, we propose an adaptive control algorithm by which the transmitter adjusts the communication mode through temporal convolutional network (TCN) based asymmetric processing. To this end, the transmitter optimizes the modulation index and power allocation ratio in short-term scale while updating the mode switching threshold in long-term scale. We demonstrate that the proposed unified SWIPT system improves the achievable rate under the self-powering condition of low-power IoT devices. Consequently it is foreseen to effectively deploy low-power IoT networks that concurrently supply both information and energy wirelessly to the devices by using the proposed unified SWIPT and adaptive control algorithm in place at the transmitter side.