A Novel Temperature-based Model for SWIPT

TL;DR

The paper addresses the limitations of traditional SWIPT by introducing a temperature-based paradigm that uses the thermal dynamics of RF signals to carry information and harvest energy without receiver splitting. By discretizing the receiver's heat equation into $T_{i+1}=T_e+ \alpha \sum_{k=1}^i (1-\beta)^{i-k}P_k+w_k$, the authors construct a virtual MIMO channel with memory that maps to a MIMO intensity channel. They derive ergodic achievable rates under channel inversion for exponential and uniform inputs, establish a capacity upper bound, and compute harvested energy under a nonlinear EH model, with closed-form expressions for each input distribution. The results show that exponential inputs outperform uniform inputs at low power for rate and EH, while uniform inputs improve EH at high power, highlighting important trade-offs and design guidance for temperature-based SWIPT in IoT and nano-sensor contexts.

Abstract

In this letter, a novel communication paradigm for simultaneous wireless information and power transfer (SWIPT) is proposed, which leverages the thermal characteristics of electromagnetic signals. In particular, the proposed scheme exploits the inherent thermal dynamics of electromagnetic signals, enabling the seamless integration of information decoding and energy harvesting (EH). As a consequence, in contrast to conventional SWIPT techniques, the proposed model eliminates the need to divide the received signal into orthogonal components. By exploiting the thermal correlation between consecutive time slots, the communication channel is converted to a virtual multiple-input multiple-output (MIMO) channel with memory. We evaluate the achievable rate of the proposed temperature-modulated channel for uniform and exponential input distributions and assess its performance in terms of harvested energy through a non-linear harvesting model. Our numerical results reveal that the exponential distribution outperforms the uniform distribution in rate and harvested energy at low input power levels, while the uniform distribution achieves a better EH performance at high input power levels.

Figures (3)

• Figure 1: System model of the considered temperature-modulated channel for SWIPT.
• Figure 2: Ergodic achievable rates and upper bound for the MIMO temperature channel under Rayleigh fading.
• Figure 3: Average harvested energy performance. Lines and markers depict theoretical and simulation results, respectively.