On the effect of blockage objects in dense MIMO SWIPT networks

TL;DR

This paper investigates how indoor obstacles like walls affect the balance between information transfer and energy harvesting in dense MIMO SWIPT networks, using stochastic models to analyze performance trade-offs.

Contribution

It introduces a stochastic framework combining Poisson Point and Manhattan Line Processes to analyze blockage effects on SWIPT network performance.

Findings

Blockages significantly impact the rate-energy trade-off.

Network densification can mitigate blockage effects.

The topology of obstacles influences the optimal deployment of network elements.

Abstract

Simultaneous information and power transfer (SWIPT) is characterised by the ambiguous role of multi-user interference. In short, the beneficial effect of multi-user interference on RF energy harvesting is obtained at the price of a reduced link capacity, thus originating nontrivial trade-offs between the achievable information rate and the harvestable energy. Arguably, in indoor environments, this trade-off might be affected by the propagation loss due to blockage objects like walls. Hence, a couple of fundamental questions arise. How much must the network elements be densified to counteract the blockage attenuation? Is blockage always detrimental on the achievable rate-energy trade-off? In this paper, we analyse the performance of an indoor multiple-input multiple-output (MIMO) SWIPT-enabled network in the attempt to shed a light of those questions. The effects of the obstacles are examined with the help of a stochastic approach in which energy transmitters (also referred to as power heads) are located by using a Poisson Point Process and walls are generated through a Manhattan Poisson Line Process. The stochastic behaviour of the signal attenuation and the multi-user interference is studied to obtain the Joint Complementary Cumulative Distribution Function (J-CCDF) of information rate and harvested power. Theoretical results are validated through Monte Carlo simulations. Eventually, the rate-energy trade-off is presented as a function of the frequency of walls to emphasise the cross-dependences between the deployment of the network elements and the topology of the venue.