Spatial Network Calculus and Performance Guarantees in Wireless Networks

TL;DR

This paper introduces a spatial network calculus framework that provides universal performance guarantees, including SINR bounds and latency guarantees, for large wireless networks with spatial regulation properties.

Contribution

It develops the first spatial network calculus with regulation classes and derives universal performance bounds applicable to various wireless network types.

Findings

Universal SINR bounds for all links in regulated networks

End-to-end latency guarantees derived from combined calculus approaches

Performance guarantees do not hold in unregulated Poisson networks

Abstract

This work develops a novel approach toward performance guarantees for all links in arbitrarily large wireless networks. It introduces a spatial network calculus, consisting of spatial regulation properties for stationary point processes and the first steps of a calculus for this regulation, which can be seen as an extension to space of the classical network calculus. Specifically, two classes of regulations are defined: one includes ball regulation and shot-noise regulation, which are shown to be equivalent and upper constraint interference; the other one includes void regulation, which lower constraints the signal power. These regulations are defined both in the strong and weak sense: the former requires the regulations to hold everywhere in space, whereas the latter only requires the regulations to hold as observed by a jointly stationary point process. Using this approach, we derive performance guarantees in device-to-device, ad hoc, and cellular networks under proper regulations. We give universal bounds on the SINR for all links, which gives link service guarantees based on information-theoretic achievability. They are combined with classical network calculus to provide end-to-end latency guarantees for all packets in wireless queuing networks. Such guarantees do not exist in networks that are not spatially regulated, e.g., Poisson networks.