Throughput Maximization in Multi-Hop Wireless Networks under Secrecy Constraint

TL;DR

This paper investigates how to maximize throughput in multi-hop wireless industrial networks while ensuring secrecy against eavesdroppers, by optimizing relay placement and coding rates using stochastic geometry.

Contribution

It introduces a stochastic-geometry based framework to optimize relay positions and coding rates for secure multi-hop throughput maximization.

Findings

Optimal coding rate depends only on path-loss exponent and is usually high.

Shorter hops are generally preferable to longer hops.

Secrecy-constrained throughput can match unconstrained optimal performance if feasible.

Abstract

This paper analyzes the throughput of industrial communication networks under a secrecy constraint. The proposed scenario is composed by sensors that measure some relevant information of the plant that is first processed by aggregator node and then sent to the control unit. The sensor measurements, their communication with the aggregetor and the information processing are all assumed perfect. To reach the control unit, the message may travel through relay nodes, forming a multi-hop, wireless link. At every hop, eavesdropper nodes attempt to acquire the messages transmitted through the legitimate link. The communication design problem posed here is how to maximize the multi-hop throughput from the aggregator to the control unit by finding the best combination of relay positions (i.e. hop length: short or long) and coding rates (i.e. high or low spectral efficiency) so that the secrecy constraint is satisfied. Using a stochastic-geometry approach, we show that the optimal choice of coding rate depends only on the path- loss exponent and is normally high while greater number of shorter hops are preferable to smaller number of longer hops. For the scenarios of interest, we prove that the optimal throughput subject to the secrecy constraint achieves the unconstrained optimal performance if a feasible solution exists.