A Simple Cooperative Transmission Protocol for Energy-Efficient Broadcasting Over Multi-Hop Wireless Networks

TL;DR

This paper introduces energy-efficient broadcasting protocols for multi-hop wireless sensor networks using cooperative diversity, achieving significant energy savings without GPS or node interaction through threshold-based node scheduling.

Contribution

It proposes OLA-T and OLA-VT protocols that optimize energy use by threshold-based relay decisions, integrating MAC and routing functions at the physical layer.

Findings

OLA-T and OLA-VT reduce energy consumption by up to 32%.

The protocols achieve efficient broadcasting with fewer hops and lower energy use.

Analytical results are validated with Monte Carlo simulations.

Abstract

This paper analyzes a broadcasting technique for wireless multi-hop sensor networks that uses a form of cooperative diversity called opportunistic large arrays (OLAs). We propose a method for autonomous scheduling of the nodes, which limits the nodes that relay and saves as much as 32% of the transmit energy compared to other broadcast approaches, without requiring Global Positioning System (GPS), individual node addressing, or inter-node interaction. This energy-saving is a result of cross-layer interaction, in the sense that the Medium Access Control (MAC) and routing functions are partially executed in the Physical (PHY) layer. Our proposed method is called OLA with a transmission threshold (OLA-T), where a node compares its received power to a threshold to decide if it should forward. We also investigate OLA with variable threshold (OLA-VT), which optimizes the thresholds as a function of level. OLA-T and OLA-VT are compared with OLA broadcasting without a transmission threshold, each in their minimum energy configuration, using an analytical method under the orthogonal and continuum assumptions. The trade-off between the number of OLA levels (or hops) required to achieve successful network broadcast and transmission energy saved is investigated. The results based on the analytical assumptions are confirmed with Monte Carlo simulations.