Deterministic Differential Search Algorithm for Distributed Sensor/Relay Networks

TL;DR

This paper introduces a deterministic differential search algorithm for distributed sensor/relay networks that efficiently aligns phases for beamforming without requiring extensive channel state information, enhancing power efficiency and reliability.

Contribution

The paper presents a novel DDSA algorithm that uses RSS differences for phase adjustment, reducing feedback overhead in distributed beamforming.

Findings

Rapid convergence to target RSS threshold

Reduces feedback overhead compared to traditional methods

Improves power efficiency and reliability in sensor networks

Abstract

For distributed sensor/relay networks, high reliability and power efficiency are often required. However, several implementation issues arise in practice. One such problem is that all the distributed transmitters have limited power supply since the power source of the transmitters cannot be recharged continually. To resolve this, distributed beamforming has been proposed as a viable solution where all distributed transmitters seek to align in phase at the receiver end. However, it is difficult to implement such transmit beamforming in a distributed fashion in practice since perfect channel state information (CSI) need to be made available at all distributed transmitters, requiring tremendous overhead to feed back CSI from the receiver to all distributed transmitters. In this paper, we propose a novel algorithm that belongs to the category of deterministic phase adjustment algorithm: the Deterministic Differential Search Algorithm (DDSA), where the differences between the measured received signal strength (RSS) are utilized judiciously to help us predict the deterministic phase adjustment done at distributed transmitters. Numerical simulations demonstrate rapid convergence to a pre-determined threshold.