Bio-Inspired Resource Allocation for Relay-Aided Device-to-Device Communications

TL;DR

This paper proposes a bio-inspired, interference-aware resource allocation framework using genetic algorithms for relay-aided D2D communications to maximize network throughput while ensuring minimum rate thresholds.

Contribution

It introduces a real-time resource allocation method based on genetic algorithms for relay-aided D2D communications in cellular networks, emphasizing interference management and performance enhancement.

Findings

Significant throughput gains over baseline methods.

Effective interference control in dense network scenarios.

Reduced computational complexity with genetic algorithms.

Abstract

The Device-to-Device (D2D) communication principle is a key enabler of direct localized communication between mobile nodes and is expected to propel a plethora of novel multimedia services. However, even though it offers a wide set of capabilities mainly due to the proximity and resource reuse gains, interference must be carefully controlled to maximize the achievable rate for coexisting cellular and D2D users. The scope of this work is to provide an interference-aware real-time resource allocation (RA) framework for relay-aided D2D communications that underlay cellular networks. The main objective is to maximize the overall network throughput by guaranteeing a minimum rate threshold for cellular and D2D links. To this direction, genetic algorithms (GAs) are proven to be powerful and versatile methodologies that account for not only enhanced performance but also reduced computational complexity in emerging wireless networks. Numerical investigations highlight the performance gains compared to baseline RA methods and especially in highly dense scenarios which will be the case in future 5G networks.