A Survey of Conventional and Artificial Intelligence / Learning based Resource Allocation and Interference Mitigation Schemes in D2D Enabled Networks

Abstract

5th generation networks are envisioned to provide seamless and ubiquitous connection to 1000-fold more devices and is believed to provide ultra-low latency and higher data rates up to tens of Gbps. Different technologies enabling these requirements are being developed including mmWave communications, Massive MIMO and beamforming, Device to Device (D2D) communications and Heterogeneous Networks. D2D communication is a promising technology to enable applications requiring high bandwidth such as online streaming and online gaming etc. It can also provide ultra-low latencies required for applications like vehicle to vehicle communication for autonomous driving. D2D communication can provide higher data rates with high energy efficiency and spectral efficiency compared to conventional communication. The performance benefits of D2D communication can be best achieved when D2D users reuses the spectrum being utilized by the conventional cellular users. This spectrum sharing in a multi-tier heterogeneous network will introduce complex interference among D2D users and cellular users which needs to be resolved. Motivated by limited number of surveys for interference mitigation and resource allocation in D2D enabled heterogeneous networks, we have surveyed different conventional and artificial intelligence based interference mitigation and resource allocation schemes developed in recent years. Our contribution lies in the analysis of conventional interference mitigation techniques and their shortcomings. Finally, the strengths of AI based techniques are determined and open research challenges deduced from the recent research are presented.

Routing-Based Interference Mitigation in SDN Enabled Beyond 5G Communication Networks: A Comprehensive Survey

“…The study in [11], is a consolidated survey on resource allocation and interference mitigation in Device to Device (D2D) communication [12] with Artificial Intelligence (AI) [13] and Machine Learning (ML) [14]. However, the survey does not cover the SDN-based opportunities and challenges in achieving interference mitigation.…”

Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks

“…D2D transmission may be the source of severe interference to the other D2D links and the CUs. A survey of different popular and AI-based interference mitigation and RA approaches developed in D2D communications is provided in [24]. Additionally, the multiagent actor critic (MAAC) is a newly proposed algorithm in [25] to mitigate interference by efficiently distributing the spectrum allocation.…”

Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

“…In the last decade we have seen many approaches for solving the D2D challenges using AI and ML [46]. The authors in [20] proposed EHSD -Exemplary Handover Scheme During D2D Communication-a framework describing a handover scheme that is based on software-defined radio (SDR) decentralization by using fuzzy logic.…”