Related papers: Combining AI/ML and PHY Layer Rule Based Inference…

Air interface is a fundamental component within any wireless communication system. In Release 18, the 3rd Generation Partnership Project (3GPP) delves into the possibilities of leveraging artificial intelligence (AI)/machine learning (ML)…

Machine learning (ML) is an important component for enabling automation in Radio Access Networks (RANs). The work on applying ML for RAN has been under development for many years and is now also drawing attention in 3GPP and Open-RAN…

Machine Learning (ML) and Artificial Intelligence(AI) have become alternative approaches in wireless networksbeside conventional approaches such as model based solutionconcepts. Whereas traditional design concepts include the mod-elling of…

We present a review of high-performance automatic modulation recognition (AMR) models proposed in the literature to classify various Radio Frequency (RF) modulation schemes. We replicated these models and compared their performance in terms…

This paper provides a systematic and comprehensive survey that reviews the latest research efforts focused on machine learning (ML) based performance improvement of wireless networks, while considering all layers of the protocol stack (PHY,…

The 3rd Generation Partnership Project (3GPP) is currently studying machine learning (ML) for the fifth generation (5G)-Advanced New Radio (NR) air interface, where spatial and temporal-domain beam prediction are important use cases. With…

Artificial intelligence (AI) and machine learning (ML) models are rapidly permeating the 5G Radio Access Network (RAN), powering beam management, channel state information (CSI) feedback, positioning, and mobility prediction. However,…

AI/ML research has predominantly been driven by domains such as computer vision, natural language processing, and video analysis. In contrast, the application of AI/ML to wireless networks, particularly at the air interface, remains in its…

The 3rd Generation Partnership Project (3GPP), the standards body for mobile networks, is in the final phase of Release 19 standardization and is beginning Release 20. Artificial Intelligence/ Machine Learning (AI/ML) has brought about a…

In this article, we advocate for the design of ad hoc artificial intelligence (AI)/machine learning (ML) models to facilitate their usage in future smart infrastructures based on communication networks. To motivate this, we first review key…

This work proposes an empirical air to ground (A2G) propagation model specifically designed for cellular connected unmanned aerial vehicles (UAVs). An in depth aerial drive test was carried out within an operating Long Term Evolution (LTE)…

The transformative power of artificial intelligence (AI) and machine learning (ML) is recognized as a key enabler for sixth generation (6G) mobile networks by both academia and industry. Research on AI/ML in mobile networks has been ongoing…

Massive MIMO is one of the main features of 5G mobile radio systems. However, it often leads to high cost, size and power consumption. To overcome these issues, the use of constrained radio frequency (RF) frontends has been proposed, as…

This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. In Part I, we introduced AI and ML as well as provided a comprehensive…

Learning-based techniques such as artificial intelligence (AI) and machine learning (ML) play an increasingly important role in the development of future communication networks. The success of a learning algorithm depends on the quality and…

Will AI/ML-defined radios become a reality in the near future? In this paper, we introduce the concept of an AI/ML-defined radio - a radio architecture specifically designed to support AI/ML-based optimization and decision-making in…

The problem of estimating the parameters of a moving target in multiple-input multiple-output (MIMO) radar is considered and a new approach for estimating the moving target parameters by making use of the phase information associated with…

Phase-Based Ranging (PBR) offers several advantages for estimating distances between wirelessly connected devices, including high accuracy over large distances and the removal of the need for antenna arrays at each transceiver. This study…

Next-generation wireless networks are getting significant attention because they promise 10-factor enhancement in mobile broadband along with the potential to enable new heterogeneous services. Services include massive machine type…

To provide higher data rates, as well as better coverage, cost efficiency, security, adaptability, and scalability, the 5G and beyond 5G networks are developed with various artificial intelligence techniques. In this two-part paper, we…