Special Issue on Software-Defined Radios for Artificial Intelligence and Internet of Things

Due to the proliferation of global connectivity in our everyday lives, we have seen a dramatic transformation in wireless communication. The invention of wireless communication in the 1960s has spawned a variety of applications. With the advancement of wireless standards, highly reconfigurable architectures have become increasingly popular, thus paving the way for Software-Defined Radios (SDRs). SDRs overcome traditional radio architectures challenges by implementing different radio features in software. With a SDR, one can eliminate the problems associated with traditional systems since it uses the middleware layer, or software layer, to integrate all the devices in an IoT network and their control and management functions.

Researchers can now work at the physical layer while implementing Internet of Things (IoT) applications, making it easier to connect and share data among devices. However, novel approaches must be devised to store and analyze large amounts of data to improve and manage the networks performance. In conjunction with IoT, Artificial Intelligence (AI) offers a highly efficient way to transform a device into an intelligent machine and automate decisions with little or no human intervention.

This Special Issue invites review articles to show the recent advancements in SDR covering standalone SDR, SDR-IoT, SDR-AI, or SDR-IoT integrated AI works. This issue also welcomes high-quality research articles proposing novel architectures that meet the demands of the industry and other interdisciplinary domains. The research articles submitted in this issue can be based on simulation or measurement results.

Potential topics include but are not limited to the following:

SDR transceivers: SDR front-end advancements, performance evaluation, circuit and chip design, simulations, measurements, applications

SDR-IoT integrated architectures: Sensors and actuators, internet gateways and data acquisition systems preprocessing, cloud or data center analysis

SDR-IoT Applications: healthcare, agriculture, railways, crime investigations, underwater communication, education, unmanned aerial vehicles

AI models/methods for SDR: artificial neural networks, convolutional neural networks, decision trees, support vector machines, kernel machines, residual learning, generative adversarial networks, fuzzy models, evolutionary methods (evolutionary algorithms and swarm intelligence)

 AI Hardware: AI design, graphics processing unit, hardware architecture, Field programmable gate arrays (FPGAs), Application-specific integrated circuits (ASICs), quantum computing

SDR-AI applications: wireless machine learning, digital signal processing, high-performance computing, medical sector, drone surveillance, construction, unmanned aerial vehicles, satellite communication, industry

SDR-AI-IoT integrated architectures: design, analysis, performance, applications 

Important Deadlines:

Manuscript Submission Deadline: 15^th October 2022

Authors Notification Date: 31^st December 2022

Revised Papers Due Date: 31^st January 2023

Final notification Date: 28^th February 2023 

Guest Editors:

Dr. Shilpa Mehta, Auckland University of Technology, Auckland, New Zealand

Email: shilpa.mehta@aut.ac.nz 

A/Prof. Xue Jun Li, Auckland University of Technology, Auckland, New Zealand  

Email:  xuejun.li@aut.ac.nz 

A/Prof. Massimo Donelli, University of Trento, Trento, Italy

Email: massimo.donelli@unitn.it 

Prof. Mohamed Lashab, University of Larbi Ben M’hidi, Oum El Bouaghi, Algeria

Email: lashab.mohamed@univ-oeb.dz