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Call for papers: Emerging Trends, Issues, and Challenges in Information Fusion and Its Applications for Massive RF Data in Smart Environments

In recent years, many organizations are working toward the fulfillment of interconnected and intelligent smart environments through encompassing a multitude of sensory modalities. The availability of such modalities entails that the latest importance in using Radio Frequency (RF) signals for the smart environment application is not only to design and implement new methods and devices to sense and fuse more information from multimode sensors, but also to fully exploit new efficient signal processing methods to handle the collected massive RF data. In this circumstance, the latest researches find that it is important to handle the challenges that arise in information fusion and its applications for massive RF data. Also, empowered by the development of advanced signal processing theory and artificial intelligence, RF signals can be used to perform more complex tasks in smart environments to improve the quality of life.

This special issue aims to bring together recent advancements, challenges, and new opportunities in information fusion and its applications for massive RF data in smart environments. In particular, we welcome studies on building a bridge between the RF signal and the smart environment, leveraging new signal processing methods for information fusion by using the optimization theory, random process theory, equation theory, number theory, etc.

The topics of interest include, but are not limited to:

  • Implementation of massive RF signals (e.g., the Wi-Fi/802.11x, ultra-wide bandwidth, radio frequency identification, Bluetooth, near-field communication, LTE, 5G/B5G, TV signals, etc) in smart environments
  • Information fusion based on advanced signal processing theory (e.g., the particle filter, Bayesian inference, multi-objective decision, game theory, etc)
  • Information fusion based on artificial intelligence (e.g., the neural network, genetic algorithm, fuzzy logic, etc)
  • Information fusion-based feature learning, extraction, analysis, selection, and fusion for massive RF data in smart environments
  • Information fusion for capturing, storing, processing, and analyzing massive RF data in smart environments
  • Performance demonstrations, prototyping, and field-tests of information fusion systems
  • Antenna, device, and waveform designs for information fusion systems
  • Applications and case studies of information fusion for massive RF data in smart environments

Important Dates (tentative)
Manuscripts due: July 1, 2021
Review results and decision notification: September 1, 2021
Revised manuscripts due: October 1, 2021
Final acceptance notification: November 1, 2021
Publication date: January 1, 2022

Lead Guest Editor
Mu Zhou, Chongqing University of Posts and Telecommunications, China

Guest Editors
Chengpeng Hao, Chinese Academy of Sciences, China
Jianxin Li, Deakin University, Australia
Ying-Ren Chien, National Ilan University, Taiwan
Hongying Meng, Brunel University London, UK
Xin Ge, Broadcom Corporation, USA


Submission Instructions
Before submitting your manuscript, please ensure you have carefully read the Instructions for Authors for EURASIP Journal on Advances in Signal Processing. The complete manuscript should be submitted through the EURASIP Journal on Advances in Signal Processing submission system. To ensure that you submit to the correct special issue please select the appropriate section in the drop-down menu upon submission. In addition, indicate within your cover letter that you wish your manuscript to be considered as part of the special issue on 'Emerging Trends, Issues, and Challenges in Information Fusion and Its Applications for Massive RF Data in Smart Environments'. All submissions will undergo rigorous peer review and accepted articles will be published within the journal as a collection.

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