Signal Processing in Radio Systems

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1242

Special Issue Editors


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Guest Editor
Instituto de Telecomunicações, ESTGA—University of Aveiro, 3750-127 Águeda, Portugal
Interests: radar; signal processing; vital-signs acquisition
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Instituto de Telecomunicações, Universidade de Aveiro, 3810-193 Aveiro, Portugal
Interests: antenna design for telecommunications; wireless power transfer; sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Signal processing plays a pivotal role in the functionality and enhancement of radio systems, encompassing a wide range of applications such as telecommunications, broadcasting, radar, and navigation systems. These technologies rely on advanced signal processing techniques to ensure efficient communication, accurate data transmission, and reliable system performance. For instance, in modern telecommunications, signal processing is crucial for modulating and demodulating signals, managing bandwidth, and mitigating interference. In radar systems, signal processing enables accurate target detection and tracking, while in navigation systems, it ensures precise positioning and timing. The continuous advancement of signal processing methodologies has led to significant improvements in the quality, speed, and efficiency of radio systems. From enhancing mobile network capacity and reliability in 5G and beyond to improving the resolution and accuracy of radar imaging, the applications of signal processing are vast and varied.

This Special Issue aims to provide a comprehensive overview of the state-of-the-art in signal processing for radio systems, bringing together cutting-edge research and fostering a deeper understanding of the challenges and opportunities in this field.

Research topics of interest include (but are not limited to) the following:

  • Signal Processing Techniques for Communication Systems:
    • Modulation and demodulation techniques;
    • Channel coding and decoding;
    • Signal detection and estimation;
    • MIMO and beamforming technologies.
  • Radio Frequency (RF) System Design and Optimization:
    • RF front-end design and optimization;
    • Spectrum management and interference mitigation;
    • RF system calibration and testing.
  • Emerging Technologies and Applications:
    • Cognitive radio and dynamic spectrum access;
    • Software-defined radio (SDR);
    • Internet of Things (IoT) and machine-to-machine (M2M) communication;
    • 5G and beyond wireless communication systems.
  • Signal Processing for Radar and Navigation Systems:
    • Radar signal processing and target detection;
    • Positioning and navigation algorithms;
    • Synthetic aperture radar (SAR) and inverse SAR.
  • Advanced Signal Processing Techniques:
    • Adaptive filtering and noise reduction;
    • Machine learning and artificial intelligence in signal processing;
    • Compressive sensing and sparse signal recovery;
    • Signal processing for secure communications.
  • Measurement, Monitoring, and Evaluation:
    • Signal quality measurement and monitoring;
    • Performance evaluation and benchmarking;
    • Standardization and regulatory aspects.

Dr. Daniel Filipe Albuquerque
Dr. Pedro Pinho
Guest Editors

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Keywords

  • signal processing
  • radio systems
  • communication systems
  • channel coding
  • MIMO technologies
  • beamforming
  • RF system design
  • spectrum management
  • interference mitigation
  • cognitive radio
  • software-defined radio (SDR)
  • Internet of Things (IoT)
  • machine-to-machine (M2M) communication
  • radar signal processing
  • navigation systems
  • synthetic aperture radar (SAR)
  • compressive sensing
  • sparse signal recovery
  • secure communications
  • signal quality measurement
  • performance evaluation
  • standardization
  • RF calibration
  • dynamic spectrum access
  • target detection
  • positioning algorithms

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Published Papers (1 paper)

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Research

17 pages, 8908 KiB  
Article
Detection of Random Body Movements Using Clustering-Based Methods in Bioradar Systems
by André Rouco, Filipe Silva, Beatriz Soares, Daniel Albuquerque, Carolina Gouveia, Susana Brás and Pedro Pinho
Information 2024, 15(10), 584; https://doi.org/10.3390/info15100584 - 25 Sep 2024
Cited by 1 | Viewed by 996
Abstract
Bioradar systems, in general, refer to radar systems used for the detection of vital signs. These systems hold significant importance across various sectors, particularly in healthcare and surveillance, due to their capacity to provide contactless solutions for monitoring physiological functions. In these applications, [...] Read more.
Bioradar systems, in general, refer to radar systems used for the detection of vital signs. These systems hold significant importance across various sectors, particularly in healthcare and surveillance, due to their capacity to provide contactless solutions for monitoring physiological functions. In these applications, the primary challenge lies in the presence of random body movements (BMs), which can significantly hinder the accurate detection of vital signs. To compensate the affected signal in a timely manner, portions of BM must be correctly identified. To address this challenge, this work proposes a solution based on the Density-Based Spatial Clustering of Applications with Noise (DBScan) algorithm to detect the occurrence of BM in radar signals. The main idea of this algorithm is to cluster the radar samples, aiming to differentiate between segments in which the subject is stable and segments in which the subject is moving. Using a dataset involving eight subjects, the proposed method successfully detects three types of body movements: chest movement, body rotation, and arm movement. The achieved results are promising, with F1 scores of 0.83, 0.73, and 0.8, respectively, for the detection of each specific movement type. Full article
(This article belongs to the Special Issue Signal Processing in Radio Systems)
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