Wireless Communications and Signals

A special issue of Signals (ISSN 2624-6120).

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 5260

Special Issue Editors


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Guest Editor
Department of Digital Systems, University of Thessaly, 351 31 Lamia, Greece
Interests: wireless sensor network; ad hoc network; optimization algorithms; wireless communications; Internet of Things

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Guest Editor
Department of Digital Systems, School of Technology, University of Thessaly, Geopolis, 41500 Larissa, Greece
Interests: physical computing; computational thinking; embedded systems; sensors; digital twin; educational technology; educational robotics; learning machines; remote labs; AR/VR; STE(A)M; IoT; IoE
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Digital Systems, Faculty of Technology, University of Thessaly, Larissa, Greece
Interests: mobile communications; forward error correction coding; reconfigurable (software radio) architectures; cross-layer architectures; V2V applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,                                                               

Wireless communication systems and networks play an important role in our daily life for several application domains such as smart health, transportations, precision agriculture, and Industry 4.0 (IIoT, IoT, etc.) This Special Issue of Wireless Communications and Signals aims to bring high quality internationally leading researchers, scientists, and engineers from both academia and industry to present and discuss state-of-the-art wireless networking and communication issues and to disseminate their findings. Papers should emphasize either theoretical issues or practical applications such as smart health, smart industry, smart agriculture, smart grids, smart vehicles, smart cities, etc. Therefore, the scope of the Special Issue is to highlight state-of-the-art technologies, algorithms, techniques, and architectures focusing on application domains which are vital for our society.

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

  • Wireless Sensor Networks
  • Networking and sensors
  • Ad hoc and Mesh Networks
  • Smart Sensors
  • Wireless Traffic and Routing
  • Wireless Multimedia Communications
  • IoT Communication Protocols (ZigBee, BLE, NFC, MQTT, XMPP)
  • Network Performance, QoS techniques and Reliability
  • Energy Efficient Routing in WNSs, IoT and Fog networks
  • Topology Control in WSN, IoT and Fog networks
  • Applications of Fog Computing and Networking
  • Cognitive Sensors and Radio Networks
  • Monitoring and Control in Wireless Networks
  • Resource Allocation Techniques
  • Measurements and Transmission in Wireless Networks
  • Intelligent Vehicular Systems
  • Wireless Edge Computing and Communications
  • Wireless Physical Computing Systems
  • Channel Modelling and Propagation
  • Wireless System Architectures and Protocols
  • Error Control, Detection and Estimation
  • 5G Communications
  • Signal Processing Algorithms and Techniques

Dr. Apostolos Xenakis
Dr. Konstantinos Kalovrektis
Dr. Costas Chaikalis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Signals is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wireless networks
  • signal processing and communications
  • applications
  • WSNs

Published Papers (2 papers)

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Research

13 pages, 520 KiB  
Article
Design of Adaptive Kalman Consensus Filters (a-KCF)
by Shalin Ye and Shufan Wu
Signals 2023, 4(3), 617-629; https://doi.org/10.3390/signals4030033 - 31 Aug 2023
Viewed by 809
Abstract
This paper addresses the problem of designing an adaptive Kalman consensus filter (a-KCF) which embedded in multiple mobile agents that are distributed in a 2D domain. The role of such filters is to provide adaptive estimation of the states of a dynamic linear [...] Read more.
This paper addresses the problem of designing an adaptive Kalman consensus filter (a-KCF) which embedded in multiple mobile agents that are distributed in a 2D domain. The role of such filters is to provide adaptive estimation of the states of a dynamic linear system through communication over a wireless sensor network. It is assumed that each sensing device (embedded in each agent) provides partial state measurements and transmits the information to its instant neighbors in the communication topology. An adaptive consensus algorithm is then adopted to enforce the agreement on the state estimates among all connected agents. The basis of a-KCF design is derived from the classic Kalman filtering theorem; the adaptation of the consensus gain for each local filter in the disagreement terms improves the convergence of the associated difference between the estimation and the actual states of the dynamic linear system, reducing it to zero with appropriate norms. Simulation results testing the performance of a-KCF confirm the validation of our design. Full article
(This article belongs to the Special Issue Wireless Communications and Signals)
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16 pages, 3248 KiB  
Article
DXN: Dynamic AI-Based Analysis and Optimisation of IoT Networks’ Connectivity and Sensor Nodes’ Performance
by Ihsan Lami and Alnoman Abdulkhudhur
Signals 2021, 2(3), 570-585; https://doi.org/10.3390/signals2030035 - 03 Sep 2021
Viewed by 2473
Abstract
Most IoT networks implement one-way messages from the sensor nodes to the “application host server” via a gateway. Messages from any sensor node in the network are sent when its sensor is triggered or at regular intervals as dictated by the application, such [...] Read more.
Most IoT networks implement one-way messages from the sensor nodes to the “application host server” via a gateway. Messages from any sensor node in the network are sent when its sensor is triggered or at regular intervals as dictated by the application, such as a Smart-City deployment of LoRaWAN traps/sensors for rat detection. However, these traps can, due to the nature of this application, be moved out of signal range from their original location, or obstructed by objects, resulting in under 69% of the messages reaching the gateway. Therefore, applications of this type would benefit from control messages from the “application host server” back to the sensor nodes for enhancing their performance/connectivity. This paper has implemented a cloud-based AI engine, as part of the “application host server”, that dynamically analyses all received messages from the sensor nodes and exchanges data/enhancement back and forth with them, when necessary. Hundreds of sensor nodes in various blocked/obstructed IoT network connectivity scenarios are used to test our DXN solution. We achieved 100% reporting success if access to any blocked sensor node was possible via a neighbouring node. DXN is based on DNN and Time Series models. Full article
(This article belongs to the Special Issue Wireless Communications and Signals)
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