Advances in Wireless Sensor Network Signal Processing

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 8081

Special Issue Editors


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Guest Editor
Department of Computer Science and Networks, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka-shi, Fukuoka 820-8502, Japan
Interests: wireless communications; mobile computing; RF-powered computing

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Guest Editor
School of Information and Communications Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Interests: 5G/B5G/6G; wireless networks; cyber-physical systems; blockchain; physical-layer security; Internet-of-Things
Special Issues, Collections and Topics in MDPI journals
Graduate School of Science and Engineering, Hosei University, 3-7-2 Kajino-cho, Koganei-shi, Tokyo 184-8584, Japan
Interests: Internet of Things; artificial intelligence; blockchain; information security

Special Issue Information

Dear Colleagues,

As a revolutionary information-gathering method, wireless sensor networks (WSNs) are an indispensable building block of Internet-of-Things (IoT) systems. Currently, data transmissions in WSNs are enabled by a wide variety of wireless communication technologies, such as Wi-Fi, ZigBee, LoRa, and NB-IoT. However, these radio solutions as they exist today are not yet well-established paths to satisfy the required reliability and efficiency of various IoT applications. This is due to their limited and insufficient signal processing capabilities regarding power consumption, data rate, coverage, immunity against interference, and so forth. In this context, this Special Issue aims to foster discussions about the design, implementation, evaluation, and application of emerging signal processing techniques for WSNs among practitioners, researchers, and educators. This Special Issue solicits articles addressing numerous topics, including but not limited to the following:

  • Design, development, and measurement of WSN testbeds and simulation tools;
  • Foundations of signal processing in WSNs;
  • Distributed and collaborative signal processing in WSNs;
  • Information theory, coding, and modulation in WSNs;
  • In-network signal processing in WSNs;
  • Signal processing for WSN spectrum efficiency and coexistence;
  • New WSN communication schemes including backscattering, MIMO, intelligent reflective surfaces, etc.;
  • Artificial intelligence for signal processing in WSNs;
  • Security aspects of signal processing in WSNs.

Dr. Chenglong Shao
Prof. Dr. Qinghe Du
Dr. Keping Yu
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 sensor networks
  • Internet of Things
  • signal processing
  • wireless communications
  • information transmission

Published Papers (5 papers)

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Research

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13 pages, 1093 KiB  
Article
Resource Allocation of UAV-Assisted IoT Node Secure Communication System
by Biyun Ma, Diyuan Xu, Xinyu Ren, Yide Wang and Jiaojiao Liu
Signals 2023, 4(3), 591-603; https://doi.org/10.3390/signals4030031 - 21 Aug 2023
Cited by 1 | Viewed by 814
Abstract
To balance the information security and energy harvest for massive internet-of-things (IoT) devices, an unmanned aerial vehicle (UAV)–assisted secure communication model is proposed in this paper. We extend the secure transmission model with physical layer security (PLS) to simultaneous wireless information and power [...] Read more.
To balance the information security and energy harvest for massive internet-of-things (IoT) devices, an unmanned aerial vehicle (UAV)–assisted secure communication model is proposed in this paper. We extend the secure transmission model with physical layer security (PLS) to simultaneous wireless information and power transfer (SWIPT) technology and optimize the UAV trajectory, transmission power, and power splitting ratio (PSR). The nonconvex object function is decomposed into three subproblems. Then a robust iterative suboptimal algorithm based on the block coordinate descent (BCD) method is proposed to solve the subproblems. Numerical simulation results are provided to show the effectiveness of the proposed method. These results clearly illustrate that our resource allocation schemes surpass baseline schemes in terms of both transmit power and ratio of harvesting energy, while maintaining an approximately instantaneous secrecy rate. Full article
(This article belongs to the Special Issue Advances in Wireless Sensor Network Signal Processing)
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17 pages, 1194 KiB  
Article
Extracting Communication, Ranging and Test Waveforms with Regularized Timing from the Chaotic Lorenz System
by Aubrey N. Beal
Signals 2023, 4(3), 507-523; https://doi.org/10.3390/signals4030027 - 11 Jul 2023
Cited by 1 | Viewed by 1056
Abstract
We present an algorithm for extracting basis functions from the chaotic Lorenz system along with timing and bit-sequence statistics. Previous work focused on modifying Lorenz waveforms and extracting the basis function of a single state variable. Importantly, these efforts initiated the development of [...] Read more.
We present an algorithm for extracting basis functions from the chaotic Lorenz system along with timing and bit-sequence statistics. Previous work focused on modifying Lorenz waveforms and extracting the basis function of a single state variable. Importantly, these efforts initiated the development of solvable chaotic systems with simple matched filters, which are suitable for many spread spectrum applications. However, few solvable chaotic systems are known, and they are highly dependent upon an engineered basis function. Non-solvable, Lorenz signals are often used to test time-series prediction schemes and are also central to efforts to maximize spectral efficiency by joining radar and communication waveforms. Here, we provide extracted basis functions for all three Lorenz state variables, their timing statistics, and their bit-sequence statistics. Further, we outline a detailed algorithm suitable for the extraction of basis functions from many chaotic systems such as the Lorenz system. These results promote the search for engineered basis functions in solvable chaotic systems, provide tools for joining radar and communication waveforms, and give an algorithmic process for modifying chaotic Lorenz waveforms to quantify the performance of chaotic time-series forecasting methods. The results presented here provide engineered test signals compatible with quantitative analysis of predicted amplitudes and regular timing. Full article
(This article belongs to the Special Issue Advances in Wireless Sensor Network Signal Processing)
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21 pages, 6060 KiB  
Article
Vehicular Visible Light Communication for Intersection Management
by M. A. Vieira, M. Vieira, P. Louro, P. Vieira and A. Fantoni
Signals 2023, 4(2), 457-477; https://doi.org/10.3390/signals4020024 - 16 Jun 2023
Cited by 2 | Viewed by 1359
Abstract
An innovative treatment for congested urban road networks is the split intersection. Here, a congested two-way–two-way traffic light-controlled intersection is transformed into two lighter intersections. By reducing conflict points and improving travel time, it facilitates smoother flow with less driver delay. We propose [...] Read more.
An innovative treatment for congested urban road networks is the split intersection. Here, a congested two-way–two-way traffic light-controlled intersection is transformed into two lighter intersections. By reducing conflict points and improving travel time, it facilitates smoother flow with less driver delay. We propose a visible light communication system based on Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Infrastructure-to-Vehicle (I2V) communications able to safely manage vehicles crossing through an intersection, leveraging Edge of Things (EoT) facilities. Headlights, street lamps, and traffic signals are used by connected vehicles to communicate with one another and with infrastructure. Through internally installed Driver Agents, an Intersection Manager coordinates traffic flow and interacts with vehicles. For the safe passage of vehicles across intersections, request/response mechanisms and time and space relative pose concepts are used. A virtual scenario is proposed, and a “mesh/cellular” hybrid architecture used. Light signals are emitted by transmitters by encoding, modulating, and converting data. Optical sensors with light-filtering properties are used as receivers and decoders. The VLC request/response concept uplink and downlink communication between the infrastructure and the vehicles is tested. Based on the results, the short-range mesh network provides a secure communication path between street lamp controllers and edge computers through neighbor traffic light controllers that have active cellular connections, as well as peer-to-peer communication, allowing V-VLC ready cars to exchange information. Full article
(This article belongs to the Special Issue Advances in Wireless Sensor Network Signal Processing)
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18 pages, 1002 KiB  
Article
Extended Kalman Filter Design for Tracking Time-of-Flight and Clock Offsets in a Two-Way Ranging System
by Sharanya Srinivas, Andrew Herschfelt and Daniel W. Bliss
Signals 2023, 4(2), 439-456; https://doi.org/10.3390/signals4020023 - 15 Jun 2023
Cited by 1 | Viewed by 1006
Abstract
As radio frequency (RF) hardware continues to improve, two-way ranging (TWR) has become a viable approach for high-precision ranging applications. The precision of a TWR system is fundamentally limited by estimates of the time offset T between two platforms and the time delay [...] Read more.
As radio frequency (RF) hardware continues to improve, two-way ranging (TWR) has become a viable approach for high-precision ranging applications. The precision of a TWR system is fundamentally limited by estimates of the time offset T between two platforms and the time delay τ of a signal propagating between them. In previous work, we derived a family of optimal “one-shot” joint delay–offset estimators and demonstrated that they reduce to a system of linear equations under reasonable assumptions. These estimators are simple and computationally efficient but are also susceptible to channel impairments that obstruct one or more measurements. In this work, we formulate an extended Kalman filter (EKF) for this class of estimators that specifically addresses this limitation. Unlike a generic KF approach, the proposed solution specifically integrates the estimation process to minimize the computational complexity. We benchmark the proposed first- and second-order EKF solutions against the existing one-shot estimators in a MATLAB Monte Carlo simulation environment. We demonstrate that the proposed solution achieves comparable estimation performance and, in the case of the second-order solution, reduces the computation time by an order of magnitude. Full article
(This article belongs to the Special Issue Advances in Wireless Sensor Network Signal Processing)
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Review

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27 pages, 1651 KiB  
Review
A Survey on Optimal Channel Estimation Methods for RIS-Aided Communication Systems
by Stamatia F. Drampalou, Nikolaos I. Miridakis, Helen C. Leligou and Panagiotis A. Karkazis
Signals 2023, 4(1), 208-234; https://doi.org/10.3390/signals4010012 - 09 Mar 2023
Cited by 3 | Viewed by 2657
Abstract
Next-generation wireless communications aim to utilize mmWave/subTHz bands. In this regime, signal propagation is vulnerable to interferences and path losses. To overcome this issue, a novel technology has been introduced, which is called reconfigurable intelligent surface (RIS). RISs control digitally the reflecting signals [...] Read more.
Next-generation wireless communications aim to utilize mmWave/subTHz bands. In this regime, signal propagation is vulnerable to interferences and path losses. To overcome this issue, a novel technology has been introduced, which is called reconfigurable intelligent surface (RIS). RISs control digitally the reflecting signals using many passive reflector arrays and implement a smart and modifiable radio environment for wireless communications. Nonetheless, channel estimation is the main problem of RIS-assisted systems because of their direct dependence on the system architecture design, the transmission channel configuration and methods used to compute channel state information (CSI) on a base station (BS) and RIS. In this paper, a concise survey on the up-to-date RIS-assisted wireless communications is provided and includes the massive multiple input-multiple output (mMIMO), multiple input-single output (MISO) and cell-free systems with an emphasis on effective algorithms computing CSI. In addition, we will present the effectiveness of the algorithms computing CSI for different communication systems and their techniques, and we will represent the most important ones. Full article
(This article belongs to the Special Issue Advances in Wireless Sensor Network Signal Processing)
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