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Mathematics
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Advanced Algorithms in Wireless Communication and Internet of Things (IoT)
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Advanced Algorithms in Wireless Communication and Internet of Things (IoT)

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Network Science".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 4599

Special Issue Editors

Dr. Farag M. Sallabi

E-Mail Website
Guest Editor
College of Information Technology, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
Interests: network protocols; real-time systems; Internet of Things; machine learning algorithms; wireless communications; cryptography; energy efficient routing; channel estimation; network optimization; channel coding; mobile computing
Dr. Mohammad Hayajneh

E-Mail Website
Guest Editor
College of Information Technology, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
Interests: MIMO packet scheduling; power and rate control algorithms; application of game theory to power and rate control algorithms; space-time codes; wireless networks; sensor networks; resource allocation and pricing in wireless data networks; performance analysis and modeling of OFDMA based wireless networks

Special Issue Information

Dear Colleagues,

The development of wireless communications and the Internet of Things have advanced considerably in recent years, opening the doors for a wide range of applications and services across many different industries. This advancement has posed significant challenges to the current Internet architecture, which has motivated researchers to revisit the existing protocols and algorithms to develop new ones that suit the latest applications and services requirements. This Special Issue focuses on advanced wireless and Internet of Things (IoT) algorithms that improve the efficiency, reliability, performance, and security of wireless communications and IoT. 

This Special Issue aims to explore and disseminate the latest research in advanced algorithms used in wireless communication and IoT, such as machine learning algorithms for predictive analytics and anomaly detection, network optimization algorithms for efficient routing and resource allocation, and cryptographic algorithms for secure communication. Other important topics include channel estimation and equalization techniques for improving signal quality, modulation and coding schemes for reliable data transmission, and hybrid analog–digital beamforming algorithms for enhancing the efficiency of wireless communication. We accept research and review articles covering a diverse range of topics, including but not limited to:

  1. Energy-efficient routing algorithms for IoT devices.
  2. Machine learning-based anomaly detection and predictive maintenance in IoT networks.
  3. Cryptographic algorithms for secure communication in IoT.
  4. Hybrid analog–digital beamforming for efficient wireless communication.
  5. Channel estimation and equalization techniques for improving signal quality.
  6. Modulation and coding schemes for reliable data transmission in IoT.
  7. Network optimization algorithms for efficient resource allocation in wireless networks and IoT.
  8. Distributed algorithms for data processing in IoT networks.
  9. Game theory-based approaches for wireless network resource allocation.
  10. Multi-objective optimization for wireless communication in IoT.
  11. Sensor data fusion and calibration.
  12. Real-time data stream processing.

Dr. Farag M. Sallabi
Dr. Mohammad Hayajneh
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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

  • Internet of Things
  • machine learning algorithms
  • advanced algorithms
  • wireless communications
  • cryptography
  • energy efficient routing
  • channel estimation
  • network optimization
  • modulation
  • channel coding

Published Papers (6 papers)

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Research

12 pages, 750 KiB  
Article
Performance Analysis of RIS-Assisted SatComs Based on a ZFBF and Co-Phasing Scheme
by Minchae Jung, Taehyoung Kim and Hyukmin Son
Mathematics 2024, 12(8), 1257; https://0-doi-org.brum.beds.ac.uk/10.3390/math12081257 - 21 Apr 2024
Viewed by 201
Abstract
In recent high-throughput satellite communication (SatCom) systems, the use of reconfigurable intelligent surfaces (RISs) has emerged as a promising solution to improve spectral efficiency and extend coverage in areas with limited terrestrial network access. However, the RIS may amplify the inter-beam interference (IBI) [...] Read more.
In recent high-throughput satellite communication (SatCom) systems, the use of reconfigurable intelligent surfaces (RISs) has emerged as a promising solution to improve spectral efficiency and extend coverage in areas with limited terrestrial network access. However, the RIS may amplify the inter-beam interference (IBI) caused by multibeam transmission at the satellite, and multiple RISs can also cause inter-RIS interference (IRI) to terrestrial users. In this paper, the performance of the RIS-assisted SatCom system is asymptotically analyzed for both full and partial channel state information (CSI) scenarios. In particular, zero-forcing beamforming is considered as the active beamforming for data transmission, while the co-phasing scheme is considered as the passive beamforming for RIS reflection. Based on the asymptotic analyses, deterministic active and passive beamforming techniques using partial CSI are proposed that can gradually eliminate both IBI and IRI, ultimately achieving ideal performance. Simulation results validate the accuracy of asymptotic analyses and demonstrate the superiority of deterministic active and passive beamforming techniques using partial CSI. The simulation results also confirm that the proposed beamforming can achieve approximately 92.8% of the ideal performance, even though it only requires partial CSI. Full article
(This article belongs to the Special Issue Advanced Algorithms in Wireless Communication and Internet of Things (IoT))
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30 pages, 1967 KiB  
Article
HCEL: Hybrid Clustering Approach for Extending WBAN Lifetime
by Heba Helal, Farag Sallabi, Mohamed A. Sharaf, Saad Harous, Mohammad Hayajneh and Heba Khater
Mathematics 2024, 12(7), 1067; https://0-doi-org.brum.beds.ac.uk/10.3390/math12071067 - 02 Apr 2024
Viewed by 509
Abstract
Wireless body area networks (WBANs) have emerged as a promising solution for addressing challenges faced by elderly individuals, limited medical facilities, and various chronic medical conditions. WBANs consist of wearable sensing and computing devices interconnected through wireless communication channels, enabling the collection and [...] Read more.
Wireless body area networks (WBANs) have emerged as a promising solution for addressing challenges faced by elderly individuals, limited medical facilities, and various chronic medical conditions. WBANs consist of wearable sensing and computing devices interconnected through wireless communication channels, enabling the collection and transmission of vital physiological data. However, the energy constraints of the battery-powered sensor nodes in WBANs pose a significant challenge to ensuring long-term operational efficiency. Two-hop routing protocols have been suggested to extend the stability period and maximize the network’s lifetime. These protocols select appropriate parent nodes or forwarders with a maximum of two hops to relay data from sensor nodes to the sink. While numerous energy-efficient routing solutions have been proposed for WBANs, reliability has often been overlooked. Our paper introduces an energy-efficient routing protocol called a Hybrid Clustering Approach for Extending WBAN Lifetime (HCEL) to address these limitations. HCEL leverages a utility function to select parent nodes based on residual energy (RE), proximity to the sink node, and the received signal strength indicator (RSSI). The parent node selection process also incorporates an energy threshold value and a constrained number of serving nodes. The main goal is to extend the overall lifetime of all nodes within the network. Through extensive simulations, the study shows that HCEL outperforms both Stable Increased Throughput Multihop Protocol for Link Efficiency (SIMPLE) and Energy-Efficient Reliable Routing Scheme (ERRS) protocols in several key performance metrics. The specific findings of our article highlight the superior performance of HCEL in terms of increased network stability, extended network lifetime, reduced energy consumption, improved data throughput, minimized delays, and improved link reliability. Full article
(This article belongs to the Special Issue Advanced Algorithms in Wireless Communication and Internet of Things (IoT))
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15 pages, 2094 KiB  
Article
Optimal Design of Group Orthogonal Phase-Coded Waveforms for MIMO Radar
by Tianqu Liu, Jinping Sun, Guohua Wang, Xianxun Yao and Yaqiong Qiao
Mathematics 2024, 12(6), 903; https://0-doi-org.brum.beds.ac.uk/10.3390/math12060903 - 19 Mar 2024
Viewed by 530
Abstract
Digital radio frequency memory (DRFM) has emerged as an advanced technique to achieve a range of jamming signals, due to its capability to intercept waveforms within a short time. multiple-input multiple-output (MIMO) radars can transmit agile orthogonal waveform sets for different pulses to [...] Read more.
Digital radio frequency memory (DRFM) has emerged as an advanced technique to achieve a range of jamming signals, due to its capability to intercept waveforms within a short time. multiple-input multiple-output (MIMO) radars can transmit agile orthogonal waveform sets for different pulses to combat DRFM-based jamming, where any two groups of waveform sets are also orthogonal. In this article, a group orthogonal waveform optimal design model is formulated in order to combat DRFM-based jamming by flexibly designing waveforms for MIMO radars. Aiming at balancing the intra- and intergroup orthogonal performances, the objective function is defined as the weighted sum of the intra- and intergroup orthogonal performance metrics. To solve the formulated model, in this article, a group orthogonal waveform design algorithm is proposed. Based on a primal-dual-type method and proper relaxations, the proposed algorithm transforms the original problem into a series of simple subproblems. Numerical results demonstrate that the obtained group orthogonal waveforms have the ability to flexibly suppress DRFM-based deceptive jamming, which is not achievable using p-majorization–minimization (p-MM) and primal-dual, two of the most advanced orthogonal waveform design algorithms. Full article
(This article belongs to the Special Issue Advanced Algorithms in Wireless Communication and Internet of Things (IoT))
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19 pages, 764 KiB  
Article
UDCO-SAGiMEC: Joint UAV Deployment and Computation Offloading for Space–Air–Ground Integrated Mobile Edge Computing
by Yinghao Xu, Fukang Deng and Jianshan Zhang
Mathematics 2023, 11(18), 4014; https://0-doi-org.brum.beds.ac.uk/10.3390/math11184014 - 21 Sep 2023
Viewed by 911
Abstract
Computation-intensive applications offloading is challenging, especially in the designated regions where communication infrastructure is absent or compromised. In this paper, we present a Space–Air–Ground integrated Mobile Edge Computing (SAGiMEC) system for these regions to provide quality computational services, where the unmanned aerial vehicles [...] Read more.
Computation-intensive applications offloading is challenging, especially in the designated regions where communication infrastructure is absent or compromised. In this paper, we present a Space–Air–Ground integrated Mobile Edge Computing (SAGiMEC) system for these regions to provide quality computational services, where the unmanned aerial vehicles (UAVs) act as in-fight edge servers to provide low-latency edge computing and the satellite provides resident cloud computing. A joint optimization problem is formulated considering UAV deployment, ground device (GD) access, and computation offloading to minimize the system average response latency. To cope with the problem’s complexity, we propose a Particle Swarm Optimization (PSO) and Greedy Strategy (GS)-based algorithm (PSO&GS) to obtain an approximate optimal solution. Extensive simulations validate the convergence of the proposed algorithm. Numerical results show that the proposed approach has excellent convergence, and the system average response latency is about 0.65x–0.85x that of the benchmark algorithm. Full article
(This article belongs to the Special Issue Advanced Algorithms in Wireless Communication and Internet of Things (IoT))
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18 pages, 7408 KiB  
Article
Deep Convolutional and Recurrent Neural-Network-Based Optimal Decoding for RIS-Assisted MIMO Communication
by Md Habibur Rahman, Mohammad Abrar Shakil Sejan, Md Abdul Aziz, Dong-Sun Kim, Young-Hwan You and Hyoung-Kyu Song
Mathematics 2023, 11(15), 3397; https://0-doi-org.brum.beds.ac.uk/10.3390/math11153397 - 03 Aug 2023
Cited by 2 | Viewed by 930
Abstract
The reconfigurable intelligent surface (RIS) is one of the most innovative and revolutionary technologies for increasing the effectiveness of wireless systems. Deep learning (DL) is a promising method that can enhance system efficacy using powerful tools in RIS-based environments. However, the lack of [...] Read more.
The reconfigurable intelligent surface (RIS) is one of the most innovative and revolutionary technologies for increasing the effectiveness of wireless systems. Deep learning (DL) is a promising method that can enhance system efficacy using powerful tools in RIS-based environments. However, the lack of extensive training of the DL model results in the reduced prediction of feature information and performance failure. Hence, to address the issues, in this paper, a combined DL-based optimal decoding model is proposed to improve the transmission error rate and enhance the overall efficiency of the RIS-assisted multiple-input multiple-output communication system. The proposed DL model is comprised of a 1-dimensional convolutional neural network (1-D CNN) and a gated recurrent unit (GRU) module where the 1-D CNN model is employed for the extraction of features from the received signal with further process over the configuration of different layers. Thereafter, the processed data are used by the GRU module for successively retrieving the transmission signal with a minimal error rate and accelerating the convergence rate. It is initially trained offline using created OFDM data sets, after which it is used online to track the channel and extract the transmitted data. The simulation results show that the proposed network performs better than the other technique that was previously used in terms of bit error rate and symbol error rate. The outcomes of the model demonstrate the suitability of the proposed model for use with the next-generation wireless communication system. Full article
(This article belongs to the Special Issue Advanced Algorithms in Wireless Communication and Internet of Things (IoT))
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20 pages, 3415 KiB  
Article
Energy-Efficient Resource Allocation for D2D-V2V Communication with Load Balancing
by Jie Bi, Xizhong Qin and Zhenhong Jia
Mathematics 2023, 11(13), 2848; https://0-doi-org.brum.beds.ac.uk/10.3390/math11132848 - 25 Jun 2023
Cited by 1 | Viewed by 843
Abstract
The significance of vehicle-to everything (V2X) communication in ensuring road safety is undeniable. In addition, real-time vehicle communication requires an ample amount of spectrum resources. However, the existing spectrum resources are seriously scarce, and the utilization rate is not high, leading to high [...] Read more.
The significance of vehicle-to everything (V2X) communication in ensuring road safety is undeniable. In addition, real-time vehicle communication requires an ample amount of spectrum resources. However, the existing spectrum resources are seriously scarce, and the utilization rate is not high, leading to high delays in V2X communication and other unfavorable factors in the case of fast-moving vehicles, bringing great safety risks to driving. Load balancing is one of the most effective methods to improve spectrum utilization. However, the existing load balancing schemes merely focus on static conditions, with a lack of joint scheduling schemes, which cannot support the communication framework of dynamic V2X. To address both of these issues, in this paper, a new communication method is proposed. In addition, this paper studies a joint load balancing scheme of mobility vehicle-to-vehicle (V2V) and user association under incomplete channel state information (CSI) and realizes the load balancing management of a cross-cell V2X network. An algorithm combining power control and resource allocation mode selection is proposed. In particular, according to different coverage areas, different allocation algorithms are adopted to maximize the overall system efficiency. The simulation results show that this strategy can maintain low latency and effectively improve the system energy efficiency of vehicle users. Full article
(This article belongs to the Special Issue Advanced Algorithms in Wireless Communication and Internet of Things (IoT))
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