Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Sustainable Solutions for 6G-Enabled Internet of Things Networks

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Related Special Issue
Published Papers

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (25 June 2023) | Viewed by 31726

Share This Special Issue

Special Issue Editors

Dr. Wali Ullah Khan

E-Mail Website1 Website2
Guest Editor

Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, 1855 Luxembourg, Luxembourg
Interests: convex/nonconvex optimizations; wireless communication; 5G/6G; ambient backscatter communications; intelligent reconfigurable surfaces; artificial intelligence/machine learning; Internet of Things
Special Issues, Collections and Topics in MDPI journals

Dr. Khaled Rabie

E-Mail Website
Guest Editor

Department of Engineering, Manchester Metropolitan University, Manchester M15GD, UK
Interests: wireless communications; IoT; 6G; smart manufacturing
Special Issues, Collections and Topics in MDPI journals

Dr. Belal Alsinglawi

E-Mail Website1 Website2
Guest Editor

School of Computer, Data and Mathematical Sciences, Western Sydney University, Rydalmere 2116, Australia
Interests: Internet of Things; machine learning; cybersecurity; health analytics; indoor positioning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The upcoming sixth-generation (6G) communication systems will continue to use high frequencies with much higher data rates, massive connectivity, and extremely low latency. Given the heterogeneity and densification of the Internet of Things (IoT), 6G systems may need to be extended to modern communication technologies for IoT applications. Some of these technologies include Intelligent Reconfigurable Surfaces (IRS), Non-orthogonal Multiple Access (NOMA), Ambient Backscatter Communication (AmBC), Artificial Intelligence/ Machine Learning (AI/ML), and Terahertz/ Millimeter-wave (THz/mmWave) communications. These emerging technologies will generate new knowledge and understanding, accelerating discovery and innovation in 6G-enabled IoT networks. Moreover, each of these efforts is designed to amplify the intrinsically multidisciplinary nature of the emerging field of IoT in the 6G era. The 6G-enabled IoT will establish theoretical, technical, and ethical frameworks that will be applied for tackling many challenges in IoT, advancing technology for humanity.

This Special Issue aims to gather recent advances and novel contributions from academic researchers and industry practitioners in the novel area of sustainable solutions for 6G-enabled IoT networks in order to fully leverage the potential capabilities and opportunities brought by this area. Topics of interests include, but are not limited to, the following:

Network architecture for 6G-enabled IoT;
Advance signal processing for 6G-enabled IoT;
AI/ML techniques for 6G-enabled IoT;
Optimal resource allocation and interference management frameworks for 6G-enabled IoT;
IRS/AmBC for 6G-enabled IoT;
NOMA techniques for 6G-enabled IoT;
Security and reliability for 6G-enabled IoT;
THz/mmWave for 6G-enabled IoT;
Edge/cloud computing for 6G-enabled IoT;
Energy harvesting techniques for 6G-enabled IoT;
6G-enabled IoT applications in unmanned aerial vehicles (UAV), vehicle to everything (V2X), device to device, and satellite communications;
Testbeds/experimentation for prototyping of 6G-enabled IoT.

Dr. Wali Ullah Khan
Dr. Khaled Rabie
Dr. Belal Alsinglawi
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. Sensors 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

6G
Internet of Things
intelligent reconfigurable surfaces
ambient backscatter communication
terahertz/millimeter communications
resource optimization
signal processing
artificial intelligence/machine learning
non-orthogonal multiple access
wireless communications

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Related Special Issue

Sustainable Solutions for 6G-Enabled Internet of Things Networks—2nd Edition in Sensors

Published Papers (13 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

16 pages, 686 KiB

Open AccessArticle

Robust Resource Control Based on AP Selection in 6G-Enabled IoT Networks

by Ashu Taneja, Ali Alqahtani, Nitin Saluja and Nayef Alqahtani

Sensors 2023, 23(15), 6788; https://doi.org/10.3390/s23156788 - 29 Jul 2023

Viewed by 1194

Abstract

The diverse application vertices of internet-of-things (IoT) including internet of vehicles (IoV), industrial IoT (IIoT) and internet of drones things (IoDT) involve intelligent communication between the massive number of objects around us. This digital transformation strives for seamless data flow, uninterrupted communication capabilities, low latency and ultra-high reliability. The limited capabilities of fifth generation (5G) technology have given way to sixth generation (6G) wireless technology. This paper presents a dynamic cell-free framework for a 6G-enabled IoT network. A number of access points (APs) are distributed over a given geographical area to serve a large number of user nodes. A pilot-based AP selection (PBAS) algorithm is proposed, which offers robust resource control through AP selection based on pilots. Selecting a subset of APs against all APs for each user node results in improved performance. In this paper, the performance of the proposed transmission model is evaluated for the achieved data rate and spectral efficiency using the proposed algorithm. It is shown that the proposed PBAS algorithm improves the spectral efficiency by

22 %

at the cell-edge and

1.5 %

at the cell-center. A comparison of the different combining techniques used at different user locations is also provided, along with the mathematical formulations. Finally, the proposed model is compared with two other transmission models for performance evaluation. It is observed that the spectral efficiency achieved by an edge node with the proposed scheme is 5.3676 bits/s/Hz, compared to 0.756 bits/s/Hz and 1.0501 bits/s/Hz, attained with transmission schemes 1 and 2, respectively. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

29 pages, 661 KiB

Open AccessArticle

Iterative List Patterned Reed-Muller Projection Detection-Based Packetized Unsourced Massive Random Access

by Wenjiao Xie, Runhe Tian and Huisheng Zhang

Sensors 2023, 23(14), 6596; https://doi.org/10.3390/s23146596 - 21 Jul 2023

Viewed by 1204

Abstract

In this paper, we consider a slot-controlled coded compressed sensing protocol for unsourced massive random access (URA) that concatenates a shared patterned Reed–Muller (PRM) inner codebook to an outer error-correction code. Due to the limitations of the geometry-based decoding algorithm in single-sequence settings and due to the message interference that may result in decreased decoding performance under multi-sequence circumstances, a list PRM projection algorithm and an iterative list PRM projection algorithm are proposed to supplant the signal detector associated with the inner PRM sequences in this paper. In detail, we first propose an enhanced path-saving algorithm, called list PRM projection detection, for use in single-user scenarios that maintains multiple candidates during the first few layers so as to remedy the risk of spreading errors. On this basis, we further propose an iterative list PRM projection algorithm for use in multi-user scenarios. The vectors for PRM codes and channel coefficients are jointly detected in an iterative manner, which offers significant improvements regarding the convergence rate for signal recovery. Furthermore, the performances of the proposed algorithms are analyzed mathematically, and we verify that the theoretical simulations are consistent with the numerical simulations. Finally, we concatenate the inner PRM codes that employ iterative list detection in two practical error-correction outer codes. According to the simulation results, we conclude that the packetized URA with the proposed iterative list projection detection works better than benchmarks in terms of the number of active users it can support in each slot and the amount of energy needed per bit to meet an expected error probability. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

24 pages, 569 KiB

Open AccessArticle

Patterned Reed–Muller Sequences with Outer A-Channel Codes and Projective Decoding for Slot-Controlled Unsourced Random Access

by Wenjiao Xie and Huisheng Zhang

Sensors 2023, 23(11), 5239; https://doi.org/10.3390/s23115239 - 31 May 2023

Cited by 2 | Viewed by 1211

Abstract

We propose a novel slot-pattern-control based coded compressed sensing for unsourced random access with an outer A-channel code capable of correcting t errors. Specifically, an RM extension code called patterned Reed–Muller (PRM) code is proposed. We demonstrate the high spectral efficiency due to its enormous sequence space and prove the geometry property in the complex domain that enhances the reliability and efficiency of detection. Accordingly, a projective decoder based on its geometry theorem is also proposed. Next, the “patterned” property of the PRM code, which partitions the binary vector space into several subspaces, is further extended as the primary principle for designing a slot control criterion that reduces the number of simultaneous transmissions in each slot. The factors affecting the chance of sequence collisions are identified. Finally, the proposed scheme is implemented in two practical outer A-channel codes: (i) the t-tree code and (ii) the Reed–Solomon code with Guruswami–Sudan list decoding, and the optimal setups are determined to minimize SNR by optimizing the inner and outer codes jointly. In comparison with the existing counterpart, our simulation results confirm that the proposed scheme compares favorably with benchmark schemes regarding the energy-per-bit requirement to meet a target error probability as well as the number of accommodated active users in the system. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

16 pages, 1206 KiB

Open AccessArticle

Low-Complexity Beamforming Design for a Cooperative Reconfigurable Intelligent Surface-Aided Cell-Free Network

by Muhammad Zain Siddiqi, Aisha Munir, Syed Agha Hassnain Mohsan, Shashi Shah, Sushank Chaudhary, Paramin Sangwongngam and Lunchakorn Wuttisittikulkij

Sensors 2023, 23(2), 903; https://doi.org/10.3390/s23020903 - 12 Jan 2023

Cited by 4 | Viewed by 2347

Abstract

Cell-free (CF) networks are proposed to suppress the interference among collocated cells by deploying several BSs without cell boundaries. Nevertheless, as installing several base stations (BSs) may require high power consumption, cooperative CF networks integrated with a reconfigurable intelligent surface (RIS)/metasurface can avoid this problem. In such cooperative RIS-aided MIMO networks, efficient beamforming schemes are essential to boost their spectral and energy efficiency. However, most of the existing available beamforming schemes to maximize spectral and energy efficiency are complex and entail high complexity due to the matrix inversions. To this end, in this work we present a computationally efficient stochastic optimization-based particle swarm optimization (PSO) algorithm to amplify the spectral efficiency of the cooperative RIS-aided CF MIMO system. In the proposed PSO algorithm, several swarms are generated, while the direction of each swarm is tuned in each iteration based on the sum-rate performance to obtain the best solution. Our simulation results show that our proposed scheme can approximate the performance of the existing solutions for both the performance metrics, i.e., spectral and energy efficiency, at a very low complexity. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

13 pages, 1860 KiB

Open AccessArticle

Multi-Task Partial Offloading with Relay and Adaptive Bandwidth Allocation for the MEC-Assisted IoT

by Hafiz Hasnain Imtiaz and Suhua Tang

Sensors 2023, 23(1), 190; https://doi.org/10.3390/s23010190 - 24 Dec 2022

Cited by 3 | Viewed by 2464

Abstract

The fifth-generation (5G) wireless network is visualized to offer many types of services with low latency requirements in Internet of Things (IoT) networks. However, the computational capabilities of IoT nodes are not enough to process complex tasks in real time. To solve this problem, multi-access edge computing (MEC) has emerged as an effective solution that will allow IoT nodes to completely or partially offload their computational tasks to MEC servers. However, the large communication delay at a low transmission rate for nodes far from the access point (AP) makes this offloading less meaningful. This paper studies joint multi-task partial offloading from multiple IoT nodes to a common MEC server collocated with an AP, and it uses relay selection to help nodes far from the AP. The computation time of all tasks is minimized by adaptive task division and resource allocation (bandwidth and computation resource), and it is solved with an evolutionary algorithm. The simulation results confirm that the proposed method with both relay selection and adaptive bandwidth allocation outperforms the methods with neither or only one function. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

20 pages, 1292 KiB

Open AccessArticle

EMS: Efficient Monitoring System to Detect Non-Cooperative Nodes in IoT-Based Vehicular Delay Tolerant Networks (VDTNs)

by Ghani Ur Rehman, Muhammad Zubair, Iqbal Qasim, Afzal Badshah, Zafar Mahmood, Muhammad Aslam and Syeda Fizah Jilani

Sensors 2023, 23(1), 99; https://doi.org/10.3390/s23010099 - 22 Dec 2022

Cited by 10 | Viewed by 2536

Abstract

Since several Internet of Things (IoT) applications have been widely deployed on unstable wireless networks, such as the Delay Tolerant Network (DTN), data communication efficiency in DTN remains a challenge for IoT applications. Vehicular Delay Tolerant Network (VDTN) has become one of DTN’s potential applications, in which the network experiences connectivity interruption due to the lack of an end-to-end relay route. VDTNs focus on node cooperation to achieve this goal. As a result, it is essential to ensure that almost all network nodes adopt the protocol to preserve network performance. This is a challenging task since nodes may diverge from the basic protocol to optimize their effectiveness. This article presents an Efficient Monitoring System (EMS) to detect and respond to just selfish nodes to minimize their entire network and data communication efficacy. The scheme is based on a network-wide cooperative sharing of node reputation. It is also necessary to increase overall network efficiency by tracking selfish nodes. The NS-2 simulator is used to run this experimental setup. Simulation results indicate that the proposed scheme performs better in terms of probability of package delivery, package delivery delay, energy consumption, and amount of packet drops. For 80% selfish nodes in the network, the packet delivery of EMS is 37% and 31% better than SOS and IPS. Similarly, the average delivery delay of EMS is 22% and 18% lower than SOS and IPS when 80% selfish nodes are incorporated in the network. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

23 pages, 6084 KiB

Open AccessArticle

Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective

by Abdulhalim Fayad, Tibor Cinkler, Jacek Rak and Manish Jha

Sensors 2022, 22(23), 9394; https://doi.org/10.3390/s22239394 - 1 Dec 2022

Cited by 28 | Viewed by 5097

Abstract

Currently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient connections between a large number of remote radio heads (RRHs) in the cell sites and the baseband unit (BBU) pool in the central location, known as the fronthaul, has emerged as a new challenge. Many wired and wireless solutions have been proposed to address this bottleneck. Specifically, optical technologies presented by passive optical networks (PONs) are introduced as the best suitable solution for 5G and beyond network fronthaul due to their properties of providing high capacity and low latency connections. We considered time and wavelength division multiplexed passive optical networks (TWDM-PONs) as a fronthaul for 5G and beyond. Taking that into consideration, in this paper, we propose an integer linear program (ILP) that results in the optimal optical fronthaul deployment while minimizing the total cost of 5G and beyond instances. However, for larger network instances, solving the ILP problem becomes unscalable and time-consuming. To address that, we developed two heuristic-based algorithms (the K-means clustering algorithm and the one based on the genetic algorithm—GA). We evaluated the suitability of our proposed ILP and heuristic algorithms in simulations by utilizing them to plan different network instances (dense and sparse). Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

15 pages, 1217 KiB

Open AccessArticle

Intelligent Reflecting Surfaces Enhanced Mobile Edge Computing: Minimizing the Maximum Computational Time

by Mubashar Sarfraz, Haya Mesfer Alshahrani, Khaled Tarmissi, Hussain Alshahrani, Mohamed Ahmed Elfaki, Manar Ahmed Hamza, Ali Nauman and Tahir Khurshaid

Sensors 2022, 22(22), 8719; https://doi.org/10.3390/s22228719 - 11 Nov 2022

Cited by 2 | Viewed by 1634

Abstract

Intelligent reflecting surfaces (IRS) and mobile edge computing (MEC) have recently attracted significant attention in academia and industry. Without consuming any external energy, IRS can extend wireless coverage by smartly reconfiguring the phase shift of a signal towards the receiver with the help of passive elements. On the other hand, MEC has the ability to reduce latency by providing extensive computational facilities to users. This paper proposes a new optimization scheme for IRS-enhanced mobile edge computing to minimize the maximum computational time of the end users’ tasks. The optimization problem is formulated to simultaneously optimize the task segmentation and transmission power of users, phase shift design of IRS, and computational resource of mobile edge. The optimization problem is non-convex and coupled on multiple variables which make it very complex. Therefore, we transform it to convex by decoupling it into sub-problems and then obtain an efficient solution. In particular, the closed-form solutions for task segmentation and edge computational resources are achieved through the monotonical relation of time and Karush–Kuhn–Tucker conditions, while the transmission power of users and phase shift design of IRS are computed using the convex optimization technique. The proposed IRS-enhanced optimization scheme is compared with edge computing nave offloading, binary offloading, and edge computing, respectively. Numerical results demonstrate the benefits of the proposed scheme compared to other benchmark schemes. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

17 pages, 1178 KiB

Open AccessArticle

Joint Power Control and Phase Shift Design for Future PD-NOMA IRS-Assisted Drone Communications under Imperfect SIC Decoding

by Saddam Aziz, Muhammad Irshad, Kallekh Afef, Heba G. Mohamed, Najm Alotaibi, Khaled Tarmissi, Mrim M. Alnfiai and Manar Ahmed Hamza

Sensors 2022, 22(22), 8603; https://doi.org/10.3390/s22228603 - 8 Nov 2022

Viewed by 1896

Abstract

Intelligent reflecting surfaces (IRS) and power-domain non-orthogonal multiple access (PD-NOMA) have recently gained significant attention for enhancing the performance of next-generation wireless communications networks. More specifically, IRS can smartly reconfigure the incident signal of the source towards the destination node, extending the wireless coverage and improving the channel capacity without consuming additional energy. On the other side, PD-NOMA can enhance the number of devices in the network without using extra spectrum resources. This paper proposes a new optimization framework for IRS-enhanced NOMA communications where multiple drones transmit data to the ground Internet of Things (IoT) devices under successive interference cancellation errors. In particular, the power budget of each drone, PD-NOMA power allocation of IoT devices, and the phase shift matrix of IRS are simultaneously optimized to enhance the total spectral efficiency of the system. Given the system model and optimization setup, the formulated problem is coupled with three variables, making it very complex and non-convex. Thus, this work first transforms and decouples the problem into subproblems and then obtains the efficient solution in two steps. In the first step, the closed-form solutions for the power budget and PD-NOMA power allocation subproblem at each drone are obtained through Karush–Kuhn–Tucker (KKT) conditions. In the second step, the subproblem of efficient phase shift design for each IRS is solved using successive convex approximation and DC programming. Numerical results demonstrate the performance of the proposed optimization scheme in comparison to the benchmark schemes. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

16 pages, 528 KiB

Open AccessArticle

Automatic Modulation Recognition Based on the Optimized Linear Combination of Higher-Order Cumulants

by Asad Hussain, Sheraz Alam, Sajjad A. Ghauri, Mubashir Ali, Husnain Raza Sherazi, Adnan Akhunzada, Iram Bibi and Abdullah Gani

Sensors 2022, 22(19), 7488; https://doi.org/10.3390/s22197488 - 2 Oct 2022

Cited by 4 | Viewed by 2245

Abstract

Automatic modulation recognition (AMR) is used in various domains—from general-purpose communication to many military applications—thanks to the growing popularity of the Internet of Things (IoT) and related communication technologies. In this research article, we propose an innovative idea of combining the classical mathematical technique of computing linear combinations (LCs) of cumulants with a genetic algorithm (GA) to create super-cumulants. These super-cumulants are further used to classify five digital modulation schemes on fading channels using the K-nearest neighbor (KNN). Our proposed classifier significantly improves the percentage recognition accuracy at lower SNRs when using smaller sample sizes. A comparison with existing techniques manifests the supremacy of our proposed classifier. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

22 pages, 841 KiB

Open AccessArticle

Efficient Matching-Based Parallel Task Offloading in IoT Networks

by Usman Mahmood Malik, Muhammad Awais Javed, Jaroslav Frnda, Jan Rozhon and Wali Ullah Khan

Sensors 2022, 22(18), 6906; https://doi.org/10.3390/s22186906 - 13 Sep 2022

Cited by 18 | Viewed by 2224

Abstract

Fog computing is one of the major components of future 6G networks. It can provide fast computing of different application-related tasks and improve system reliability due to better decision-making. Parallel offloading, in which a task is split into several sub-tasks and transmitted to different fog nodes for parallel computation, is a promising concept in task offloading. Parallel offloading suffers from challenges such as sub-task splitting and mapping of sub-tasks to the fog nodes. In this paper, we propose a novel many-to-one matching-based algorithm for the allocation of sub-tasks to fog nodes. We develop preference profiles for IoT nodes and fog nodes to reduce the task computation delay. We also propose a technique to address the externalities problem in the matching algorithm that is caused by the dynamic preference profiles. Furthermore, a detailed evaluation of the proposed technique is presented to show the benefits of each feature of the algorithm. Simulation results show that the proposed matching-based offloading technique outperforms other available techniques from the literature and improves task latency by 52% at high task loads. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

20 pages, 4042 KiB

Open AccessArticle

Stochastic Recognition of Human Physical Activities via Augmented Feature Descriptors and Random Forest Model

by Sheikh Badar ud din Tahir, Abdul Basit Dogar, Rubia Fatima, Affan Yasin, Muhammad Shafiq, Javed Ali Khan, Muhammad Assam, Abdullah Mohamed and El-Awady Attia

Sensors 2022, 22(17), 6632; https://doi.org/10.3390/s22176632 - 2 Sep 2022

Cited by 12 | Viewed by 2878

Abstract

Human physical activity recognition from inertial sensors is shown to be a successful approach for monitoring elderly individuals and children in indoor and outdoor environments. As a result, researchers have shown significant interest in developing state-of-the-art machine learning methods capable of utilizing inertial sensor data and providing key decision support in different scenarios. This paper analyzes data-driven techniques for recognizing human daily living activities. Therefore, to improve the recognition and classification of human physical activities (for example, walking, drinking, and running), we introduced a model that integrates data preprocessing methods (such as denoising) along with major domain features (such as time, frequency, wavelet, and time–frequency features). Following that, stochastic gradient descent (SGD) is used to improve the performance of the extracted features. The selected features are catered to the random forest classifier to detect and monitor human physical activities. Additionally, the proposed HPAR system was evaluated on five benchmark datasets, namely the IM-WSHA, PAMAP-2, UCI HAR, MobiAct, and MOTIONSENSE databases. The experimental results show that the HPAR system outperformed the present state-of-the-art methods with recognition rates of 90.18%, 91.25%, 91.83%, 90.46%, and 92.16% from the IM-WSHA, PAMAP-2, UCI HAR, MobiAct, and MOTIONSENSE datasets, respectively. The proposed HPAR model has potential applications in healthcare, gaming, smart homes, security, and surveillance. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Figure 1

17 pages, 1049 KiB

Open AccessArticle

Performance Analysis of Dual-Hop Hybrid RF-UOWC NOMA Systems

by Ahmed Samir, Mohamed Elsayed, Ahmad A. Aziz El-Banna, Imran Shafique Ansari, Khaled Rabie and Basem M. ElHalawany

Sensors 2022, 22(12), 4521; https://doi.org/10.3390/s22124521 - 15 Jun 2022

Cited by 12 | Viewed by 2493

Abstract

The hybrid combination between underwater optical wireless communication (UOWC) and radio frequency (RF) is a vital demand for enabling communication through the air–water boundary. On the other hand, non-orthogonal multiple access (NOMA) is a key technology for enhancing system performance in terms of spectral efficiency. In this paper, we propose a downlink NOMA-based dual-hop hybrid RF-UOWC with decode and forward (DF) relaying. The UOWC channels are characterized by exponential-generalized Gamma (EGG) fading, while the RF channel is characterized by Rayleigh fading. Exact closed-form expressions of outage probabilities and approximated closed-form expressions of ergodic capacities are derived, for each NOMA individual user and the overall system as well, under the practical assumption of imperfect successive interference cancellation (SIC). These expressions are then verified via Monte-Carlo simulation for various underwater scenarios. To gain more insight into the system performance, we analyzed the asymptotic outage probabilities and the diversity order. Moreover, we formulated and solved a power allocation optimization problem to obtain an outage-optimal performance. For the sake of comparison and to highlight the achievable gain, the system performance is compared against a benchmark orthogonal multiple access (OMA)-based system. Full article

(This article belongs to the Special Issue Sustainable Solutions for 6G-Enabled Internet of Things Networks)

► Show Figures

Journal Menu

Journal Browser

Sustainable Solutions for 6G-Enabled Internet of Things Networks

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Related Special Issue

Published Papers (13 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI