Toward Smart Traffic Management With 3D Placement Optimization in UAV-Assisted NOMA IIoT Networks

Adam, Abuzar B. M.; Muthanna, Mohammed Saleh Ali; Muthanna, Ammar; Nguyen, Ngoc‐Tu; El‐Latif, Ahmed A. Abd

doi:10.1109/tits.2022.3182651

Cited by 24 publications

(3 citation statements)

References 37 publications

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“…The PPP-based approximate SIR analysis method serves as a valuable tool for evaluating network effectiveness across diverse deployment scenarios, addressing the challenges posed by non-Poisson point processes. Research on network topologies and transmission techniques continues to captivate both academic and industrial realms as a pivotal pursuit in enhancing energy efficiency (EE) and consumption in future mobile communication systems [15][16][17][18].…”

Section: Literature Reviewmentioning

confidence: 99%

Enhancing Energy Efficiency and Coverage in HetNets through Antenna Optimization

Dahri,

Shaikh,

Panhwer

et al. 2023

VFAST trans. softw. eng.

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The advent of 5G technology has opened up new opportunities across various fields, including healthcare. In the context of wireless communication, the deployment of a two-tier heterogeneous network (HetNet) plays a crucial role in ensuring robust connections among devices, users, and healthcare infrastructure. This study focuses on optimizing coverage and energy efficiency (EE) in HetNets, tailored for specific application domains. We begin by examining how antenna height impacts coverage within macro and pico cells. Precise antenna placement is critical, as it significantly alters coverage patterns, particularly in healthcare settings, which can range from large hospital complexes to remote telemedicine locations. Additionally, we investigate the strategic adjustment of antenna gain in macro and pico cells, showing how this optimization enhances coverage and minimizes interference. Achieving this balance is essential for the reliable transmission of data. Our research also considers the interplay of antenna height, EE, and the maximum number of users ($N_{max}$). Surprisingly, we find that $N_{max}$ has a limited impact on coverage and EE compared to antenna configuration. This emphasizes the crucial role of antenna design and placement in crafting efficient wireless networks.Our study provides insights into improving coverage and EE in HetNets, with implications for various applications. It underscores the importance of strategic antenna optimization in shaping efficient and resilient communication systems. Furthermore, we explore the impact of $\beta$ on EE and leverage idle mode capabilities for further EE enhancements.

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Section: Literature Reviewmentioning

confidence: 99%

Enhancing Energy Efficiency and Coverage in HetNets through Antenna Optimization

Dahri,

Shaikh,

Panhwer

et al. 2023

VFAST trans. softw. eng.

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“…In the civil applications arena, Jiang et al investigated optimal power allocation schemes for NOMA in a high-speed railway scenarios [343] and showed that NOMA performance is better than the traditional orthogonal multiple access (OMA) schemes. Adam et al investigated 3D placement optimization in UAVassisted NOMA industrial IoT (IIoT) networks for smart traffic management [344]. The authors suggested that path aggregation networks (PANet) show promise in real-time applications when solving nonconvex problems associated with optimal 3D placement in communication networks.…”

Section: ) 5g Mmwave Uav-assisted Communication Networkmentioning

confidence: 99%

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

et al. 2022

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The use of drones, formally known as unmanned aerial vehicles (UAVs), has significantly increased across a variety of applications over the past few years. This is due to the rapid advancement towards the design and production of inexpensive and dependable UAVs and the growing request for the utilization of such platforms particularly in civil applications. With their intrinsic attributes such as high mobility, rapid deployment and flexible altitude, UAVs have the potential to be utilized in many wireless system applications. On the one hand, UAVs are able to operate as flying mobile terminals within wireless/cellular networks to support a variety of missions such as goods delivery, search and rescue, precision agriculture monitoring, and remote sensing. On the other hand, UAVs can be utilized as aerial base stations to increase wireless communication coverage, reliability, and the capacity of wireless systems without additional investment in wireless systems infrastructure. The aim of this article is to review the current applications of UAVs for civil and commercial purposes. The focus of this paper is on the challenges and communication requirements associated with UAV-based communication systems. This article initially classifies UAVs in terms of various parameters, some of which can impact UAVs' communication performance. It then provides an overview of aerial networking and investigates UAVs routing protocols specifically, which are considered as one of the challenges in UAV communication. This article later investigates the use of UAV networks in a variety of civil applications and considers many challenges and communication demands of these applications. Subsequently, different types of simulation platforms are investigated from a communication and networking viewpoint. Finally, it identifies areas of future research.

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“…ML algorithms learn from the input and produce deterministic output without being explicitly programmed. ML is gaining prominence in the Internet of Things (IoT) networks [5]- [7]. An IoT network is a set of AI devices/sensors that communicate among devices without human intervention.…”

Section: Introductionmentioning

confidence: 99%

Edge ML Technique for Smart Traffic Management in Intelligent Transportation Systems

Hazarika,

Choudhury,

Nasralla

et al. 2024

IEEE Access

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In urban traffic, a Dynamic Traffic Light System (DTLS) is an important aspect of automatic driving. DTLS estimates the time of the light signal from images of dynamically changing road traffic. In conventional traffic light systems, light signals are enabled at predefined or fixed time intervals without having information on the current traffic density on the road. This static behavior of the traffic light system increases unnecessary waiting time on the road, eventually creating traffic jams, environmental pollution, and other health emergencies. The smart traffic light system addresses these issues with self-learning algorithms and dynamically allows traffic to pass by learning current traffic density. In this paper, a visionbased DTLS is proposed using the YOLO (You Only Look Once) object detection algorithm that detects and counts the total number of vehicles on the roads of a traffic signal junction. The traffic signals are tuned based on the computed traffic to minimize the overall delay at that junction. Moreover, the traffic junctions are facilitated to communicate with the adjacent junctions to transmit the cumulative traffic delay observed. This delay is used to prioritize traffic passing through salient blocks like schools, offices, hospitals, etc. The paper aims to minimize the overhead incurred in both computations of traffic (using approximate computing) and in communication networks (using low-power technologies of IEEE 802.15.4 standard, specifically DSME MAC and/or LoRaWAN). The proposed system accomplishes its objective of smart city infrastructure by optimizing the traffic flow. Further, the paper provides a mechanism for green traffic corridors for emergency vehicles.

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Toward Smart Traffic Management With 3D Placement Optimization in UAV-Assisted NOMA IIoT Networks

Cited by 24 publications

References 37 publications

Enhancing Energy Efficiency and Coverage in HetNets through Antenna Optimization

Enhancing Energy Efficiency and Coverage in HetNets through Antenna Optimization

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

Edge ML Technique for Smart Traffic Management in Intelligent Transportation Systems

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