Analysis of Localization Performance in mm-Wave 5G Network Under Channel Uncertainties

Sellami, Amal; Nasraoui, Leïla; Najjar, Leila

doi:10.1109/jiot.2022.3218370

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…Figure 1 illustrates a typical Industry 4.0 scenario in a smart warehouse where a forklift moves products from the conveyor belt to the shelves. In such a scenario, the localization and tracking of the forklift can be achieved using geometry-based methods, which rely on accurate estimation of localization parameters [5,17]. As in [14], we assume the channel's dependency on the response vector.…”

Section: System Modelmentioning

confidence: 99%

Adaptive DCS-SOMP for Localization Parameter Estimation in 5G Networks

da Conceição,

Rocha

2023

Sensors

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In this work, we model a 5G downlink channel using millimeter-wave (mmWave) and massive Multiple-Input Multiple-Output (mMIMO) technologies, considering the following localization parameters: Time of Arrival (TOA), Two-Dimensional Angle of Departure (2D-AoD), and Two-Dimensional Angle of Arrival (2D-AoA), both encompassing azimuth and elevation. Our research focuses on the precise estimation of these parameters within a three-dimensional (3D) environment, which is crucial in Industry 4.0 applications such as smart warehousing. In such scenarios, determining the device localization is paramount, as products must be handled with high precision. To achieve these precise estimations, we employ an adaptive approach built upon the Distributed Compressed Sensing—Subspace Orthogonal Matching Pursuit (DCS-SOMP) algorithm. We obtain better estimations using an adaptive approach that dynamically adapts the sensing matrix during each iteration, effectively constraining the search space. The results demonstrate that our approach outperforms the traditional method in terms of accuracy, speed to convergence, and memory use.

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Section: System Modelmentioning

confidence: 99%

Adaptive DCS-SOMP for Localization Parameter Estimation in 5G Networks

da Conceição,

Rocha

2023

Sensors

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“…However, energy efficiency is no longer relevant in a normal heterogeneous network because base stations (BSs) in the small cell and macro cells must deal with data flow rate, control signal, and always stay awake [2]- [4]. On the other hand, the initial fifth generation (5G) millimetre wave (mmWave) new radio deployment will concentrate on enhanced mobile broadband, which utilises a unique combination of radio frequency bands to increase data bandwidth and energy connection efficiency [5], [6], thereby improving download and upload speeds and decreasing latency [7]- [10]. The most significant factor in creating 5G networks that must be considered is energy consumption and efficiency [11]- [13].…”

Section: Introductionmentioning

confidence: 99%

Energy saving performance analysis for future fifth generation millimetre-wave cellular networks

Anwar Apandi,

Muhammad

2024

Bulletin EEI

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The deployment of fifth generation (5G) millimetre-wave (mmWave) base stations (BSs) will consume more energy over time due to the limited time available, despite the increasing interest in developing 5G mmWave wireless communication technology. Constructing 5G mmWave cellular network infrastructure can improve energy efficiency, which is a challenge to implement in heterogeneous networks. This paper presents analytical frameworks for monitoring the effectiveness of 5G mmWave cellular networks. Based on the state management of BS, a system model for 2-tier heterogeneous networks is developed, and particle swarm optimization (PSO) is then used to compute the total energy consumption of the heterogeneous networks. Energy consumption was compared and analysed by leveraging state switching and the aggregate delay for three methods: fundamental separation, conventional separation, and a proposed energy-saving method that introduced a sleep state. Simulation shows that the proposed energy-saving method, which is a combination of conventional separation approaches, has the lowest total energy consumption and offers a 9% reduction compared to other related works. The results validate the accuracy of the power usage used in the 5G mmWave cellular network of the proposed method.

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Joint Angle Estimation Error Analysis and 3-D Positioning Algorithm Design for mmWave Positioning System

Tang

Pan

et al. 2024

IEEE Internet Things J.

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Analysis of Localization Performance in mm-Wave 5G Network Under Channel Uncertainties

Cited by 3 publications

References 4 publications

Adaptive DCS-SOMP for Localization Parameter Estimation in 5G Networks

Adaptive DCS-SOMP for Localization Parameter Estimation in 5G Networks

Energy saving performance analysis for future fifth generation millimetre-wave cellular networks

Joint Angle Estimation Error Analysis and 3-D Positioning Algorithm Design for mmWave Positioning System

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