Radio propagation and wireless coverage of LSAA-based 5G millimeter-wave mobile communication systems

Wang, Haiming; Zhang, Peize; Li, Jing; You, Xiaohu

doi:10.23919/j.cc.2019.05.001

Cited by 37 publications

(21 citation statements)

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“…To overcome the high path loss effect, Karthikeya, et al [67] proposed the design of a co-polarized stacked antenna with a pattern diversity for indoor base stations. Similarly, [68] proposed the use of large-scale antenna arrays to extend the 5G mm-Wave band coverage to lower the effect of path loss. Figure 1 shows the 3D map and the google earth map of the study area.…”

Section: Methodsmentioning

confidence: 99%

Deterministic 5G mmWave Large-Scale 3D Path Loss Model for Lagos Island, Nigeria

Hinga

Atayero

2021

IEEE Access

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5G millimeter wave (mmWave) application in mobile connectivity to realize high-speed, reliable communication is attributed with high path loss. This paper presents a detailed 3D ray-tracing technique at 28 GHz for Lagos Island to investigate five unique path loss scenarios: path loss, free space path loss with antenna pattern, free space path loss without antenna pattern, excess path loss with antenna pattern, and the excess path loss without antenna pattern for an urban environment. The Close-In (CI) model, Floating Intercept (FI) path loss model, and a root mean square error (RMSE) are used to model and evaluate the best path loss model for Lagos Island. The average achieved FI (α ,β, σ) parameters were 189.92352, 0.1654, and 0.66948, While the average CI (η,Xσ) parameters were 2.309355 and 56.236425. From all the scenarios evaluated, the lowest path loss exponent achieved was 0.45, while the highest path loss exponent was 3.8. We have established that the FI path loss model accurately characterizes path loss for the Lagos Island environment with the lowest RMSE of 0.0359 dB and the highest RSME of 0.0997 dB. In contrast, the CI model over-predict the path loss at 28 GHz with the lowest RMSE of 0.0495 dB and the highest RMSE of 2.2547 dB. This work opens up a new area of research on mm-Wave at 28 GHz in Lagos Island, and the results obtained from this work can be used to benchmark future studies on mmWave in a similar environment.

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Section: Methodsmentioning

confidence: 99%

Deterministic 5G mmWave Large-Scale 3D Path Loss Model for Lagos Island, Nigeria

Hinga

Atayero

2021

IEEE Access

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“…Fig. 4 shows a typical measured directional PDP for the NLoS scenario in the CBD environment, where the effective PDP filtering the contribution of noise floor (red part) is estimated following the method proposed in [32]. The 30 dB power threshold and 20 dB SNR are employed to compute P D .…”

Section: A Clustering Multipath Componentsmentioning

confidence: 99%

Radio Propagation Measurements and Cluster-Based Analysis for 5G Millimeter-Wave Cellular Systems in Dense Urban Environments

Zhang¹,

Yang²,

Wang³

et al. 2020

Preprint

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Empirical channel modeling is necessary for the deployment of the fifth-generation (5G) millimeter-wave (mmWave) cellular system in actual environments. In this paper, cluster-based analyses of mmWave channel characteristics in two typical dense urban environments are performed. First, radio propagation measurement campaigns are conducted at two primary 5G bands of 28 GHz and 39 GHz in a central business district and a dense residential area. The custom-designed channel sounder supports high-efficiency directional scanning sounding, which helps to collect sufficient data for statistical channel modeling. Next, using an improved autoclustering algorithm, multipath clusters and their scattering sources are identified. Mapping results show that multiple reflections from exterior walls and diffraction over building corners or rooftops enhance the coverage for non-line-of-sight (NLoS) links and the influences of these propagation mechanisms are intuitively embodied as changes in the topologies of deployment environments. Finally, an appropriate measure for cluster-level channel characteristics is provided including cluster number, Ricean K-factor, root mean squared (RMS) delay spread, RMS angular spread, and their correlations. Comparisons of these parameters across two mmWave bands are also given. The measurement and modeling results shed light on a fully understanding of mmWave channels in dense urban environments across multiple bands.

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“…During the past few years, wireless communication has been widely developed and has gained more attention to study the propagation characteristics of wireless signals in indoor and outdoor environments 1,2 . As a result, the evolution of wireless technology has bought several advantages such as cost effectiveness, flexibility, speed, and accessibility 3 .…”

Section: Introductionmentioning

confidence: 99%

WOAIP: Wireless Optimization Algorithm for Indoor Placement Based on Binary Particle Swarm Optimization (BPSO)

Naif

Mohammed

2022

Baghdad Sci.J

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Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received signal strength (RSS) measurements simulated using Wireless InSite (WI) software were considered in the test case study by comparing the results collected from WI with the present wireless simulated physical AP deployment of the targeted building - Computer Science Department at University of Baghdad. The performance evaluation of WOAIP shows an increase in terms of AP placement and optimization distinguished in order to increase the wireless coverage ratio to 92.93% compared to 58.5% of present AP coverage (or 24.5% coverage enhancement on average).

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Radio propagation and wireless coverage of LSAA-based 5G millimeter-wave mobile communication systems

Cited by 37 publications

References 0 publications

Deterministic 5G mmWave Large-Scale 3D Path Loss Model for Lagos Island, Nigeria

Deterministic 5G mmWave Large-Scale 3D Path Loss Model for Lagos Island, Nigeria

Radio Propagation Measurements and Cluster-Based Analysis for 5G Millimeter-Wave Cellular Systems in Dense Urban Environments

WOAIP: Wireless Optimization Algorithm for Indoor Placement Based on Binary Particle Swarm Optimization (BPSO)

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