Performance Analysis of Cellular Ultradense IoT Networks With Wireless Backhauls

Elbayoumi, Mohammed; Ibrahim, Mohamed Izham Mohamed; Elhoushy, Salah; Hamouda, Walaa; Youssef, Amr M.

doi:10.1109/jiot.2023.3265192

Cited by 4 publications

(1 citation statement)

References 40 publications

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“…In [12], the upper bound of the network capacity with wireless backhaul is evaluated based on the number of antennas per BS. In [13], with the tool of stochastic geometry, the authors examine the performance of mMTC in an ultra-dense network (UDN) environment that utilizes the mmWave band and employs wireless backhaul support for the small cell. In [14], the authors propose a load-balancing algorithm for small-cell-integrated access and backhaul networks operating in the millimeter wave (mmWave) band.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Small-Cell Capacity with Wireless Backhaul

Tao,

Liu

2024

Electronics

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Recently, hyperdense small cells have been proposed to meet the challenge of the tremendous increment in cellular data service requirements. To reduce the deployment cost, as well as operated cost, these small cells are usually connected to limited backhauls, in which case the backhaul capacity may become a bottleneck in busy hours. In this paper, we propose an optimal scheme for the small cells to utilize the macrocell links as its wireless backhaul. Based on stochastic geometry, the analytical expressions of network capacity with in-band and out-band wireless backhaul are derived and validated using simulation results. The optimized results show that our proposed scheme can significantly improve the network performance in scenarios with a high traffic load.

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Section: Introductionmentioning

confidence: 99%

Enhancing Small-Cell Capacity with Wireless Backhaul

Tao,

Liu

2024

Electronics

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Modeling medium dense cellular network and evaluation of probability of coverage

Vaddi

Venkatesh

Gupta

2023

Trans Emerging Tel Tech

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It is well known that cellular networks are continuously densifying at an enormous rate everywhere around the globe. Much work has been done in modeling ultra‐dense cellular (UDC) network. However, at present, there are no satisfactory models for medium dense cellular (MDC) network. Motivation of our work is to fill this gap in the literature. In particular, we propose to develop a model for the MDC network and derive the coverage probability. In this article, an optimization problem based on sparse dictionary learning (SDL) has been used to find a linear dependency between the UDC region and MDC region with respect to the base stations. A model for the MDC network is defined based on the linear dependency produced using SDL. The linear dependency allows us to define a relation connecting the distance metric between the MDC and UDC regions. Different terms in the expression for the equivalent distance metric have been identified, and the most relevant terms have been used to evaluate the coverage probability of the MDC network. Validation of our model has been done by comparing the correlation graph between the proposed model and the ideal model. Our proposed network model opens up the scope for more accurate modeling and analysis of medium‐dense cellular networks.

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Outage and Rate Analysis for Industrial Internet of Things in Multitier Visible Light Communication Networks Inside Finite 3-D Space

Zhou,

Huang,

2024

IEEE Internet Things J.

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Performance Analysis of Cellular Ultradense IoT Networks With Wireless Backhauls

Cited by 4 publications

References 40 publications

Enhancing Small-Cell Capacity with Wireless Backhaul

Enhancing Small-Cell Capacity with Wireless Backhaul

Modeling medium dense cellular network and evaluation of probability of coverage

Outage and Rate Analysis for Industrial Internet of Things in Multitier Visible Light Communication Networks Inside Finite 3-D Space

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