In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the
Aug 11, 2021 · Abstract Path gain and effective directional gain in azimuth in urban canyons from actual rooftop base station sites are characterized based on a massive data set of 3000 links
This paper provides an analytical derivation of the probability density function of signal-to-interference-plus-noise ratio in the scenario where mobile stations interfere with each other.
Jun 13, 2018 · In this, the reasonable configuration of the density of base stations is very essential for the network performance improvement, especially for the network energy optimization.
Base station deployment strategy is one of the key challenges to be addressed for fulfilling the future capacity demand with energy efficiency. In this paper, we investigate the relationship
Optimal base station (BS) density, to minimise network energy consumption, is studied. Contrary to previous works, both the spatial randomness of the network topology and the wireless traffic
Feb 19, 2014 · I. INTRODUCTION Cell size reduction provides increased spectral reuse and increased data rates to mobile users. As the cell size decreases, the number of users per base
Jan 1, 2021 · Gravity method: A geophysical technique based on measuring the variations in the Earth''s gravity field at specific locations. Gravity stations: Locations where gravity
Nov 12, 2021 · Base station locations (dots) and corresponding Voronoi cells (lines) in a rural area. The area in the blue rectangular and the whole area are denoted by `RA1'' and `RA2'',
May 31, 2024 · Base station densification is one of the key approaches for delivering high capacity in radio access networks. However, current static deployments are often impractical and
Feb 19, 2014 · ides increased spectral reuse and increased data rates to mobile users. As the cell size decreases, the number of users per base station (BS) decreases leading to a greater
May 31, 2020 · The beamforming technology of the new fifth generation (5G) communication technology, different from the conventional ones, is updated by millimeter-wave technology,
Jan 12, 2021 · Abstract: Since the analysis of cell coverage faces complex environments in unmanned aerial vehicle base station (UAV-BS) systems, general coverage probability in a
Sep 10, 2024 · We propose an approach to infer real datasets with spatial homogeneity in urban, suburban or rural areas. We remind the notions of stationarity, isotropy, complete spatial
Jun 1, 2021 · Note that derivation according to (10) is a complex procedure as the achieved rate is actually a function of a random number of random variables (RV). Obtaining capacity pdf is
May 17, 2013 · Using the result, we calculate the density of success transmissions in the downlink cellular network. An interesting observation is that the success transmission density increases
Feb 26, 2015 · In particular, our approach allows the derivation of realistic estimates of the energy-optimal density of base stations corresponding to a given user density, under a fixed
Apr 11, 2020 · The methodol-ogy is based on the analytical characterization of the array near field in both its average and peak power density levels, and the derivation of simple prediction
Sep 1, 2020 · In this paper, a loss minimization issue is proposed, which includes both cost of user power consumption and base station (BS) deployment. A multi-tier heterogeneous
May 17, 2013 · An interesting observation is that the success transmission density increases with the base station density, but the increasing rate diminishes. This means that the number of
Dec 1, 2020 · In this study, we couple geographic information system (GIS) and a heuristic algorithm to search for the optimal locations of each BS in a 5G network. The spatial modelling
May 17, 2013 · In this paper, we use the stochastic geometry approach, where base stations can be modeled as a homogeneous Poisson point process. We also consider the user density, and
Jan 16, 2024 · 22 Sleep modes energy-optimal density of base stations corresponding to a given user density, under a 33 23 fixed performance constraint. Our results allow different sleep
Jun 15, 2012 · In this paper, we adopt stochastic geometry theory to analyze the optimal macro/micro BS (base station) density for energy-efficient heterogeneous cellular networks
May 9, 2019 · Therefore, for HetNets deployment in reality, the pico-cell range expansion (CRE) bias, the power of ABS and the density of pico base stations
Jan 23, 2018 · This paper develops a new approach to the modeling and analysis of heterogeneous cellular networks (HetNets) that accurately incorporates coupling across the
sumption is minimized and the optimal base station density is obtained. For a path loss exponent > 4, we observe the existence of a minimum cell size belo which shrinking the cell would result in an overall increase of power. However, for 4, there exists no such optimal cell-
sing the density of base stations for a given target rate and coverage. It turns out that after a certain po er threshold, noise plays a significant role on both coverage and rate.For > 4, we obtain an expression for the optimum base station density which minimizes area power consumption and maximizes power efficiency1 under target rate an
power has to be scaled down with increase WER FOR TARGET COVERAGE AND RATEA. Minimum transmit power for coverageAs the BS density increases, the transmit power of the base stations may be decreased because of the decreasing cell size. However, reducing the ransmit pow r, decreases the coverage probability because of the noise. See Fig.
user is denoted by RT ; it is independent of the base station density. The i terference-limited spectral efficiency, corresponding to P = 1, is (1). It is independ nt of the base station density and depends only on path loss exponent . So, irrespective of he transmit power, the m
The total area of the study area and the total area of buildings in the study area are 356.1 ha and 64.5 ha, respectively. Thus, the building density in the study area is approximately 0.18. Fig. 4. Map of the study area. The data we used to perform the optimization are listed in Table 1. All data were processed and stored in a file geodatabase.
The experimental results indicate that to achieve service coverage greater than 95% in the study area, the density of BSs in this area cannot be lower than 45 BSs/km 2, which is consistent with the estimates of Ge et al. (2016) (40-50 BSs/km 2) and Palizban et al. (2017) (40-60 BSs/km 2).
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