1,296 research outputs found
A Stochastic Geometry Framework for LOS/NLOS Propagation in Dense Small Cell Networks
The need to carry out analytical studies of wireless systems often motivates
the usage of simplified models which, despite their tractability, can easily
lead to an overestimation of the achievable performance. In the case of dense
small cells networks, the standard single slope path-loss model has been shown
to provide interesting, but supposedly too optimistic, properties such as the
invariance of the outage/coverage probability and of the spectral efficiency to
the base station density. This paper seeks to explore the performance of dense
small cells networks when a more accurate path-loss model is taken into
account. We first propose a stochastic geometry based framework for small cell
networks where the signal propagation accounts for both the Line-of-Sight (LOS)
and Non-Line-Of-Sight (NLOS) components, such as the model provided by the 3GPP
for evaluation of pico-cells in Heterogeneous Networks. We then study the
performance of these networks and we show the dependency of some metrics such
as the outage/coverage probability, the spectral efficiency and Area Spectral
Efficiency (ASE) on the base station density and on the LOS likelihood of the
propagation environment. Specifically, we show that, with LOS/NLOS propagation,
dense networks still achieve large ASE gain but, at the same time, suffer from
high outage probability.Comment: Typo corrected in eq. (3); Typo corrected in legend of Fig. 1-2;
Typos corrected and definitions of some variables added in Section III.E;
Final result unchanged; Paper accepted to IEEE ICC 201
Coverage, capacity and energy efficiency analysis in the uplink of mmWave cellular networks
In this paper, using the concept of stochastic geometry, we present an analytical framework to evaluate the signal-to-interference-and-noise-ratio (SINR) coverage in the uplink of millimeter wave cellular networks. By using a distance-dependent line-of-sight (LOS) probability function, the location of LOS and non-LOS users are modeled as two independent non-homogeneous Poisson point processes, with each having a different pathloss exponent. The analysis takes account of per-user fractional power control (FPC), which couples the transmission of users based on location-dependent channel inversion. We consider the following scenarios in our analysis: 1) Pathloss-based FPC (PL-FPC) which is performed using the measured pathloss and 2) Distance-based FPC (D-FPC) which is performed using the measured distance. Using the developed framework, we derive expressions for the area spectral efficiency and energy efficiency. Results suggest that in terms of SINR coverage, D-FPC outperforms PL-FPC scheme at high SINR where the future networks are expected to operate. It achieves equal or better area spectral efficiency and energy efficiency compared with the PL-FPC scheme. Contrary to the conventional ultra-high frequency cellular networks, in both FPC schemes, the SINR coverage decreases as the cell density becomes greater than a threshold, while the area spectral efficiency experiences a slow growth region
Dynamic Base Station Repositioning to Improve Spectral Efficiency of Drone Small Cells
With recent advancements in drone technology, researchers are now considering
the possibility of deploying small cells served by base stations mounted on
flying drones. A major advantage of such drone small cells is that the
operators can quickly provide cellular services in areas of urgent demand
without having to pre-install any infrastructure. Since the base station is
attached to the drone, technically it is feasible for the base station to
dynamic reposition itself in response to the changing locations of users for
reducing the communication distance, decreasing the probability of signal
blocking, and ultimately increasing the spectral efficiency. In this paper, we
first propose distributed algorithms for autonomous control of drone movements,
and then model and analyse the spectral efficiency performance of a drone small
cell to shed new light on the fundamental benefits of dynamic repositioning. We
show that, with dynamic repositioning, the spectral efficiency of drone small
cells can be increased by nearly 100\% for realistic drone speed, height, and
user traffic model and without incurring any major increase in drone energy
consumption.Comment: Accepted at IEEE WoWMoM 2017 - 9 pages, 2 tables, 4 figure
Wireless Powered Dense Cellular Networks: How Many Small Cells Do We Need?
This paper focuses on wireless powered 5G dense cellular networks, where base
station (BS) delivers energy to user equipment (UE) via the microwave radiation
in sub-6 GHz or millimeter wave (mmWave) frequency, and UE uses the harvested
energy for uplink information transmission. By addressing the impacts of
employing different number of antennas and bandwidths at lower and higher
frequencies, we evaluate the amount of harvested energy and throughput in such
networks. Based on the derived results, we obtain the required small cell
density to achieve an expected level of harvested energy or throughput. Also,
we obtain that when the ratio of the number of sub-6 GHz BSs to that of the
mmWave BSs is lower than a given threshold, UE harvests more energy from a
mmWave BS than a sub-6 GHz BS. We find how many mmWave small cells are needed
to perform better than the sub-6 GHz small cells from the perspectives of
harvested energy and throughput. Our results reveal that the amount of
harvested energy from the mmWave tier can be comparable to the sub-6 GHz
counterpart in the dense scenarios. For the same tier scale, mmWave tier can
achieve higher throughput. Furthermore, the throughput gap between different
mmWave frequencies increases with the mmWave BS density.Comment: pages 1-14, accepted by IEEE Journal on Selected Areas in
Communication
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