26,024 research outputs found
Spatial spectrum and energy efficiency of random cellular networks
It is a great challenge to evaluate the network performance of cellular
mobile communication systems. In this paper, we propose new spatial spectrum
and energy efficiency models for Poisson-Voronoi tessellation (PVT) random
cellular networks. To evaluate the user access the network, a Markov chain
based wireless channel access model is first proposed for PVT random cellular
networks. On that basis, the outage probability and blocking probability of PVT
random cellular networks are derived, which can be computed numerically.
Furthermore, taking into account the call arrival rate, the path loss exponent
and the base station (BS) density in random cellular networks, spatial spectrum
and energy efficiency models are proposed and analyzed for PVT random cellular
networks. Numerical simulations are conducted to evaluate the network spectrum
and energy efficiency in PVT random cellular networks.Comment: appears in IEEE Transactions on Communications, April, 201
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
Uplink capacity of a variable density cellular system with multicell processing
In this work we investigate the information theoretic capacity of the uplink of a cellular system. Assuming centralised processing for all base stations, we consider a power-law path loss model along with variable cell size (variable density of Base Stations) and we formulate an average path-loss approximation. Considering a realistic Rician flat fading environment, the analytical result for the per-cell capacity is derived for a large number of users distributed over each cell. We extend this general approach to model the uplink of sectorized cellular system. To this end, we assume that the user terminals are served by perfectly directional receiver antennas, dividing the cell coverage area into perfectly non-interfering sectors. We show how the capacity is increased (due to degrees of freedom gain) in comparison to the single receiving antenna system and we investigate the asymptotic behaviour when the number of sectors grows large. We further extend the analysis to find the capacity when the multiple antennas used for each Base Station are omnidirectional and uncorrelated (power gain on top of degrees of freedom gain). We validate the numerical solutions with Monte Carlo simulations for random fading realizations and we interpret the results for the real-world systems
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