5,245 research outputs found
MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network
Ultra-dense network (UDN) has been considered as a promising candidate for
future 5G network to meet the explosive data demand. To realize UDN, a
reliable, Gigahertz bandwidth, and cost-effective backhaul connecting
ultra-dense small-cell base stations (BSs) and macro-cell BS is prerequisite.
Millimeter-wave (mmWave) can provide the potential Gbps traffic for wireless
backhaul. Moreover, mmWave can be easily integrated with massive MIMO for the
improved link reliability. In this article, we discuss the feasibility of
mmWave massive MIMO based wireless backhaul for 5G UDN, and the benefits and
challenges are also addressed. Especially, we propose a digitally-controlled
phase-shifter network (DPSN) based hybrid precoding/combining scheme for mmWave
massive MIMO, whereby the low-rank property of mmWave massive MIMO channel
matrix is leveraged to reduce the required cost and complexity of transceiver
with a negligible performance loss. One key feature of the proposed scheme is
that the macro-cell BS can simultaneously support multiple small-cell BSs with
multiple streams for each smallcell BS, which is essentially different from
conventional hybrid precoding/combining schemes typically limited to
single-user MIMO with multiple streams or multi-user MIMO with single stream
for each user. Based on the proposed scheme, we further explore the fundamental
issues of developing mmWave massive MIMO for wireless backhaul, and the
associated challenges, insight, and prospect to enable the mmWave massive MIMO
based wireless backhaul for 5G UDN are discussed.Comment: This paper has been accepted by IEEE Wireless Communications
Magazine. This paper is related to 5G, ultra-dense network (UDN), millimeter
waves (mmWave) fronthaul/backhaul, massive MIMO, sparsity/low-rank property
of mmWave massive MIMO channels, sparse channel estimation, compressive
sensing (CS), hybrid digital/analog precoding/combining, and hybrid
beamforming. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=730653
Dealing with Interference in Distributed Large-scale MIMO Systems: A Statistical Approach
This paper considers the problem of interference control through the use of
second-order statistics in massive MIMO multi-cell networks. We consider both
the cases of co-located massive arrays and large-scale distributed antenna
settings. We are interested in characterizing the low-rankness of users'
channel covariance matrices, as such a property can be exploited towards
improved channel estimation (so-called pilot decontamination) as well as
interference rejection via spatial filtering. In previous work, it was shown
that massive MIMO channel covariance matrices exhibit a useful finite rank
property that can be modeled via the angular spread of multipath at a MIMO
uniform linear array. This paper extends this result to more general settings
including certain non-uniform arrays, and more surprisingly, to two dimensional
distributed large scale arrays. In particular our model exhibits the dependence
of the signal subspace's richness on the scattering radius around the user
terminal, through a closed form expression. The applications of the
low-rankness covariance property to channel estimation's denoising and
low-complexity interference filtering are highlighted.Comment: 12 pages, 11 figures, to appear in IEEE Journal of Selected Topics in
Signal Processin
Spatial and Social Paradigms for Interference and Coverage Analysis in Underlay D2D Network
The homogeneous Poisson point process (PPP) is widely used to model spatial
distribution of base stations and mobile terminals. The same process can be
used to model underlay device-to-device (D2D) network, however, neglecting
homophilic relation for D2D pairing presents underestimated system insights. In
this paper, we model both spatial and social distributions of interfering D2D
nodes as proximity based independently marked homogeneous Poisson point
process. The proximity considers physical distance between D2D nodes whereas
social relationship is modeled as Zipf based marks. We apply these two
paradigms to analyze the effect of interference on coverage probability of
distance-proportional power-controlled cellular user. Effectively, we apply two
type of functional mappings (physical distance, social marks) to Laplace
functional of PPP. The resulting coverage probability has no closed-form
expression, however for a subset of social marks, the mark summation converges
to digamma and polygamma functions. This subset constitutes the upper and lower
bounds on coverage probability. We present numerical evaluation of these bounds
on coverage probability by varying number of different parameters. The results
show that by imparting simple power control on cellular user, ultra-dense
underlay D2D network can be realized without compromising the coverage
probability of cellular user.Comment: 10 pages, 10 figure
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