4,003 research outputs found
Energy Efficiency in Two-Tiered Wireless Sensor Networks
We study a two-tiered wireless sensor network (WSN) consisting of access
points (APs) and base stations (BSs). The sensing data, which is
distributed on the sensing field according to a density function , is first
transmitted to the APs and then forwarded to the BSs. Our goal is to find an
optimal deployment of APs and BSs to minimize the average weighted total, or
Lagrangian, of sensor and AP powers. For , we show that the optimal
deployment of APs is simply a linear transformation of the optimal -level
quantizer for density , and the sole BS should be located at the geometric
centroid of the sensing field. Also, for a one-dimensional network and uniform
, we determine the optimal deployment of APs and BSs for any and .
Moreover, to numerically optimize node deployment for general scenarios, we
propose one- and two-tiered Lloyd algorithms and analyze their convergence
properties. Simulation results show that, when compared to random deployment,
our algorithms can save up to 79\% of the power on average.Comment: 11 pages, 7 figure
Channel Estimation for mmWave Massive MIMO Based Access and Backhaul in Ultra-Dense Network
Millimeter-wave (mmWave) massive MIMO used for access and backhaul in
ultra-dense network (UDN) has been considered as the promising 5G technique. We
consider such an heterogeneous network (HetNet) that ultra-dense small base
stations (BSs) exploit mmWave massive MIMO for access and backhaul, while
macrocell BS provides the control service with low frequency band. However, the
channel estimation for mmWave massive MIMO can be challenging, since the pilot
overhead to acquire the channels associated with a large number of antennas in
mmWave massive MIMO can be prohibitively high. This paper proposes a structured
compressive sensing (SCS)-based channel estimation scheme, where the angular
sparsity of mmWave channels is exploited to reduce the required pilot overhead.
Specifically, since the path loss for non-line-of-sight paths is much larger
than that for line-of-sight paths, the mmWave massive channels in the angular
domain appear the obvious sparsity. By exploiting such sparsity, the required
pilot overhead only depends on the small number of dominated multipath.
Moreover, the sparsity within the system bandwidth is almost unchanged, which
can be exploited for the further improved performance. Simulation results
demonstrate that the proposed scheme outperforms its counterpart, and it can
approach the performance bound.Comment: 6 pages, 5 figures. Millimeter-wave (mmWave), mmWave massive MIMO,
compressive sensing (CS), hybrid precoding, channel estimation, access,
backhaul, ultra-dense network (UDN), heterogeneous network (HetNet). arXiv
admin note: substantial text overlap with arXiv:1604.03695, IEEE
International Conference on Communications (ICC'16), May 2016, Kuala Lumpur,
Malaysi
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