315 research outputs found
Position and Orientation Estimation through Millimeter Wave MIMO in 5G Systems
Millimeter wave signals and large antenna arrays are considered enabling
technologies for future 5G networks. While their benefits for achieving
high-data rate communications are well-known, their potential advantages for
accurate positioning are largely undiscovered. We derive the Cram\'{e}r-Rao
bound (CRB) on position and rotation angle estimation uncertainty from
millimeter wave signals from a single transmitter, in the presence of
scatterers. We also present a novel two-stage algorithm for position and
rotation angle estimation that attains the CRB for average to high
signal-to-noise ratio. The algorithm is based on multiple measurement vectors
matching pursuit for coarse estimation, followed by a refinement stage based on
the space-alternating generalized expectation maximization algorithm. We find
that accurate position and rotation angle estimation is possible using signals
from a single transmitter, in either line-of- sight, non-line-of-sight, or
obstructed-line-of-sight conditions.Comment: The manuscript has been revised, and increased from 27 to 31 pages.
Also, Fig.2, Fig. 10 and Table I are adde
Channel Estimation for Millimeter-Wave Massive MIMO with Hybrid Precoding over Frequency-Selective Fading Channels
Channel estimation for millimeter-wave (mmWave) massive MIMO with hybrid
precoding is challenging, since the number of radio frequency (RF) chains is
usually much smaller than that of antennas. To date, several channel estimation
schemes have been proposed for mmWave massive MIMO over narrow-band channels,
while practical mmWave channels exhibit the frequency-selective fading (FSF).
To this end, this letter proposes a multi-user uplink channel estimation scheme
for mmWave massive MIMO over FSF channels. Specifically, by exploiting the
angle-domain structured sparsity of mmWave FSF channels, a distributed
compressive sensing (DCS)-based channel estimation scheme is proposed.
Moreover, by using the grid matching pursuit strategy with adaptive measurement
matrix, the proposed algorithm can solve the power leakage problem caused by
the continuous angles of arrival or departure (AoA/AoD). Simulation results
verify that the good performance of the proposed solution.Comment: 4 pages, 3 figures, accepted by IEEE Communications Letters. This
paper may be the first one that investigates the frequency selective fading
channel estimation for mmWave massive MIMO systems with hybrid precoding. Key
words: Millimeter-wave (mmWave) massive MIMO, frequency-selective fading,
channel estimation, compressive sensing, hybrid precodin
Pilot Beam Sequence Design for Channel Estimation in Millimeter-Wave MIMO Systems: A POMDP Framework
In this paper, adaptive pilot beam sequence design for channel estimation in
large millimeter-wave (mmWave) MIMO systems is considered. By exploiting the
sparsity of mmWave MIMO channels with the virtual channel representation and
imposing a Markovian random walk assumption on the physical movement of the
line-of-sight (LOS) and reflection clusters, it is shown that the sparse
channel estimation problem in large mmWave MIMO systems reduces to a sequential
detection problem that finds the locations and values of the non-zero-valued
bins in a two-dimensional rectangular grid, and the optimal adaptive pilot
design problem can be cast into the framework of a partially observable Markov
decision process (POMDP). Under the POMDP framework, an optimal adaptive pilot
beam sequence design method is obtained to maximize the accumulated
transmission data rate for a given period of time. Numerical results are
provided to validate our pilot signal design method and they show that the
proposed method yields good performance.Comment: 6 pages, 6 figures, submitted to IEEE ICC 201
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