39 research outputs found
60 GHz Blockage Study Using Phased Arrays
The millimeter wave (mmWave) frequencies offer the potential for enormous
capacity wireless links. However, designing robust communication systems at
these frequencies requires that we understand the channel dynamics over both
time and space: mmWave signals are extremely vulnerable to blocking and the
channel can thus rapidly appear and disappear with small movement of obstacles
and reflectors. In rich scattering environments, different paths may experience
different blocking trajectories and understanding these multi-path blocking
dynamics is essential for developing and assessing beamforming and
beam-tracking algorithms. This paper presents the design and experimental
results of a novel measurement system which uses phased arrays to perform
mmWave dynamic channel measurements. Specifically, human blockage and its
effects across multiple paths are investigated with only several microseconds
between successive measurements. From these measurements we develop a modeling
technique which uses low-rank tensor factorization to separate the available
paths so that their joint statistics can be understood.Comment: To appear in the Proceedings of the 51st Asilomar Conference on
Signals, Systems, and Computers, 201
Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications
Reconfigurable Intelligent Surfaces (RISs) have been recently considered as
an energy-efficient solution for future wireless networks due to their fast and
low-power configuration, which has increased potential in enabling massive
connectivity and low-latency communications. Accurate and low-overhead channel
estimation in RIS-based systems is one of the most critical challenges due to
the usually large number of RIS unit elements and their distinctive hardware
constraints. In this paper, we focus on the downlink of a RIS-empowered
multi-user Multiple Input Single Output (MISO) downlink communication systems
and propose a channel estimation framework based on the PARAllel FACtor
(PARAFAC) decomposition to unfold the resulting cascaded channel model. We
present two iterative estimation algorithms for the channels between the base
station and RIS, as well as the channels between RIS and users. One is based on
alternating least squares (ALS), while the other uses vector approximate
message passing to iteratively reconstruct two unknown channels from the
estimated vectors. To theoretically assess the performance of the ALS-based
algorithm, we derived its estimation Cram\'er-Rao Bound (CRB). We also discuss
the achievable sum-rate computation with estimated channels and different
precoding schemes for the base station. Our extensive simulation results show
that our algorithms outperform benchmark schemes and that the ALS technique
achieve the CRB. It is also demonstrated that the sum rate using the estimated
channels reached that of perfect channel estimation under various settings,
thus, verifying the effectiveness and robustness of the proposed estimation
algorithms
5G Positioning and Mapping with Diffuse Multipath
5G mmWave communication is useful for positioning due to the geometric
connection between the propagation channel and the propagation environment.
Channel estimation methods can exploit the resulting sparsity to estimate
parameters(delay and angles) of each propagation path, which in turn can be
exploited for positioning and mapping. When paths exhibit significant spread in
either angle or delay, these methods breakdown or lead to significant biases.
We present a novel tensor-based method for channel estimation that allows
estimation of mmWave channel parameters in a non-parametric form. The method is
able to accurately estimate the channel, even in the absence of a specular
component. This in turn enables positioning and mapping using only diffuse
multipath. Simulation results are provided to demonstrate the efficacy of the
proposed approach