2 research outputs found
Millimeter-Wave Beamformed Full-dimensional MIMO Channel Estimation Based on Atomic Norm Minimization
The millimeter-wave (mmWave) full-dimensional (FD) MIMO system employs planar
arrays at both the base station and user equipment and can simultaneously
support both azimuth and elevation beamforming. In this paper, we propose
atomic-norm-based methods for mmWave FD-MIMO channel estimation under both
uniform planar arrays (UPA) and non-uniform planar arrays (NUPA). Unlike
existing algorithms such as compressive sensing (CS) or subspace methods, the
atomic-norm-based algorithms do not require to discretize the angle spaces of
the angle of arrival (AoA) and angle of departure (AoD) into grids, thus
provide much better accuracy in estimation. In the UPA case, to reduce the
computational complexity, the original large-scale 4D atomic norm minimization
problem is approximately reformulated as a semi-definite program (SDP)
containing two decoupled two-level Toeplitz matrices. The SDP is then solved
via the alternating direction method of multipliers (ADMM) where each iteration
involves only closed-form computations. In the NUPA case, the atomic-norm-based
formulation for channel estimation becomes nonconvex and a
gradient-decent-based algorithm is proposed to solve the problem. Simulation
results show that the proposed algorithms achieve better performance than the
CS-based and subspace-based algorithms
Beamforming Network Optimization for Reducing Channel Time Variation in High-Mobility Massive MIMO
Communications in high-mobility environments have caught a lot of attentions
recently. In this paper, fast time-varying channels for massive multiple-input
multiple-output (MIMO) systems are addressed. We derive the exact channel power
spectrum density (PSD) for the uplink from a high-speed railway (HSR) to a base
station (BS) and propose to further reduce the channel time variation via
beamforming network optimization. A large-scale uniform linear array (ULA) is
equipped at the HSR to separate multiple Doppler shifts in angle domain through
high-resolution transmit beamforming. Each branch comprises a dominant Doppler
shift, which can be compensated to suppress the channel time variation, and we
derive the channel PSD and the Doppler spread to assess the residual channel
time variation. Interestingly, the channel PSD can be exactly expressed as the
product of a pattern function and a beam-distortion function. The former
reflects the impact of array aperture and is the converted radiation pattern of
ULA, while the latter depends on the configuration of beamforming directions.
Inspired by the PSD analysis, we introduce a common configurable amplitudes and
phases (CCAP) parameter to optimize the beamforming network, by partly removing
the constant modulus quantized phase constraints of matched filter (MF)
beamformers. In this way, the residual Doppler shifts can be ulteriorly
suppressed, further reducing the residual channel time variation. The optimal
CCAP parameter minimizing the Doppler spread is derived in a closed form.
Numerical results are provided to corroborate both the channel PSD analysis and
the superiority of beamforming network optimization technique.Comment: Double columns, 13 pages, 10 figures, transactions pape