376 research outputs found
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
Low-Complexity Hybrid Beamforming for Massive MIMO Systems in Frequency-Selective Channels
Hybrid beamforming for frequency-selective channels is a challenging problem
as the phase shifters provide the same phase shift to all of the subcarriers.
The existing approaches solely rely on the channel's frequency response and the
hybrid beamformers maximize the average spectral efficiency over the whole
frequency band. Compared to state-of-the-art, we show that substantial sum-rate
gains can be achieved, both for rich and sparse scattering channels, by jointly
exploiting the frequency and time domain characteristics of the massive
multiple-input multiple-output (MIMO) channels. In our proposed approach, the
radio frequency (RF) beamformer coherently combines the received symbols in the
time domain and, thus, it concentrates signal's power on a specific time
sample. As a result, the RF beamformer flattens the frequency response of the
"effective" transmission channel and reduces its root mean square delay spread.
Then, a baseband combiner mitigates the residual interference in the frequency
domain. We present the closed-form expressions of the proposed beamformer and
its performance by leveraging the favorable propagation condition of massive
MIMO channels and we prove that our proposed scheme can achieve the performance
of fully-digital zero-forcing when number of employed phase shifter networks is
twice the resolvable multipath components in the time domain.Comment: Accepted to IEEE Acces
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