27,121 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
Dispensing with Channel Estimation…
In this article, we investigate the feasibility of noncoherent detection schemes in wireless communication systems as a low-complexity alternative to the family of coherent schemes. The noncoherent schemes require no channel knowledge at the receiver for the detection of the received signal, while the coherent schemes require channel inherently complex estimation, which implies that pilot symbols have to be transmitted resulting in a wastage of the available bandwidth as well as the transmission power
An Iterative Receiver for OFDM With Sparsity-Based Parametric Channel Estimation
In this work we design a receiver that iteratively passes soft information
between the channel estimation and data decoding stages. The receiver
incorporates sparsity-based parametric channel estimation. State-of-the-art
sparsity-based iterative receivers simplify the channel estimation problem by
restricting the multipath delays to a grid. Our receiver does not impose such a
restriction. As a result it does not suffer from the leakage effect, which
destroys sparsity. Communication at near capacity rates in high SNR requires a
large modulation order. Due to the close proximity of modulation symbols in
such systems, the grid-based approximation is of insufficient accuracy. We show
numerically that a state-of-the-art iterative receiver with grid-based sparse
channel estimation exhibits a bit-error-rate floor in the high SNR regime. On
the contrary, our receiver performs very close to the perfect channel state
information bound for all SNR values. We also demonstrate both theoretically
and numerically that parametric channel estimation works well in dense
channels, i.e., when the number of multipath components is large and each
individual component cannot be resolved.Comment: Major revision, accepted for IEEE Transactions on Signal Processin
Two-Way Training for Discriminatory Channel Estimation in Wireless MIMO Systems
This work examines the use of two-way training to efficiently discriminate
the channel estimation performances at a legitimate receiver (LR) and an
unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless
system. This work improves upon the original discriminatory channel estimation
(DCE) scheme proposed by Chang et al where multiple stages of feedback and
retraining were used. While most studies on physical layer secrecy are under
the information-theoretic framework and focus directly on the data transmission
phase, studies on DCE focus on the training phase and aim to provide a
practical signal processing technique to discriminate between the channel
estimation performances at LR and UR. A key feature of DCE designs is the
insertion of artificial noise (AN) in the training signal to degrade the
channel estimation performance at UR. To do so, AN must be placed in a
carefully chosen subspace based on the transmitter's knowledge of LR's channel
in order to minimize its effect on LR. In this paper, we adopt the idea of
two-way training that allows both the transmitter and LR to send training
signals to facilitate channel estimation at both ends. Both reciprocal and
non-reciprocal channels are considered and a two-way DCE scheme is proposed for
each scenario. {For mathematical tractability, we assume that all terminals
employ the linear minimum mean square error criterion for channel estimation.
Based on the mean square error (MSE) of the channel estimates at all
terminals,} we formulate and solve an optimization problem where the optimal
power allocation between the training signal and AN is found by minimizing the
MSE of LR's channel estimate subject to a constraint on the MSE achievable at
UR. Numerical results show that the proposed DCE schemes can effectively
discriminate between the channel estimation and hence the data detection
performances at LR and UR.Comment: 1
Optimal Pilot Symbols Ratio in terms of Spectrum and Energy Efficiency in Uplink CoMP Networks
In wireless networks, Spectrum Efficiency (SE) and Energy Efficiency (EE) can
be affected by the channel estimation that needs to be well designed in
practice. In this paper, considering channel estimation error and non-ideal
backhaul links, we optimize the pilot symbols ratio in terms of SE and EE in
uplink Coordinated Multi-point (CoMP) networks. Modeling the channel estimation
error, we formulate the SE and EE maximization problems by analyzing the system
capacity with imperfect channel estimation. The maximal system capacity in SE
optimization and the minimal transmit power in EE optimization, which both have
the closed-form expressions, are derived by some reasonable approximations to
reduce the complexity of solving complicated equations. Simulations are carried
out to validate the superiority of our scheme, verify the accuracy of our
approximation, and show the effect of pilot symbols ratio.Comment: 5 pages, 3 figures, 2017 IEEE 85th Vehicular Technology Conference
(VTC Spring
- …