2 research outputs found
Joint CSIT Acquisition Based on Low-Rank Matrix Completion for FDD Massive MIMO Systems
Channel state information at the transmitter (CSIT) is essential for
frequency-division duplexing (FDD) massive MIMO systems, but conventional
solutions involve overwhelming overhead both for downlink channel training and
uplink channel feedback. In this letter, we propose a joint CSIT acquisition
scheme to reduce the overhead. Particularly, unlike conventional schemes where
each user individually estimates its own channel and then feed it back to the
base station (BS), we propose that all scheduled users directly feed back the
pilot observation to the BS, and then joint CSIT recovery can be realized at
the BS. We further formulate the joint CSIT recovery problem as a low-rank
matrix completion problem by utilizing the low-rank property of the massive
MIMO channel matrix, which is caused by the correlation among users. Finally,
we propose a hybrid low-rank matrix completion algorithm based on the singular
value projection to solve this problem. Simulations demonstrate that the
proposed scheme can provide accurate CSIT with lower overhead than conventional
schemes
Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems
Millimeter wave (mmWave) communications has been regarded as a key enabling
technology for 5G networks. In contrast to conventional
multiple-input-multiple-output (MIMO) systems, precoding in mmWave MIMO cannot
be performed entirely at baseband using digital precoders, as only a limited
number of signal mixers and analog-to-digital converters (ADCs) can be
supported considering their cost and power consumption. As a cost-effective
alternative, a hybrid precoding transceiver architecture, combining a digital
precoder and an analog precoder, has recently received considerable attention.
However, the optimal design of such hybrid precoders has not been fully
understood. In this paper, treating the hybrid precoder design as a matrix
factorization problem, effective alternating minimization (AltMin) algorithms
will be proposed for two different hybrid precoding structures, i.e., the
fully-connected and partially-connected structures. In particular, for the
fully-connected structure, an AltMin algorithm based on manifold optimization
is proposed to approach the performance of the fully digital precoder, which,
however, has a high complexity. Thus, a low-complexity AltMin algorithm is then
proposed, by enforcing an orthogonal constraint on the digital precoder.
Furthermore, for the partially-connected structure, an AltMin algorithm is also
developed with the help of semidefinite relaxation. For practical
implementation, the proposed AltMin algorithms are further extended to the
broadband setting with orthogonal frequency division multiplexing (OFDM)
modulation. Simulation results will demonstrate significant performance gains
of the proposed AltMin algorithms over existing hybrid precoding algorithms.
Moreover, based on the proposed algorithms, simulation comparisons between the
two hybrid precoding structures will provide valuable design insights.Comment: 16 pages,8 figures, to appear in IEEE Journal of Selected Topics in
Signal Processin