1,576 research outputs found
A Generalized Framework on Beamformer Design and CSI Acquisition for Single-Carrier Massive MIMO Systems in Millimeter Wave Channels
In this paper, we establish a general framework on the reduced dimensional
channel state information (CSI) estimation and pre-beamformer design for
frequency-selective massive multiple-input multiple-output MIMO systems
employing single-carrier (SC) modulation in time division duplex (TDD) mode by
exploiting the joint angle-delay domain channel sparsity in millimeter (mm)
wave frequencies. First, based on a generic subspace projection taking the
joint angle-delay power profile and user-grouping into account, the reduced
rank minimum mean square error (RR-MMSE) instantaneous CSI estimator is derived
for spatially correlated wideband MIMO channels. Second, the statistical
pre-beamformer design is considered for frequency-selective SC massive MIMO
channels. We examine the dimension reduction problem and subspace (beamspace)
construction on which the RR-MMSE estimation can be realized as accurately as
possible. Finally, a spatio-temporal domain correlator type reduced rank
channel estimator, as an approximation of the RR-MMSE estimate, is obtained by
carrying out least square (LS) estimation in a proper reduced dimensional
beamspace. It is observed that the proposed techniques show remarkable
robustness to the pilot interference (or contamination) with a significant
reduction in pilot overhead
Channel Estimation for mmWave Massive MIMO Based Access and Backhaul in Ultra-Dense Network
Millimeter-wave (mmWave) massive MIMO used for access and backhaul in
ultra-dense network (UDN) has been considered as the promising 5G technique. We
consider such an heterogeneous network (HetNet) that ultra-dense small base
stations (BSs) exploit mmWave massive MIMO for access and backhaul, while
macrocell BS provides the control service with low frequency band. However, the
channel estimation for mmWave massive MIMO can be challenging, since the pilot
overhead to acquire the channels associated with a large number of antennas in
mmWave massive MIMO can be prohibitively high. This paper proposes a structured
compressive sensing (SCS)-based channel estimation scheme, where the angular
sparsity of mmWave channels is exploited to reduce the required pilot overhead.
Specifically, since the path loss for non-line-of-sight paths is much larger
than that for line-of-sight paths, the mmWave massive channels in the angular
domain appear the obvious sparsity. By exploiting such sparsity, the required
pilot overhead only depends on the small number of dominated multipath.
Moreover, the sparsity within the system bandwidth is almost unchanged, which
can be exploited for the further improved performance. Simulation results
demonstrate that the proposed scheme outperforms its counterpart, and it can
approach the performance bound.Comment: 6 pages, 5 figures. Millimeter-wave (mmWave), mmWave massive MIMO,
compressive sensing (CS), hybrid precoding, channel estimation, access,
backhaul, ultra-dense network (UDN), heterogeneous network (HetNet). arXiv
admin note: substantial text overlap with arXiv:1604.03695, IEEE
International Conference on Communications (ICC'16), May 2016, Kuala Lumpur,
Malaysi
Multiuser Millimeter Wave Beamforming Strategies with Quantized and Statistical CSIT
To alleviate the high cost of hardware in mmWave systems, hybrid
analog/digital precoding is typically employed. In the conventional two-stage
feedback scheme, the analog beamformer is determined by beam search and
feedback to maximize the desired signal power of each user. The digital
precoder is designed based on quantization and feedback of effective channel to
mitigate multiuser interference. Alternatively, we propose a one-stage feedback
scheme which effectively reduces the complexity of the signalling and feedback
procedure. Specifically, the second-order channel statistics are leveraged to
design digital precoder for interference mitigation while all feedback overhead
is reserved for precise analog beamforming. Under a fixed total feedback
constraint, we investigate the conditions under which the one-stage feedback
scheme outperforms the conventional two-stage counterpart. Moreover, a rate
splitting (RS) transmission strategy is introduced to further tackle the
multiuser interference and enhance the rate performance. Consider (1) RS
precoded by the one-stage feedback scheme and (2) conventional transmission
strategy precoded by the two-stage scheme with the same first-stage feedback as
(1) and also certain amount of extra second-stage feedback. We show that (1)
can achieve a sum rate comparable to that of (2). Hence, RS enables remarkable
saving in the second-stage training and feedback overhead.Comment: submitted to TW
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