787 research outputs found
Adaptive AoA estimation and beamforming with hybrid antenna arrays
A new type of hybrid antenna array consisting of analogue subarrays followed by a digital beamformer is proposed for practical implementation of long range high data rate millimetre wave communications systems. An adaptive algorithm, referred to as the differential beam search (DBS), is proposed for the angle of arrival (AoA) estimation to control the phase shifters in the analogue subarrays and to perform digital beamforming. This algorithm does not need the knowledge of a reference signal and effectively solves the phase ambiguity problem in AoA estimation inherent to the practical subarray configuration. The performance of the proposed DBS algorithms is demonstrated by simulations. © 2009 IEEE
Millimeter Wave MIMO Channel Estimation Based on Adaptive Compressed Sensing
Multiple-input multiple-output (MIMO) systems are well suited for
millimeter-wave (mmWave) wireless communications where large antenna arrays can
be integrated in small form factors due to tiny wavelengths, thereby providing
high array gains while supporting spatial multiplexing, beamforming, or antenna
diversity. It has been shown that mmWave channels exhibit sparsity due to the
limited number of dominant propagation paths, thus compressed sensing
techniques can be leveraged to conduct channel estimation at mmWave
frequencies. This paper presents a novel approach of constructing beamforming
dictionary matrices for sparse channel estimation using the continuous basis
pursuit (CBP) concept, and proposes two novel low-complexity algorithms to
exploit channel sparsity for adaptively estimating multipath channel parameters
in mmWave channels. We verify the performance of the proposed CBP-based
beamforming dictionary and the two algorithms using a simulator built upon a
three-dimensional mmWave statistical spatial channel model, NYUSIM, that is
based on real-world propagation measurements. Simulation results show that the
CBP-based dictionary offers substantially higher estimation accuracy and
greater spectral efficiency than the grid-based counterpart introduced by
previous researchers, and the algorithms proposed here render better
performance but require less computational effort compared with existing
algorithms.Comment: 7 pages, 5 figures, in 2017 IEEE International Conference on
Communications Workshop (ICCW), Paris, May 201
Hybrid Beamforming via the Kronecker Decomposition for the Millimeter-Wave Massive MIMO Systems
Despite its promising performance gain, the realization of mmWave massive
MIMO still faces several practical challenges. In particular, implementing
massive MIMO in the digital domain requires hundreds of RF chains matching the
number of antennas. Furthermore, designing these components to operate at the
mmWave frequencies is challenging and costly. These motivated the recent
development of hybrid-beamforming where MIMO processing is divided for separate
implementation in the analog and digital domains, called the analog and digital
beamforming, respectively. Analog beamforming using a phase array introduces
uni-modulus constraints on the beamforming coefficients, rendering the
conventional MIMO techniques unsuitable and call for new designs. In this
paper, we present a systematic design framework for hybrid beamforming for
multi-cell multiuser massive MIMO systems over mmWave channels characterized by
sparse propagation paths. The framework relies on the decomposition of analog
beamforming vectors and path observation vectors into Kronecker products of
factors being uni-modulus vectors. Exploiting properties of Kronecker mixed
products, different factors of the analog beamformer are designed for either
nulling interference paths or coherently combining data paths. Furthermore, a
channel estimation scheme is designed for enabling the proposed hybrid
beamforming. The scheme estimates the AoA of data and interference paths by
analog beam scanning and data-path gains by analog beam steering. The
performance of the channel estimation scheme is analyzed. In particular, the
AoA spectrum resulting from beam scanning, which displays the magnitude
distribution of paths over the AoA range, is derived in closed-form. It is
shown that the inter-cell interference level diminishes inversely with the
array size, the square root of pilot sequence length and the spatial separation
between paths.Comment: Submitted to IEEE JSAC Special Issue on Millimeter Wave
Communications for Future Mobile Networks, minor revisio
Compressed Sensing Based Multi-User Millimeter Wave Systems: How Many Measurements Are Needed?
Millimeter wave (mmWave) systems will likely employ directional beamforming
with large antenna arrays at both the transmitters and receivers. Acquiring
channel knowledge to design these beamformers, however, is challenging due to
the large antenna arrays and small signal-to-noise ratio before beamforming. In
this paper, we propose and evaluate a downlink system operation for multi-user
mmWave systems based on compressed sensing channel estimation and conjugate
analog beamforming. Adopting the achievable sum-rate as a performance metric,
we show how many compressed sensing measurements are needed to approach the
perfect channel knowledge performance. The results illustrate that the proposed
algorithm requires an order of magnitude less training overhead compared with
traditional lower-frequency solutions, while employing mmWave-suitable
hardware. They also show that the number of measurements need to be optimized
to handle the trade-off between the channel estimate quality and the training
overhead.Comment: IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP) 201
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