1,497 research outputs found
Achievable Rates of Multi-User Millimeter Wave Systems with Hybrid Precoding
Millimeter wave (mmWave) systems will likely employ large antenna arrays at
both the transmitters and receivers. A natural application of antenna arrays is
simultaneous transmission to multiple users, which requires multi-user
precoding at the transmitter. Hardware constraints, however, make it difficult
to apply conventional lower frequency MIMO precoding techniques at mmWave. This
paper proposes and analyzes a low complexity hybrid analog/digital beamforming
algorithm for downlink multi-user mmWave systems. Hybrid precoding involves a
combination of analog and digital processing that is motivated by the
requirement to reduce the power consumption of the complete radio frequency and
mixed signal hardware. The proposed algorithm configures hybrid precoders at
the transmitter and analog combiners at multiple receivers with a small
training and feedback overhead. For this algorithm, we derive a lower bound on
the achievable rate for the case of single-path channels, show its asymptotic
optimality at large numbers of antennas, and make useful insights for more
general cases. Simulation results show that the proposed algorithm offers
higher sum rates compared with analog-only beamforming, and approaches the
performance of the unconstrained digital precoding solutions.Comment: to be presented in IEEE ICC 2015 - Workshop on 5G & Beyond - Enabling
Technologies and Application
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
Multiuser Precoding and Channel Estimation for Hybrid Millimeter Wave MIMO Systems
In this paper, we develop a low-complexity channel estimation for hybrid
millimeter wave (mmWave) systems, where the number of radio frequency (RF)
chains is much less than the number of antennas equipped at each transceiver.
The proposed channel estimation algorithm aims to estimate the strongest
angle-of-arrivals (AoAs) at both the base station (BS) and the users. Then all
the users transmit orthogonal pilot symbols to the BS via these estimated
strongest AoAs to facilitate the channel estimation. The algorithm does not
require any explicit channel state information (CSI) feedback from the users
and the associated signalling overhead of the algorithm is only proportional to
the number of users, which is significantly less compared to various existing
schemes. Besides, the proposed algorithm is applicable to both non-sparse and
sparse mmWave channel environments. Based on the estimated CSI, zero-forcing
(ZF) precoding is adopted for multiuser downlink transmission. In addition, we
derive a tight achievable rate upper bound of the system. Our analytical and
simulation results show that the proposed scheme offer a considerable
achievable rate gain compared to fully digital systems, where the number of RF
chains equipped at each transceiver is equal to the number of antennas.
Furthermore, the achievable rate performance gap between the considered hybrid
mmWave systems and the fully digital system is characterized, which provides
useful system design insights.Comment: 6 pages, accepted for presentation, ICC 201
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
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