1,381 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
Receive Spatial Modulation for Massive MIMO Systems
In this paper, we consider the downlink of a massive
multiple-input-multiple-output (MIMO) single user transmission system operating
in the millimeter wave outdoor narrowband channel environment. We propose a
novel receive spatial modulation architecture aimed to reduce the power
consumption at the user terminal, while attaining a significant throughput. The
energy consumption reduction is obtained through the use of analog devices
(amplitude detector), which reduces the number of radio frequency chains and
analog-to-digital-converters (ADCs). The base station transmits spatial and
modulation symbols per channel use. We show that the optimal spatial symbol
detector is a threshold detector that can be implemented by using one bit ADC.
We derive closed form expressions for the detection threshold at different
signal-to-noise-ratio (SNR) regions showing that a simple threshold can be
obtained at high SNR and its performance approaches the exact threshold. We
derive expressions for the average bit error probability in the presence and
absence of the threshold estimation error showing that a small number of pilot
symbols is needed. A performance comparison is done between the proposed system
and fully digital MIMO showing that a suitable constellation selection can
reduce the performance gap
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities
Recently there has been a flurry of research on the use of reconfigurable
intelligent surfaces (RIS) in wireless networks to create smart radio
environments. In a smart radio environment, surfaces are capable of
manipulating the propagation of incident electromagnetic waves in a
programmable manner to actively alter the channel realization, which turns the
wireless channel into a controllable system block that can be optimized to
improve overall system performance. In this article, we provide a tutorial
overview of reconfigurable intelligent surfaces (RIS) for wireless
communications. We describe the working principles of reconfigurable
intelligent surfaces (RIS) and elaborate on different candidate implementations
using metasurfaces and reflectarrays. We discuss the channel models suitable
for both implementations and examine the feasibility of obtaining accurate
channel estimates. Furthermore, we discuss the aspects that differentiate RIS
optimization from precoding for traditional MIMO arrays highlighting both the
arising challenges and the potential opportunities associated with this
emerging technology. Finally, we present numerical results to illustrate the
power of an RIS in shaping the key properties of a MIMO channel.Comment: to appear in the IEEE Transactions on Cognitive Communications and
Networking (TCCN
Beamspace Aware Adaptive Channel Estimation for Single-Carrier Time-varying Massive MIMO Channels
In this paper, the problem of sequential beam construction and adaptive
channel estimation based on reduced rank (RR) Kalman filtering for
frequency-selective massive multiple-input multiple-output (MIMO) systems
employing single-carrier (SC) in time division duplex (TDD) mode are
considered. In two-stage beamforming, a new algorithm for statistical
pre-beamformer design is proposed for spatially correlated time-varying
wideband MIMO channels under the assumption that the channel is a stationary
Gauss-Markov random process. The proposed algorithm yields a nearly optimal
pre-beamformer whose beam pattern is designed sequentially with low complexity
by taking the user-grouping into account, and exploiting the properties of
Kalman filtering and associated prediction error covariance matrices. The
resulting design, based on the second order statistical properties of the
channel, generates beamspace on which the RR Kalman estimator can be realized
as accurately as possible. It is observed that the adaptive channel estimation
technique together with the proposed sequential beamspace construction shows
remarkable robustness to the pilot interference. This comes with significant
reduction in both pilot overhead and dimension of the pre-beamformer lowering
both hardware complexity and power consumption.Comment: 7 pages, 3 figures, accepted by IEEE ICC 2017 Wireless Communications
Symposiu
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