3,244 research outputs found
Adaptive Reduced-Rank Minimum Symbol-Error-Rate Receive Processing for Large-Scale Multiple-Antenna Systems
In this work, we propose a novel adaptive reduced-rank receive processing
strategy based on joint preprocessing, decimation and filtering (JPDF) for
large-scale multiple-antenna systems. In this scheme, a reduced-rank framework
is employed for linear receive processing and multiuser interference
suppression based on the minimization of the symbol-error-rate (SER) cost
function. We present a structure with multiple processing branches that
performs a dimensionality reduction, where each branch contains a group of
jointly optimized preprocessing and decimation units, followed by a linear
receive filter. We then develop stochastic gradient (SG) algorithms to compute
the parameters of the preprocessing and receive filters, along with a
low-complexity decimation technique for both binary phase shift keying (BPSK)
and -ary quadrature amplitude modulation (QAM) symbols. In addition, an
automatic parameter selection scheme is proposed to further improve the
convergence performance of the proposed reduced-rank algorithms. Simulation
results are presented for time-varying wireless environments and show that the
proposed JPDF minimum-SER receive processing strategy and algorithms achieve a
superior performance than existing methods with a reduced computational
complexity.Comment: 16 pages, 13 figures, IEEE Transactions on Communications, 201
Flexible Widely-Linear Multi-Branch Decision Feedback Detection Algorithms for Massive MIMO Systems
This paper presents widely-linear multi-branch decision feedback detection
techniques for large-scale multiuser multiple-antenna systems. We consider a
scenario with impairments in the radio-frequency chain in which the in-phase
(I) and quadrature (Q) components exhibit an imbalance, which degrades the
receiver performance and originates non-circular signals. A widely-linear
multi-branch decision feedback receiver is developed to mitigate both the
multiuser interference and the I/Q imbalance effects. An iterative detection
and decoding scheme with the proposed receiver and convolutional codes is also
devised. Simulation results show that the proposed techniques outperform
existing algorithms.Comment: 3 figures, 9 pages. arXiv admin note: text overlap with
arXiv:1308.272
Detection and Estimation Algorithms in Massive MIMO Systems
This book chapter reviews signal detection and parameter estimation
techniques for multiuser multiple-antenna wireless systems with a very large
number of antennas, known as massive multi-input multi-output (MIMO) systems.
We consider both centralized antenna systems (CAS) and distributed antenna
systems (DAS) architectures in which a large number of antenna elements are
employed and focus on the uplink of a mobile cellular system. In particular, we
focus on receive processing techniques that include signal detection and
parameter estimation problems and discuss the specific needs of massive MIMO
systems. Simulation results illustrate the performance of detection and
estimation algorithms under several scenarios of interest. Key problems are
discussed and future trends in massive MIMO systems are pointed out.Comment: 7 figures, 14 pages. arXiv admin note: substantial text overlap with
arXiv:1310.728
Study of Channel Estimation Algorithms for Large-Scale Multiple-Antenna Systems using 1-Bit ADCs and Oversampling
Large-scale multiple-antenna systems with large bandwidth are fundamental for
future wireless communications, where the base station employs a large antenna
array. In this scenario, one problem faced is the large energy consumption as
the number of receive antennas scales up. Recently, low-resolution
analog-to-digital converters (ADCs) have attracted much attention.
Specifically, 1-bit ADCs are suitable for such systems due to their low cost
and low energy consumption. This paper considers uplink large-scale
multiple-antenna systems with 1-bit ADCs on each receive antenna. We
investigate the benefits of using oversampling for channel estimation in terms
of the mean square error and symbol error rate performance. In particular,
low-resolution aware channel estimators are developed based on the Bussgang
decomposition for 1-bit oversampled systems and analytical bounds on the mean
square error are also investigated. Numerical results are provided to
illustrate the performance of the proposed channel estimation algorithms and
the derived theoretical bounds.Comment: 11 figures, 14 page
Multi-User Flexible Coordinated Beamforming using Lattice Reduction for Massive MIMO Systems
The application of precoding algorithms in multi-user massive multiple-input
multiple-output (MU-Massive-MIMO) systems is restricted by the dimensionality
constraint that the number of transmit antennas has to be greater than or equal
to the total number of receive antennas. In this paper, a lattice reduction
(LR)-aided flexible coordinated beamforming (LR-FlexCoBF) algorithm is proposed
to overcome the dimensionality constraint in overloaded MU-Massive-MIMO
systems. A random user selection scheme is integrated with the proposed
LR-FlexCoBF to extend its application to MU-Massive-MIMO systems with arbitary
overloading levels. Simulation results show that significant improvements in
terms of bit error rate (BER) and sum-rate performances can be achieved by the
proposed LR-FlexCoBF precoding algorithm.Comment: 5 figures, Eusipc
Study of Channel Estimation with Oversampling for 1-bit Large-Scale MIMO Systems
In this paper, we propose an oversampling based low-resolution aware least
squares channel estimator for large-scale multiple-antenna systems with 1-bit
analog-to-digital converters on each receive antenna. To mitigate the
information loss caused by the coarse quantization, oversampling is applied at
the receiver, where the sampling rate is faster than the Nyquist rate. We also
characterize analytical performances, in terms of the deterministic
Cram\'er-Rao bounds, on estimating the channel parameters. Based on the
correlation of the filtered noise, both the Fisher information for white noise
and a lower bound of Fisher information for colored noise are provided.
Numerical results are provided to illustrate the mean square error performances
of the proposed channel estimator and the corresponding Cram\'er-Rao bound as a
function of the signal-to-noise ratio.Comment: 7 pages, 3 figure
Study of BEM-Type Channel Estimation Techniques for 5G Multicarrier Systems
In this paper, we investigate channel estimation techniques for 5G
multicarrier systems. Due to the characteristics of the 5G application
scenarios, channel estimation techniques have been tested in Orthogonal
Frequency Division Multiplexing (OFDM) and Generalized Frequency Division
Multiplexing (GFDM) systems. The orthogonality between subcarriers in OFDM
systems permits inserting and extracting pilots without interference. However,
due to pulse shaping, subcarriers in GFDM are no longer orthogonal and
interfere with each other. Due to such interference, the channel estimation for
GFDM is not trivial. A robust and low-complexity channel estimator can be
obtained by combining a minimum mean-square error (MMSE) regularization and the
basis expansion model (BEM) approach. In this work, we develop a BEM-type
channel estimator along with a strategy to obtain the covariance matrix of the
BEM coefficients. Simulations show that the BEM-type channel estimation shows
performance close to that of the linear MMSE (LMMSE), even though there is no
need to know the channel power delay profile, and its complexity is low.Comment: 2 figures, 7 page
Study of Unique-Word Based GFDM Transmission Systems
In this paper, we propose the use of a deterministic sequence, known as
unique word (UW), instead of the cyclic prefix (CP) in generalized frequency
division multiplexing (GFDM) systems. The UW consists of known sequences that,
if not null, can be used advantageously for synchronization and channel
estimation purposes. In addition, UW allows the application of a highly
efficient linear minimum mean squared error (LMMSE) smoother for noise
reduction at the receiver. To avoid the conditions of non-orthogonality caused
by the insertion of the UW and performance degradation in time varying
frequency-selective channels, we use frequency-shift offset quadrature
amplitude modulation (FS-OQAM). We present a signal model of a UW-GFDM system
considering a single and multiple UWs. We then develop an LMMSE receive filter
for signal reception of the proposed UW-GFDM system. Simulations show that the
proposed UW-GFDM system outperforms prior work.Comment: 5 pages, 4 figure
Study of Switched Max-Link Buffer-Aided Relay Selection for Cooperative MIMO Systems
In this paper, we investigate relay selection for cooperative
multiple-antenna systems that are equipped with buffers, which increase the
reliability of wireless links. In particular, we present a novel relay
selection technique based on switching and the Max-Link protocol that is named
Switched Max-Link. We also introduce a novel relay selection criterion based on
the maximum likelihood (ML) principle denoted maximum minimum distance that is
incorporated into. Simulations are then employed to evaluate the performance of
the proposed and existing techniques.Comment: 8 pages, 3 figures. arXiv admin note: text overlap with
arXiv:1707.0095
Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A Survey, Classification and Challenges
Precoding has been conventionally considered as an effective means of
mitigating the interference and efficiently exploiting the available in the
multiantenna downlink channel, where multiple users are simultaneously served
with independent information over the same channel resources. The early works
in this area were focused on transmitting an individual information stream to
each user by constructing weighted linear combinations of symbol blocks
(codewords). However, more recent works have moved beyond this traditional view
by: i) transmitting distinct data streams to groups of users and ii) applying
precoding on a symbol-per-symbol basis. In this context, the current survey
presents a unified view and classification of precoding techniques with respect
to two main axes: i) the switching rate of the precoding weights, leading to
the classes of block- and symbol-level precoding, ii) the number of users that
each stream is addressed to, hence unicast-/multicast-/broadcast- precoding.
Furthermore, the classified techniques are compared through representative
numerical results to demonstrate their relative performance and uncover
fundamental insights. Finally, a list of open theoretical problems and
practical challenges are presented to inspire further research in this area.Comment: Submitted to IEEE Communications Surveys & Tutorial
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