97 research outputs found
Blind Adaptive Constrained Constant-Modulus Reduced-Rank Interference Suppression Algorithms Based on Interpolation, Switched Decimation and Filtering
This work proposes a blind adaptive reduced-rank scheme and constrained
constant-modulus (CCM) adaptive algorithms for interference suppression in
wireless communications systems. The proposed scheme and algorithms are based
on a two-stage processing framework that consists of a transformation matrix
that performs dimensionality reduction followed by a reduced-rank estimator.
The complex structure of the transformation matrix of existing methods
motivates the development of a blind adaptive reduced-rank constrained (BARC)
scheme along with a low-complexity reduced-rank decomposition. The proposed
BARC scheme and a reduced-rank decomposition based on the concept of joint
interpolation, switched decimation and reduced-rank estimation subject to a set
of constraints are then detailed. The proposed set of constraints ensures that
the multi-path components of the channel are combined prior to dimensionality
reduction. In order to cost-effectively design the BARC scheme, we develop
low-complexity decimation techniques, stochastic gradient and recursive least
squares reduced-rank estimation algorithms. A model-order selection algorithm
for adjusting the length of the estimators is devised along with techniques for
determining the required number of switching branches to attain a predefined
performance. An analysis of the convergence properties and issues of the
proposed optimization and algorithms is carried out, and the key features of
the optimization problem are discussed. We consider the application of the
proposed algorithms to interference suppression in DS-CDMA systems. The results
show that the proposed algorithms outperform the best known reduced-rank
schemes, while requiring lower complexity.Comment: 9 figures; IEEE Transactions on Signal Processing, 201
Coordinate Tomlinson-Harashima Precoding Design for Overloaded Multi-user MIMO Systems
Tomlinson-Harashima precoding (THP) is a nonlinear processing technique
employed at the transmit side to implement the concept of dirty paper coding
(DPC). The perform of THP, however, is restricted by the dimensionality
constraint that the number of transmit antennas has to be greater or equal to
the total number of receive antennas. In this paper, we propose an iterative
coordinate THP algorithm for the scenarios in which the total number of receive
antennas is larger than the number of transmit antennas. The proposed algorithm
is implemented on two types of THP structures, the decentralized THP (dTHP)
with diagonal weighted filters at the receivers of the users, and the
centralized THP (cTHP) with diagonal weighted filter at the transmitter.
Simulation results show that a much better bit error rate (BER) and sum-rate
performances can be achieved by the proposed iterative coordinate THP compared
to the previous linear art.Comment: 3 figures, 6 pages, ISWCS 2014. arXiv admin note: text overlap with
arXiv:1401.475
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
Low-Complexity Variable Forgetting Factor Constrained Constant Modulus RLS Algorithm for Adaptive Beamforming
In this paper, a recursive least squares (RLS) based blind adaptive
beamforming algorithm that features a new variable forgetting factor (VFF)
mechanism is presented. The beamformer is designed according to the constrained
constant modulus (CCM) criterion, and the proposed adaptive algorithm operates
in the generalized sidelobe canceler (GSC) structure. A detailed study of its
operating properties is carried out, including a convexity analysis and a mean
squared error (MSE) analysis of its steady-state behavior. The results of
numerical experiments demonstrate that the proposed VFF mechanism achieves a
superior learning and tracking performance compared to other VFF mechanisms.Comment: 10 pages, 4 figures, Elsevier Signal Processing, 201
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 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
Study of Robust Distributed Beamforming Based on Cross-Correlation and Subspace Projection Techniques
In this work, we present a novel robust distributed beamforming (RDB)
approach to mitigate the effects of channel errors on wireless networks
equipped with relays based on the exploitation of the cross-correlation between
the received data from the relays at the destination and the system output. The
proposed RDB method, denoted cross-correlation and subspace projection (CCSP)
RDB, considers a total relay transmit power constraint in the system and the
objective of maximizing the output signal-to-interference-plus-noise ratio
(SINR). The relay nodes are equipped with an amplify-and-forward (AF) protocol
and we assume that the channel state information (CSI) is imperfectly known at
the relays and there is no direct link between the sources and the destination.
The CCSP does not require any costly optimization procedure and simulations
show an excellent performance as compared to previously reported algorithms.Comment: 3 figures, 7 pages. arXiv admin note: text overlap with
arXiv:1707.00953
Study of Efficient Robust Adaptive Beamforming Algorithms Based on Shrinkage Techniques
This paper proposes low-complexity robust adaptive beamforming (RAB)
techniques based on shrinkage methods. We firstly briefly review a
Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) batch algorithm to
estimate the desired signal steering vector mismatch, in which the
interference-plus-noise covariance (INC) matrix is also estimated with a
recursive matrix shrinkage method. Then we develop low complexity adaptive
robust version of the conjugate gradient (CG) algorithm to both estimate the
steering vector mismatch and update the beamforming weights. A computational
complexity study of the proposed and existing algorithms is carried out.
Simulations are conducted in local scattering scenarios and comparisons to
existing RAB techniques are provided.Comment: 9 pages, 2 figures. arXiv admin note: text overlap with
arXiv:1505.0678
Study of Joint MSINR and Relay Selection Algorithms for Distributed Beamforming
This paper presents joint maximum signal-to-interference-plus-noise ratio
(MSINR) and relay selection algorithms for distributed beamforming. We propose
a joint MSINR and restricted greedy search relay selection (RGSRS) algorithm
with a total relay transmit power constraint that iteratively optimizes both
the beamforming weights at the relays nodes, maximizing the SINR at the
destination. Specifically, we devise a relay selection scheme that based on
greedy search and compare it to other schemes like restricted random relay
selection (RRRS) and restricted exhaustive search relay selection (RESRS). A
complexity analysis is provided and simulation results show that the proposed
joint MSINR and RGSRS algorithm achieves excellent bit error rate (BER) and
SINR performances.Comment: 7 pages, 2 figures. arXiv admin note: text overlap with
arXiv:1707.0095
Sparsity-Based STAP Design Based on Alternating Direction Method with Gain/Phase Errors
We present a novel sparsity-based space-time adaptive processing (STAP)
technique based on the alternating direction method to overcome the severe
performance degradation caused by array gain/phase (GP) errors. The proposed
algorithm reformulates the STAP problem as a joint optimization problem of the
spatio-Doppler profile and GP errors in both single and multiple snapshots, and
introduces a target detector using the reconstructed spatio-Doppler profiles.
Simulations are conducted to illustrate the benefits of the proposed algorithm.Comment: 7 figures, 1 tabl
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