77 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
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
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
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
Low-Rank Signal Processing: Design, Algorithms for Dimensionality Reduction and Applications
We present a tutorial on reduced-rank signal processing, design methods and
algorithms for dimensionality reduction, and cover a number of important
applications. A general framework based on linear algebra and linear estimation
is employed to introduce the reader to the fundamentals of reduced-rank signal
processing and to describe how dimensionality reduction is performed on an
observed discrete-time signal. A unified treatment of dimensionality reduction
algorithms is presented with the aid of least squares optimization techniques,
in which several techniques for designing the transformation matrix that
performs dimensionality reduction are reviewed. Among the dimensionality
reduction techniques are those based on the eigen-decomposition of the observed
data vector covariance matrix, Krylov subspace methods, joint and iterative
optimization (JIO) algorithms and JIO with simplified structures and switching
(JIOS) techniques. A number of applications are then considered using a unified
treatment, which includes wireless communications, sensor and array signal
processing, and speech, audio, image and video processing. This tutorial
concludes with a discussion of future research directions and emerging topics.Comment: 23 pages, 6 figure
Study of Buffer-Aided Space-Time Coding for Multiple-Antenna Cooperative Wireless Networks
In this work we propose an adaptive buffer-aided space-time coding scheme for
cooperative wireless networks. A maximum likelihood receiver and adjustable
code vectors are considered subject to a power constraint with an
amplify-and-forward cooperation strategy. Each multiple-antenna relay is
equipped with a buffer and is capable of storing the received symbols before
forwarding them to the destination. We also present an adaptive relay selection
and optimization algorithm, in which the instantaneous signal to noise ratio in
each link is calculated and compared at the destination. An adjustable code
vector obtained by a feedback channel at each relay is employed to form a
space-time coded vector which achieves a higher coding gain than standard
schemes. A stochastic gradient algorithm is developed to compute the parameters
of the adjustable code vector with reduced computational complexity. Simulation
results show that the proposed buffer-aided scheme and algorithm obtain
performance gains over existing schemes.Comment: 7 pages, 2 figure
Joint Power Adjustment and Interference Mitigation Techniques for Cooperative Spread Spectrum Systems
This paper presents joint power allocation and interference mitigation
techniques for the downlink of spread spectrum systems which employ multiple
relays and the amplify and forward cooperation strategy. We propose a joint
constrained optimization framework that considers the allocation of power
levels across the relays subject to an individual power constraint and the
design of linear receivers for interference suppression. We derive constrained
minimum mean-squared error (MMSE) expressions for the parameter vectors that
determine the optimal power levels across the relays and the linear receivers.
In order to solve the proposed optimization problem efficiently, we develop
joint adaptive power allocation and interference suppression algorithms that
can be implemented in a distributed fashion. The proposed stochastic gradient
(SG) and recursive least squares (RLS) algorithms mitigate the interference by
adjusting the power levels across the relays and estimating the parameters of
the linear receiver. SG and RLS channel estimation algorithms are also derived
to determine the coefficients of the channels across the base station, the
relays and the destination terminal. The results of simulations show that the
proposed techniques obtain significant gains in performance and capacity over
non-cooperative systems and cooperative schemes with equal power allocation.Comment: 6 figures. arXiv admin note: text overlap with arXiv:1301.009
Resource Allocation and Interference Mitigation Techniques for Cooperative Multi-Antenna and Spread Spectrum Wireless Networks
This chapter presents joint interference suppression and power allocation
algorithms for DS-CDMA and MIMO networks with multiple hops and
amplify-and-forward and decode-and-forward (DF) protocols. A scheme for joint
allocation of power levels across the relays and linear interference
suppression is proposed. We also consider another strategy for joint
interference suppression and relay selection that maximizes the diversity
available in the system. Simulations show that the proposed cross-layer
optimization algorithms obtain significant gains in capacity and performance
over existing schemes.Comment: 10 figures. arXiv admin note: substantial text overlap with
arXiv:1301.009
Linear Reduced-Rank Interference Suppression for DS-UWB Systems Using Switched Approximations of Adaptive Basis Functions
In this work, we propose a novel low-complexity reduced-rank scheme and
consider its application to linear interference suppression in direct-sequence
ultra-wideband (DS-UWB) systems. Firstly, we investigate a generic reduced-rank
scheme that jointly optimizes a projection vector and a reduced-rank filter by
using the minimum mean-squared error (MMSE) criterion. Then a low-complexity
scheme, denoted switched approximation of adaptive basis functions (SAABF), is
proposed. The SAABF scheme is an extension of the generic scheme, in which the
complexity reduction is achieved by using a multi-branch framework to simplify
the structure of the projection vector. Adaptive implementations for the SAABF
scheme are developed by using least-mean squares (LMS) and recursive
least-squares (RLS) algorithms. We also develop algorithms for selecting the
branch number and the model order of the SAABF scheme. Simulations show that in
the scenarios with severe inter-symbol interference (ISI) and multiple access
interference (MAI), the proposed SAABF scheme has fast convergence and
remarkable interference suppression performance with low complexity.Comment: 9 figures. arXiv admin note: text overlap with arXiv:1305.297
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
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