589 research outputs found
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
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
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
Massive MIMO and Waveform Design for 5th Generation Wireless Communication Systems
This article reviews existing related work and identifies the main challenges
in the key 5G area at the intersection of waveform design and large-scale
multiple antenna systems, also known as Massive MIMO. The property of
self-equalization is introduced for Filter Bank Multicarrier (FBMC)-based
Massive MIMO, which can reduce the number of subcarriers required by the
system. It is also shown that the blind channel tracking property of FBMC can
be used to address pilot contamination -- one of the main limiting factors of
Massive MIMO systems. Our findings shed light into and motivate for an entirely
new research line towards a better understanding of waveform design with
emphasis on FBMC-based Massive MIMO networks.Comment: 6 pages, 2 figures, 1st International Conference on 5G for Ubiquitous
Connectivit
Joint SIC and Relay Selection for Cooperative DS-CDMA Systems
In this work, we propose a cross-layer design strategy based on a joint
successive interference cancellation (SIC) detection technique and a
multi-relay selection algorithm for the uplink of cooperative direct-sequence
code-division multiple access (DS-CDMA) systems. We devise a low-cost greedy
list-based SIC (GL-SIC) strategy with RAKE receivers as the front-end that can
approach the maximum likelihood detector performance. %Unlike prior art, the
proposed GL-SIC algorithm %exploits the Euclidean distance between users of
interest, multiple %ordering and their constellation points to build an
effective list %of detection candidates. We also present a low-complexity
multi-relay selection algorithm based on greedy techniques that can approach
the performance of an exhaustive search. %A cross-layer %design strategy that
brings together the proposed GL-SIC algorithm %and the greedy relay selection
is then developed. Simulations show an excellent bit error rate performance of
the proposed detection and relay selection algorithms as compared to existing
techniques.Comment: 5 figures, conferenc
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 Opportunistic Cooperation Techniques using Jamming and Relays for Physical-Layer Security in Buffer-aided Relay Networks
In this paper, we investigate opportunistic relay and jammer cooperation
schemes in multiple-input multiple-output (MIMO) buffer-aided relay networks.
The network consists of one source, an arbitrary number of relay nodes,
legitimate users and eavesdroppers, with the constraints of physical layer
security. We propose an algorithm to select a set of relay nodes to enhance the
legitimate users' transmission and another set of relay nodes to perform
jamming of the eavesdroppers. With Inter-Relay interference (IRI) taken into
account, interference cancellation can be implemented to assist the
transmission of the legitimate users. Secondly, IRI can also be used to further
increase the level of harm of the jamming signal to the eavesdroppers. By
exploiting the fact that the jamming signal can be stored at the relay nodes,
we also propose a hybrid algorithm to set a signal-to-interference and noise
ratio (SINR) threshold at the node to determine the type of signal stored at
the relay node. With this separation, the signals with high SINR are delivered
to the users as conventional relay systems and the low SINR performance signals
are stored as potential jamming signals. Simulation results show that the
proposed techniques obtain a significant improvement in secrecy rate over
previously reported algorithms.Comment: 8 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
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
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