1,079 research outputs found
Multi-Feedback Successive Interference Cancellation for Multiuser MIMO Systems
In this paper, a low-complexity multiple feedback successive interference
cancellation (MF-SIC) strategy is proposed for the uplink of multiuser
multiple-input multiple-output (MU-MIMO) systems. In the proposed MF-SIC
{algorithm with shadow area constraints (SAC)}, an enhanced interference
cancellation is achieved by introducing {constellation points as the
candidates} to combat the error propagation in decision feedback loops. We also
combine the MF-SIC with multi-branch (MB) processing, which achieves a higher
detection diversity order. For coded systems, a low-complexity soft-input
soft-output (SISO) iterative (turbo) detector is proposed based on the MF and
the MB-MF interference suppression techniques. The computational complexity of
the MF-SIC is {comparable to} the conventional SIC algorithm {since very little
additional complexity is required}. {Simulation} results show that the
algorithms significantly outperform the conventional SIC scheme and {approach}
the optimal detector.Comment: 6 figure
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
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
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
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
Multi-Branch Lattice-Reduction SIC for Multiuser MIMO Systems
In this paper, we propose a new detection technique for multiuser
multiple-input multiple-output (MU-MIMO) systems. The proposed scheme combines
a lattice reduction (LR) transformation, which makes the channel matrix nearly
orthogonal, and then employs a multi-branch (MB) technique with successive
interference cancellation (SIC). A single LR transformation is required for the
receive filters of all branches in the scheme, which proposes a different
ordering for each branch and generates a list of detection candidates. The best
vector of estimated symbols is chosen according to the maximum likelihood (ML)
selection criterion. Simulation results show that the proposed detection
structure has a near-optimal performance while the computational complexity is
much lower than that of the ML detector.Comment: 7 figures, ISWCS 201
Adaptive Decision Feedback Detection with Parallel Interference Cancellation and Constellation Constraints for Multi-Antenna Systems
In this paper, a novel low-complexity adaptive decision feedback detection
with parallel decision feedback and constellation constraints (P-DFCC) is
proposed for multiuser MIMO systems. We propose a constrained constellation map
which introduces a number of selected points served as the feedback candidates
for interference cancellation. By introducing a reliability checking, a higher
degree of freedom is introduced to refine the unreliable estimates. The P-DFCC
is followed by an adaptive receive filter to estimate the transmitted symbol.
In order to reduce the complexity of computing the filters with time-varying
MIMO channels, an adaptive recursive least squares (RLS) algorithm is employed
in the proposed P-DFCC scheme. An iterative detection and decoding (Turbo)
scheme is considered with the proposed P-DFCC algorithm. Simulations show that
the proposed technique has a complexity comparable to the conventional parallel
decision feedback detector while it obtains a performance close to the maximum
likelihood detector at a low to medium SNR range.Comment: 10 figure
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
Distributed Iterative Detection Based on Reduced Message Passing for Networked MIMO Cellular Systems
This paper considers base station cooperation (BSC) strategies for the uplink
of a multi-user multi-cell high frequency reuse scenario where distributed
iterative detection (DID) schemes with soft/hard interference cancellation
algorithms are studied. The conventional distributed detection scheme exchanges
{soft symbol estimates} with all cooperating BSs. Since a large amount of
information needs to be shared via the backhaul, the exchange of hard bit
information is preferred, however a performance degradation is experienced. In
this paper, we consider a reduced message passing (RMP) technique in which each
BS generates a detection list with the probabilities for the desired symbol
that are sorted according to the calculated probability. The network then
selects the best {detection candidates} from the lists and conveys the index of
the constellation symbols (instead of double-precision values) among the
cooperating cells. The proposed DID-RMP achieves an inter-cell-interference
(ICI) suppression with low backhaul traffic overhead compared with {the
conventional soft bit exchange} and outperforms the previously reported
hard/soft information exchange algorithms.Comment: 9 pages, 6 figures. IEEE Transactions on Vehicular Technology, 201
Adaptive Decision Feedback Reduced-Rank Equalization Based on Joint Iterative Optimization of Adaptive Estimation Algorithms for Multi-Antenna Systems
This paper presents a novel adaptive reduced-rank multi-input-multi-output
(MIMO) decision feedback equalization structure based on joint iterative
optimization of adaptive estimators. The novel reduced-rank equalization
structure consists of a joint iterative optimization of two equalization
stages, namely, a projection matrix that performs dimensionality reduction and
a reduced-rank estimator that retrieves the desired transmitted symbol. The
proposed reduced-rank structure is followed by a decision feedback scheme that
is responsible for cancelling the inter-antenna interference caused by the
associated data streams. We describe least squares (LS) expressions for the
design of the projection matrix and the reduced-rank estimator along with
computationally efficient recursive least squares (RLS) adaptive estimation
algorithms. Simulations for a MIMO equalization application show that the
proposed scheme outperforms the state-of-the-art reduced-rank and the
conventional estimation algorithms at about the same complexity.Comment: 6 figures. arXiv admin note: substantial text overlap with
arXiv:1301.269
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