Adaptive Iterative Decision Feedback Detection Algorithms for Multi-User MIMO Systems

An adaptive iterative decision multi-feedback detection algorithm with constellation constraints is proposed for multiuser multi-antenna systems. An enhanced detection and interference cancellation is performed by introducing multiple constellation points as decision candidates. A complexity reduction strategy is developed to avoid redundant processing with reliable decisions along with an adaptive recursive least squares algorithm for time-varying channels. An iterative detection and decoding scheme is also considered with the proposed detection algorithm. Simulations show that the proposed technique has a complexity as low as the conventional decision feedback detector while it obtains a performance close to the maximum likelihood detector.Comment: 5 figures, ICASSP 2012. arXiv admin note: text overlap with arXiv:1302.595

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

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

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

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

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

Low-Complexity Robust Adaptive Beamforming Algorithms Based on Shrinkage for Mismatch Estimation

In this paper, we propose low-complexity robust adaptive beamforming (RAB) techniques that based on shrinkage methods. The only prior knowledge required by the proposed algorithms are the angular sector in which the actual steering vector is located and the antenna array geometry. We firstly present a Low-Complexity Shrinkage-Based Mismatch Estimation (LOCSME) algorithm to estimate the desired signal steering vector mismatch, in which the interference-plus-noise covariance (INC) matrix is estimated with Oracle Approximating Shrinkage (OAS) method and the weights are computed with matrix inversions. We then develop low-cost stochastic gradient (SG) recursions to estimate the INC matrix and update the beamforming weights, resulting in the proposed LOCSME-SG algorithm. Simulation results show that both LOCSME and LOCSME-SG achieve very good output signal-to-interference-plus-noise ratio (SINR) compared to previously reported adaptive RAB algorithms.Comment: 8 pages, 2 figures, WSA. arXiv admin note: text overlap with arXiv:1311.233

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