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

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

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 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

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 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 Max-Link Relay Selection with Buffers for Multi-Way Cooperative Multi-Antenna Systems

In this paper, we present a relay-selection strategy for multi-way cooperative multi-antenna systems that are aided by a central processor node, where a cluster formed by two users is selected to simultaneously transmit to each other with the help of relays. In particular, we present a novel multi-way relay selection strategy based on the selection of the best link, exploiting the use of buffers and physical-layer network coding, that is called Multi-Way Buffer-Aided Max-Link (MW-Max-Link). We compare the proposed MW-Max-Link to existing techniques in terms of bit error rate, pairwise error probability, sum rate and computational complexity. Simulations are then employed to evaluate the performance of the proposed and existing techniques.Comment: 5 pages, 3 figure

Compression and Combining Based on Channel Shortening and Rank Reduction Techniques for Cooperative Wireless Sensor Networks

This paper investigates and compares the performance of wireless sensor networks where sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of $L$ sensors. As the destination has the capacity of processing only $U$ out of these $L$ signals, the strongest $U$ signals are selected while the remaining $(L-U)$ signals are suppressed. A preprocessing block similar to channel-shortening is proposed in this contribution. However, this preprocessing block employs a rank-reduction technique instead of channel-shortening. By employing this preprocessing, we are able to decrease the computational complexity of the system without affecting the bit error rate (BER) performance. From our simulations, it can be shown that these schemes outperform the channel-shortening schemes in terms of computational complexity. In addition, the proposed schemes have a superior BER performance as compared to channel-shortening schemes when sensors employ fixed gain amplification. However, for sensors which employ variable gain amplification, a tradeoff exists in terms of BER performance between the channel-shortening and these schemes. These schemes outperform channel-shortening scheme for lower signal-to-noise ratio.Comment: In IEEE Transactions on Vehicular Technology, 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

Adaptive Power Allocation Strategies using DSTC in Cooperative MIMO Networks

Adaptive Power Allocation (PA) algorithms with different criteria for a cooperative Multiple-Input Multiple-Output (MIMO) network equipped with Distributed Space-Time Coding (DSTC) are proposed and evaluated. Joint constrained optimization algorithms to determine the power allocation parameters, the channel parameters and the receive filter are proposed for each transmitted stream in each link. Linear receive filter and maximum-likelihood (ML) detection are considered with Amplify-and-Forward (AF) and Decode-and-Forward (DF) cooperation strategies. In the proposed algorithms, the elements in the PA matrices are optimized at the destination node and then transmitted back to the relay nodes via a feedback channel. The effects of the feedback errors are considered. Linear MMSE expressions and the PA matrices depend on each other and are updated iteratively. Stochastic gradient (SG) algorithms are developed with reduced computational complexity. Simulation results show that the proposed algorithms obtain significant performance gains as compared to existing power allocation schemes.Comment: 5 figures, 9 pages. IET Communications, 201