Full Diversity Space-Time Block Codes with Low-Complexity Partial Interference Cancellation Group Decoding

Partial interference cancellation (PIC) group decoding proposed by Guo and Xia is an attractive low-complexity alternative to the optimal processing for multiple-input multiple-output (MIMO) wireless communications. It can well deal with the tradeoff among rate, diversity and complexity of space-time block codes (STBC). In this paper, a systematic design of full-diversity STBC with low-complexity PIC group decoding is proposed. The proposed code design is featured as a group-orthogonal STBC by replacing every element of an Alamouti code matrix with an elementary matrix composed of multiple diagonal layers of coded symbols. With the PIC group decoding and a particular grouping scheme, the proposed STBC can achieve full diversity, a rate of $(2M)/(M+2)$ and a low-complexity decoding for $M$ transmit antennas. Simulation results show that the proposed codes can achieve the full diversity with PIC group decoding while requiring half decoding complexity of the existing codes.Comment: 10 pages, 3 figures

Index modulation for next generation wireless communications.

Doctoral Degree. University of KwaZulu-Natal, Durban.A multicarrier index modulation technique in the form of quadrature spatial modulation (QSM) orthogonal frequency division multiplexing (QSM-OFDM) is proposed, in which transmit antenna indices are employed to transmit additional bits. Monte Carlo simulation results demonstrates a 5 dB gain in signal-to-noise ratio (SNR) over other OFDM schemes. Furthermore, an analysis of the receiver computational complexity is presented. A low-complexity near-ML detector for space-time block coded (STBC) spatial modulation (STBC-SM) with cyclic structure (STBC-CSM), which demonstrate near-ML error performance and yields significant reduction in computational complexity is proposed. In addition, the union-bound theoretical framework to quantify the average bit-error probability (ABEP) of STBC-CSM is formulated and validates the Monte Carlo simulation results. The application of media-based modulation (MBM), to STBC-SM and STBC-CSM employing radio frequency (RF) mirrors, in the form of MBSTBC-SM and MBSTBC-CSM is proposed to improve the error performance. Numerical results of the proposed schemes demonstrate significant improvement in error performance when compared with STBC-CSM and STBC-SM. In addition, the analytical framework of the union-bound on the ABEP of MBSTBC-SM and MBSTBC-CSM for the ML detector is formulated and agrees well with Monte Carlo simulations. Furthermore, a low-complexity near-ML detector for MBSTBC-SM and MBSTBC-CSM is proposed, and achieves a near-ML error performance. Monte Carlo simulation results demonstrate a trade-off between the error performance and the resolution of the detector that is employed. Finally, the application of MBM, an index modulated system to spatial modulation, in the form of spatial MBM (SMBM) is investigated. SMBM employs RF mirrors located around the transmit antenna units to create distinct channel paths to the receiver. This thesis presents an easy to evaluate theoretical bound for the error performance of SMBM, which is validated by Monte Carlo simulation results. Lastly, two low-complexity suboptimal mirror activation pattern (MAP) optimization techniques are proposed, which improve the error performance of SMBM significantly

A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment

The application of multiple-input multiple-output (MIMO) techniques to non-orthogonal multiple access (NOMA) systems is important to enhance the performance gains of NOMA. In this paper, a novel MIMO-NOMA framework for downlink and uplink transmission is proposed by applying the concept of signal alignment. By using stochastic geometry, closed-form analytical results are developed to facilitate the performance evaluation of the proposed framework for randomly deployed users and interferers. The impact of different power allocation strategies, such as fixed power allocation and cognitive radio inspired power allocation, on the performance of MIMO-NOMA is also investigated. Computer simulation results are provided to demonstrate the performance of the proposed framework and the accuracy of the developed analytical results

On the Achievable Error Region of Physical Layer Authentication Techniques over Rayleigh Fading Channels

For a physical layer message authentication procedure based on the comparison of channel estimates obtained from the received messages, we focus on an outer bound on the type I/II error probability region. Channel estimates are modelled as multivariate Gaussian vectors, and we assume that the attacker has only some side information on the channel estimate, which he does not know directly. We derive the attacking strategy that provides the tightest bound on the error region, given the statistics of the side information. This turns out to be a zero mean, circularly symmetric Gaussian density whose correlation matrices may be obtained by solving a constrained optimization problem. We propose an iterative algorithm for its solution: Starting from the closed form solution of a relaxed problem, we obtain, by projection, an initial feasible solution; then, by an iterative procedure, we look for the fixed point solution of the problem. Numerical results show that for cases of interest the iterative approach converges, and perturbation analysis shows that the found solution is a local minimum

MIMO Radar Target Localization and Performance Evaluation under SIRP Clutter

Multiple-input multiple-output (MIMO) radar has become a thriving subject of research during the past decades. In the MIMO radar context, it is sometimes more accurate to model the radar clutter as a non-Gaussian process, more specifically, by using the spherically invariant random process (SIRP) model. In this paper, we focus on the estimation and performance analysis of the angular spacing between two targets for the MIMO radar under the SIRP clutter. First, we propose an iterative maximum likelihood as well as an iterative maximum a posteriori estimator, for the target's spacing parameter estimation in the SIRP clutter context. Then we derive and compare various Cram\'er-Rao-like bounds (CRLBs) for performance assessment. Finally, we address the problem of target resolvability by using the concept of angular resolution limit (ARL), and derive an analytical, closed-form expression of the ARL based on Smith's criterion, between two closely spaced targets in a MIMO radar context under SIRP clutter. For this aim we also obtain the non-matrix, closed-form expressions for each of the CRLBs. Finally, we provide numerical simulations to assess the performance of the proposed algorithms, the validity of the derived ARL expression, and to reveal the ARL's insightful properties.Comment: 34 pages, 12 figure