Labeling Diversity for 2x2 WLAN Coded-Cooperative Networks

Labelling diversity is an efficient technique recently proposed in the literature and aims to improve the bit error rate(BER) performance of wireless local area network (WLAN) systems with two transmit and two receive antennas without increasing the transmit power and bandwidth requirements. In this paper, we employ labelling diversity with different space-time channel codes such as convolutional, turbo and low density parity check (LDPC) for both point-to-point and coded-cooperative communication scenarios. Joint iterative decoding schemes for distributed turbo and LDPC codes are also presented. BER performance bounds at an error floor (EF) region are derived and verified with the help of numerical simulations for both cooperative and non-cooperative schemes. Numerical simulations show that the coded-cooperative schemes with labelling diversity achieve better BER performances and use of labelling diversity at the source node significantly lowers relay outage probability and hence the overall BER performance of the coded-cooperative scheme is improved manifolds

EXIT charts for system design and analysis

Near-capacity performance may be achieved with the aid of iterative decoding, where extrinsic soft information is exchanged between the constituent decoders in order to improve the attainable system performance. Extrinsic information Transfer (EXIT) charts constitute a powerful semi-analytical tool used for analysing and designing iteratively decoded systems. In this tutorial, we commence by providing a rudimentary overview of the iterative decoding principle and the concept of soft information exchange. We then elaborate on the concept of EXIT charts using three iteratively decoded prototype systems as design examples. We conclude by illustrating further applications of EXIT charts, including near-capacity designs, the concept of irregular codes and the design of modulation schemes

Uncoded space-time labelling diversity : data rate & reliability enhancements and application to real-world satellite broadcasting.

Doctoral Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF

Artificial intelligence based design optimization for improving diversity in wireless links.

Masters Degree. University of KwaZulu-Natal, Durban.Abstract available in PDF

Turbo codes and turbo algorithms

In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding

Uncoded space-time labeling diversity with three transmit antennas: symbol mapping designs and error performance analysis.

Doctoral Degrees. University of KwaZulu-Natal, Durban.Abstract available in PDF.Publications on page iii

Bandwidth-efficient communication systems based on finite-length low density parity check codes

Low density parity check (LDPC) codes are linear block codes constructed by pseudo-random parity check matrices. These codes are powerful in terms of error performance and, especially, have low decoding complexity. While infinite-length LDPC codes approach the capacity of communication channels, finite-length LDPC codes also perform well, and simultaneously meet the delay requirement of many communication applications such as voice and backbone transmissions. Therefore, finite-length LDPC codes are attractive to employ in low-latency communication systems. This thesis mainly focuses on the bandwidth-efficient communication systems using finite-length LDPC codes. Such bandwidth-efficient systems are realized by mapping a group of LDPC coded bits to a symbol of a high-order signal constellation. Depending on the systems' infrastructure and knowledge of the channel state information (CSI), the signal constellations in different coded modulation systems can be two-dimensional multilevel/multiphase constellations or multi-dimensional space-time constellations. In the first part of the thesis, two basic bandwidth-efficient coded modulation systems, namely LDPC coded modulation and multilevel LDPC coded modulation, are investigated for both additive white Gaussian noise (AWGN) and frequency-flat Rayleigh fading channels. The bounds on the bit error rate (BER) performance are derived for these systems based on the maximum likelihood (ML) criterion. The derivation of these bounds relies on the union bounding and combinatoric techniques. In particular, for the LDPC coded modulation, the ML bound is computed from the Hamming distance spectrum of the LDPC code and the Euclidian distance profile of the two-dimensional constellation. For the multilevel LDPC coded modulation, the bound of each decoding stage is obtained for a generalized multilevel coded modulation, where more than one coded bit is considered for level. For both systems, the bounds are confirmed by the simulation results of ML decoding and/or the performance of the ordered-statistic decoding (OSD) and the sum-product decoding. It is demonstrated that these bounds can be efficiently used to evaluate the error performance and select appropriate parameters (such as the code rate, constellation and mapping) for the two communication systems.The second part of the thesis studies bandwidth-efficient LDPC coded systems that employ multiple transmit and multiple receive antennas, i.e., multiple-input multiple-output (MIMO) systems. Two scenarios of CSI availability considered are: (i) the CSI is unknown at both the transmitter and the receiver; (ii) the CSI is known at both the transmitter and the receiver. For the first scenario, LDPC coded unitary space-time modulation systems are most suitable and the ML performance bound is derived for these non-coherent systems. To derive the bound, the summation of chordal distances is obtained and used instead of the Euclidean distances. For the second case of CSI, adaptive LDPC coded MIMO modulation systems are studied, where three adaptive schemes with antenna beamforming and/or antenna selection are investigated and compared in terms of the bandwidth efficiency. For uncoded discrete-rate adaptive modulation, the computation of the bandwidth efficiency shows that the scheme with antenna selection at the transmitter and antenna combining at the receiver performs the best when the number of antennas is small. For adaptive LDPC coded MIMO modulation systems, an achievable threshold of the bandwidth efficiency is also computed from the ML bound of LDPC coded modulation derived in the first part

Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

Low-complexity iterative receivers for multiuser space-time block coding systems

Iterative processing has been shown to be very effective in multiuser space-time block coding (STBC) systems. The complexity and efficiency of an iterative receiver depend heavily on how the log-likelihood ratios (LLRs) of the coded bits are computed and exchanged at the receiver among its three major components, namely the multiuser detector, the maximum a posterior probability (MAP) demodulators and the MAP channel decoders. This thesis first presents a method to quantitatively measure the system complexities with floating-point operations (FLOPS) and a technique to evaluate the iterative receiver's convergence property based on mutual information and extrinsic information transfer (EXIT) charts.Then, an integrated iterative receiver is developed by applying the sigma mappings for M-ary quadrature amplitude modulation (M-QAM) constellations. Due to the linear relationship between the coded bits and the transmitted channel symbol, the multiuser detector can work on the bit-level and hence improves the convergence property of the iterative receiver. It is shown that the integrated iterative receiver is an attractive candidate to replace the conventional receiver when a few receive antennas and a high-order M-QAM constellation are employed. Finally, a more general two-loop iterative receiver is proposed by introducing an inner iteration loop between the MAP demodulators and the MAP convolutional decoders besides the outer iteration loop that involves the multiuser detection (MUD) as in the conventional iterative receiver. The proposed two-loop iterative receiver greatly improves the iteration efficiency. It is demonstrated that the proposed two-loop iterative receiver can achieve the same asymptotic performance as that of the conventional iterative receiver, but with much less outer-loop iterations