Multilevel Block Coded Modulation with Unequal Error Protection

Multilevel block coded modulation (BCM) schemes with unequal error protection (UEP) are investigated. These schemes are based on unconventional set partitions that greatly reduce the error coefficients associated with multi-stage decoding of conventional BCM, at the expense of smaller intra-set distances

A novel rate allocation method for multilevel coded modulation

We present a new rate allocation scheme for multilevel coded modulation based on the minimization of the total block error rate (BLER). The proposed method uses affine code components and hard decision multistage decoding. Exhaustive search for the rate allocation which minimizes the total BLER justifies the near-optimum performance of the introduced method in moderate to high SNRs. Compared to previous approaches this new rate allocation scheme can improve the performance of the system by 1 dB at BLER = 10 −6 for 16-QAM with Ungerboeck set partitioning. Interestingly, our results indicate that the optimum rate allocation is a function of the SNR. Finally, the performance of some specific codes are evaluated by simulation and union bounds to verify the theoretical results

Time-Splitting Multiple-Access

It is shown that the encoding/decoding problem for any asynchronous M-user memoryless multiple-access channel can be reduced to corresponding problems for at most 2M-1 single-user memoryless channels. This is done via a method called time-splitting multiple-access which is closely related to a recently developed method called rate-splitting multiple access. It is also related to multilevel coding. The practical interest for time-splitting multiple access is that it reduces the seemingly hard task of finding good multiple-access codes and implementable decoders for such codes to the much better understood task of finding codes and decoders for single-user channels. As a by-product, some interesting properties of the capacity region of M-user asynchronous discrete memoryless channels are derived

Optimal Signaling and Labelling For Constellation-Constrained Communication Systems

Most communication systems use a finite signal set as their alphabet set to form a codebook to transmit data over a communication channel in a reliable fashion. The problem with Conventional methods which implement Coded Modulation (CM) schemes such as Trellis Coded Modulation or Multi-level Coding Multi-Stage Decoding is their complexity of dealing with codes with different rates in each level which makes the design and implementation a difficult task. One simple way to implement Coded Modulation is Bit-Interleaved Coded Modulation (BICM) which uses only a single binary encoder to transmit data. Although BICM is a suboptimal scheme compared to CM, its simplicity, from a practical point of view, is a great motivation to design BICM scheme achieving rates close to those obtained by CM. Lots of efforts have been taken place in the past twenty years to design optimal constellation for different snr regimes in CM under various constraints. Some of them are revisited in this study. A novel approach, called Adjustable Weights Model (AWM), will be presented to design constellations which work very well in both CM and BICM schemes. The model also induces a particular labelling on the constellation. In this work, some properties of AWM are studied. AWM is used to facilitate design of near optimal signalling for CM and BICM schemes. An optimization problem is formed to find the optimal parameters of the proposed model. Global optimization methods are used to solve the optimization problems. It is shown that the optimal points are always on the boundary of the domain by using data processing inequality . Some suboptimal solutions are provided by moment and cumulants matching techniques. The model has the ability to produce different constellations by adjusting its weights. It is well established that the optimal constellation for high snr region is equillattice. This model also converges to an equillattice constellation in high snr region. Number of nonzero weight parameters in the model can vary according to snr, help us to circumvent the saturation problem with conventional CM scheme. BICM capacity is presented and its relation with CM capacity is discussed. BICM capacity, as a function of snr, is expanded around zero snr. Different constellations and their labeling can be characterized based on the coefficients in the Taylor expansion. The most important difference between CM and BICM is the effect of labelling in the former scheme. Labelling is irrelevant in CM, but greatly influences the system performance in BICM. Effect of labelling and how to search for optimal labeling is part of this study. It is shown that AWM is optimal at medium and low snr regimes. The model coupled with its underlying labelling is first order optimal. Although Gray labelling is optimal at high snr, it is not optimal in the low snr regime. Higher order optimal constellations are defined to be the constellations that have more than one coefficient in their Taylor expansion matched with CM capacity coefficients. It gives us a powerful tool to study constellation in medium snr regime which has not been already discovered. In addition, optimality criterion is provided

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

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Adaptive iterative decoding : block turbo codes and multilevel codes

New adaptive, iterative approaches to the decoding of block Turbo codes and multilevel codes are developed. Block Turbo codes are considered as they can readily provide high data rates, low decoding complexity and good performance. Multilevel codes are considered as they provide a moderate complexity approach to a high complexity code and can provide codes with good bandwidth efficiency. The work develops two adaptive sub-optimal soft output decoding algorithms for block Turbo codes. One is based on approximation and the other on the distance properties of the component codes. They can be used with different codes, modulation schemes, channel conditions and in different applications without modification. Both approaches provide improved performance compared to previous approaches on the additive white Gaussian noise (AWGN) channel. The approximation based adaptive algorithm is also investigated on the uncorrelated Rayleigh fiat fading channel and is shown to improve performance over previous approaches. Multilevel codes are typically decoded using a multistage decoder (MSD) for complexity reasons. Each level passes hard decisions to subsequent levels. If the approximation based adaptive algorithm is used to decode component codes in a traditional MSD it improves performance significantly. Performance can be improved further by passing reliability (extrinsic) information to all previous and subsequent levels using an iterative MSD. A new iterative multistage decoding algorithm for multilevel codes is developed by treating the extrinsic information as a Gaussian random variable. If the adaptive algorithms are used in conjunction with iterative multistage decoding on the AWGN channel, then a significant improvement in performance is obtained compared to results using a traditional MSD