Self-concatenated code design and its application in power-efficient cooperative communications

In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions

Multilevel Orthogonal Coded Modulation

Multilevel orthogonal coded modulation technique is a combination of orthogonal channel coding and M-ary modulation, where two or more codes are used simultaneously to detect and correct multiple errors with bandwidth efficiency. The concept, principles, and simulations of the multilevel orthogonal coding combined with M-ary modulations is presented in this thesis. In multilevel orthogonal coding, both information and orthogonal code blocks are split into multiple levels. The information data in each level are mapped to the corresponding orthogonal codes. The outputs of the encoders are then grouped to form symbols suitable for input to spectrally efficient multilevel modulations. The modulated symbols are then transmitted to the channel. At the receiver, the decoding is performed using the correlative decoder. The correlative decoding is also performed in multiple levels independently. At each level of decoding, the incoming orthogonal codes with errors are cross-correlated with the known set of orthogonal code blocks. Then the code set that gives the smallest correlation value, at each level, is chosen as the desired orthogonal code output. The implementing of multilevel encoding and decoding structure increases the error correcting capability of the system significantly, allowing multiple numbers of error corrections. Also, error correction capability of orthogonal codes improves with increasing the code lengths. Combining longer codes in multilevel structures the system shows better error performance. Additionally, the multilevel encoding outputs are suitable for performing multilevel modulation (M-ary modulation), which allows the transmissions of a large number of bits per symbol. This makes the systems to have minimum transmission bandwidths that increase the throughput. The encoding and decoding structures for three code rates: rate ݬ rate ެ and rate 1, for different orthogonal code lengths are presented and simulated. The transmission bandwidths, bandwidth efficiencies are calculated and error performance analyses of systems are conducted. M-ary Phase Shift Keying (PSK) and M-ary Quadrature Amplitude Modulation (QAM) modulation techniques are chosen as modulation techniques to simulate and analyze the performances in MATLAB. To show the application of MOCM, multilevel orthogonal coded M-ary PSK modulation transmitted in optical wireless communication systems using ambient light cancellation technology is also presented. To simulate the error performances, additive white Gaussian noise channel is used at various signal-to-noise ratios (SNR). The number of errors before decoding and after decoding is counted and tabulated. The number of bit error corrected at specified signal to noise ratio is also tabulated. Error performance curves are plotted and coding gains are observed. The results show the performance improvement of the systems compared to uncoded systems. Also, the coded systems are bandwidth efficient. Thus, the multilevel orthogonal coded modulation systems provide higher error correction capability with bandwidth efficiency

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

Advanced Coding And Modulation For Ultra-wideband And Impulsive Noises

The ever-growing demand for higher quality and faster multimedia content delivery over short distances in home environments drives the quest for higher data rates in wireless personal area networks (WPANs). One of the candidate IEEE 802.15.3a WPAN proposals support data rates up to 480 Mbps by using punctured convolutional codes with quadrature phase shift keying (QPSK) modulation for a multi-band orthogonal frequency-division multiplexing (MB-OFDM) system over ultra wideband (UWB) channels. In the first part of this dissertation, we combine more powerful near-Shannon-limit turbo codes with bandwidth efficient trellis coded modulation, i.e., turbo trellis coded modulation (TTCM), to further improve the data rates up to 1.2 Gbps. A modified iterative decoder for this TTCM coded MB-OFDM system is proposed and its bit error rate performance under various impulsive noises over both Gaussian and UWB channel is extensively investigated, especially in mismatched scenarios. A robust decoder which is immune to noise mismatch is provided based on comparison of impulsive noises in time domain and frequency domain. The accurate estimation of the dynamic noise model could be very difficult or impossible at the receiver, thus a significant performance degradation may occur due to noise mismatch. In the second part of this dissertation, we prove that the minimax decoder in \cite, which instead of minimizing the average bit error probability aims at minimizing the worst bit error probability, is optimal and robust to certain noise model with unknown prior probabilities in two and higher dimensions. Besides turbo codes, another kind of error correcting codes which approach the Shannon capacity is low-density parity-check (LDPC) codes. In the last part of this dissertation, we extend the density evolution method for sum-product decoding using mismatched noises. We will prove that as long as the true noise type and the estimated noise type used in the decoder are both binary-input memoryless output symmetric channels, the output from mismatched log-likelihood ratio (LLR) computation is also symmetric. We will show the Shannon capacity can be evaluated for mismatched LLR computation and it can be reduced if the mismatched LLR computation is not an one-to-one mapping function. We will derive the Shannon capacity, threshold and stable condition of LDPC codes for mismatched BIAWGN and BIL noise types. The results show that the noise variance estimation errors will not affect the Shannon capacity and stable condition, but the errors do reduce the threshold. The mismatch in noise type will only reduce Shannon capacity when LLR computation is based on BIL

Turbo space-time coded modulation : principle and performance analysis

A breakthrough in coding was achieved with the invention of turbo codes. Turbo codes approach Shannon capacity by displaying the properties of long random codes, yet allowing efficient decoding. Coding alone, however, cannot fully address the problem of multipath fading channel. Recent advances in information theory have revolutionized the traditional view of multipath channel as an impairment. New results show that high gains in capacity can be achieved through the use of multiple antennas at the transmitter and the receiver. To take advantage of these new results in information theory, it is necessary to devise methods that allow communication systems to operate close to the predicted capacity. One such method recently invented is space-time coding, which provides both coding gain and diversity advantage. In this dissertation, a new class of codes is proposed that extends the concept of turbo coding to include space-time encoders as constituent building blocks of turbo codes. The codes are referred to as turbo spacetime coded modulation (turbo-STCM). The motivation behind the turbo-STCM concept is to fuse the important properties of turbo and space-time codes into a unified design framework. A turbo-STCM encoder is proposed, which consists of two space-time codes in recursive systematic form concatenated in parallel. An iterative symbol-by-symbol maximum a posteriori algorithm operating in the log domain is developed for decoding turbo-STCM. The decoder employs two a posteriori probability (APP) computing modules concatenated in parallel; one module for each constituent code. The analysis of turbo-STCM is demonstrated through simulations and theoretical closed-form expressions. Simulation results are provided for 4-PSK and 8-PSK schemes over the Rayleigh block-fading channel. It is shown that the turbo-STCM scheme features full diversity and full coding rate. The significant gain can be obtained in performance over conventional space-time codes of similar complexity. The analytical union bound to the bit error probability is derived for turbo-STCM over the additive white Gaussian noise (AWGN) and the Rayleigh block-fading channels. The bound makes it possible to express the performance analysis of turbo-STCM in terms of the properties of the constituent space-time codes. The union bound is demonstrated for 4-PSK and 8-PSK turbo-STCM with two transmit antennas and one/two receive antennas. Information theoretic bounds such as Shannon capacity, cutoff rate, outage capacity and the Fano bound, are computed for multiantenna systems over the AWGN and fading channels. These bounds are subsequently used as benchmarks for demonstrating the performance of turbo-STCM

Improved timing recovery in wireless mobile receivers

The problem of timing recovery in wireless mobile receiver systems is critical. This is partly because timing recovery functions must follow rapid parameter changes inherent in mobile systems and partly because both bandwidth and power must be conserved in low signal to noise ratio communication channels. The ultimate goal is therefore to achieve a low bit error rate on the recovered information for improving QoS provisioning to terminal mobile users. Traditional timing recovery methods have over-relied on phase-locked loops for timing information adjustment. However, associated schemes do not exploit code properties. This leads to synchronization difficulties in digital receivers separated from transmitters by lossy channels. In this paper we present a soft timing phase estimation algorithm for wireless mobile receivers in low signal to noise ratios. In order to develop a bandwidth and power efficient timing recovery method for wireless mobile receivers, a raised cosine filter and a multilevel phase shift keying modulation scheme are implemented and no clock signals are transmitted to the receiver. In the proposed method, the receiver exploits the soft decisions computed at each turbo decoding iteration to provide reliable estimates of a soft timing signal, which in turn, improves the decoding time. The derived method, based on sequential minimization techniques, approaches the theoretical Cramer-Rao bound with unbiased estimates within a few iterations.Key Words: discrete polyphase matched filters, maximum likelihood estimators, iterative turbo receivers, log-MAP b