In this thesis, the low-power design of two popular error-control code decoders has been presented. It first proposes a low-power Viterbi decoder based on the improved reference path generation method which can lead to significant reduction of the memory accesses during the trace-back operation of the survival memory unit. The use of the reference path has been addressed in the past; this mechanism is further extended in this thesis to take into account the selection of starting states for the trace-back and path prediction operations. Our simulation results show that the best saving ratio of memory access can be up to 92% by choosing the state with the minimum state-metric for both trace-back and path prediction. However, the implementation of our look-ahead path prediction initiated from the minimum state will suffer a lot of area overhead especially for Viterbi applications with large state number. Therefore, this thesis instead realizes a 64-state Viterbi decoder whose path prediction starts from the predicted state obtained from the previous prediction phase. Our implementation results show that the actual power reduction ratio ranges from 31% to 47% for various signal-to-noise ratio settings while the area overhead is about 10%. The second major contribution of this thesis is to apply the similar low-power technique to the design of Soft-Output-Viterbi-Algorithm (SOVA) based Turbo code decoders. Our experimental results show that for eight-state SOVA Turbo code, our reference path generation mechanism can reduce more that 95% memory accesses, which can help saving the overall power consumption by 15.6% with a slight area overhead of 3%.

Recent information theoretical results indicate that dirty-paper coding (DPC) achieves the entire capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This thesis presents practical code designs for Gaussian BCs based on DPC. To simplify our designs, we assume constraints on the individual rates for each user instead of the customary constraint on transmitter power. The objective therefore is to minimize the transmitter power such that the practical decoders of all users are able to operate at the given rate constraints. The enabling element of our code designs is a practical DPC scheme based on nested turbo codes. We start with Cover's simplest two-user Gaussian BC as a toy example and present a code design that operates 1.44 dB away from the capacity region boundary at the transmission rate of 1 bit per sample per dimension for each user. Then we consider the case of the multiple-input multiple-output BC and develop a practical limit-approaching code design under the assumption that the channel state information is available perfectly at the receivers as well as at the transmitter. The optimal precoding strategy in this case can be derived by invoking duality between the MIMO BC and MIMO multiple access channel (MAC). However, this approach requires transformation of the optimal MAC covariances to their corresponding counterparts in the BC domain. To avoid these computationally complex transformations, we derive a closed-form expression for the optimal precoding matrix for the two-user case and use it to determine the optimal precoding strategy. For more than two users we propose a low-complexity suboptimal strategy, which, for three transmit antennas at the base station and three users (each with a single receive antenna), performs only 0.2 dB worse than the optimal scheme. Our obtained results are only 1.5 dB away from the capacity limit. Moreover simulations indicate that our practical DPC based scheme significantly outperforms the prevalent suboptimal strategies such as time division multiplexing and zero forcing beamforming. The drawback of DPC based designs is the requirement of channel state information at the transmitter. However, if the channel state information can be communicated back to the transmitter effectively, DPC does indeed have a promising future in code designs for MIMO BCs.

In this thesis, we discuss the implementation of a low latency decoding algorithm for turbo codes and repeat accumulate codes and compare the implementation results in terms of maximum available clock speed, resource consumption, error correction performance, and the data (information bit) rate. In order to decrease the latency a parallelized decoder structure is introduced for these mentioned codes and the results are obtained by implementing the decoders on a field programmable gate array. The memory collision problem is avoided by using collision-free interleavers. Through a proposed quantization scheme and normalization approximations, computational issues are handled for overcoming the overflow and underflow issues in a fixed point arithmetic. Also, the effect of different implementation styles are observed.

In this thesis, we study the performance of an antenna switching (AS) system in comparison to an Alamouti coded system. We analyze the outage probabilities and propose minimum mean-squared error based iterative equalizers for both systems. We see from the outage probability analysis of both systems that the AS system may achieve the same diversity order of the Alamouti coded scheme contingent on the transmission rate and constellation size. In the proposed receiver, MMSE equalization and channel decoding are jointly carried out in an iterative fashion. We use both hard and soft decision channel decoders in our simulations. It is observed that the Alamouti based scheme performs better when the channel state information is perfect. The Alamouti scheme also performs better than the AS scheme when the channel state information is imperfect in hard decision channel decoder case and a random interleaver is used. On the other hand, if a random interleaver is not used, AS scheme performs remarkably better than the Alamouti scheme in hard decision channel decoder case. In a soft decision channel decoder case, when the channel state information is imperfect, the AS scheme performs approximately a 2 dB better than the Alamouti scheme. Moreover, there is approximately a 3 dB performance gain if a soft decision channel decoder is used instead of hard decision.

In recent years, extensive studies on alternative fuels have been conducted to find environmentally friendly, economically feasible fuels due to finite petroleum sources, environmental and economical reasons. In this thesis, effects of alternative fuels on engine performance and exhaust emission are studied experimentally. Cold and reacting tests have been performed. Volumetric flow rate, discharge pressure are measured according to different pump speed. Droplet diameters, droplet distribution, spray cone angle and two dimensional velocity distribution from combustor fuel nozzle are determined by IPI and PIV technique. The comparative performance of alternative fuels and JET A-1 are investigated by atmospheric combustion tests and experimental turbojet tests in terms of exhaust gas temperatures, emissions, combustion chamber efficiency. Emissions, combustion chamber exit temperature profile, power turbine inlet and exhaust gas temperatures, effects of fuels on engine performance are observed and measured in detail at RR Allison 250 C-18 turbo-shaft engine.

No description available.

Dans ce travail, nous nous intéressons au problème du codage canal, dont le but est de corriger les erreurs dûes au canal lors d'une transmission numérique. En particulier, les turbo codes constituent la dernière avancée dans ce domaine et atteignent la borne prédite par C.E. Shannon en 1948. Nous présentons une simplification de la mise en oeuvre du turbo décodeur de R. Pyndiah, ainsi que des systèmes de synchronisation profitant des informations apportées par le turbo décodeur.

Solutions to the problem of large peak to average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems are proposed. Although the design of PAPR reduction codewords has been extensively studied and the existence of asymptotically good codes with low PAPR has been proved, still no reduced PAPR capacity achieving code has been constructed. This is the topic of the current thesis.This goal is achieved by implementing a time-frequency turbo block coded OFDM. In this scheme, we design the frequency domain component code to have a PAPR bounded by a small number. The time domain component code is designed to obtain good performance while the decoding algorithm has reasonable complexity. Through comparative numerical evaluation we show that our method achieves considerable improvement in terms of PAPR with slight performance degradation compared to capacity achieving codes with similar block lengths. For the frequency domain component code, we used the realization of Golay sequences as cosets of the fi rst order Reed-Muller code and the modi cation of dual BCH code. A simple MAP decoding algorithm for the modi ed dual BCH code is also provided. Finally, we provide a flexible and practical scheme based on probabilistic approach to a PAPR problem. This approach decreases the PAPR without any signi cant performance loss and without any adverse impact or required change to the system. / Engineering and Applied Sciences

The ever-increasing demands for transmission capacity are the cause for the quick evolution of optical communication systems. Channel transmission at 100 Gb/s is already being considered by network operators. The major transmission impairments at these high rates are intra-channel and inter-channel nonlinearities, nonlinear phase noise, and polarization mode dispersion. By implementing LDPC-coded modulation schemes with soft decoding and Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm for equalization we have demonstrated significant improvements in system performance experiencing several impairments simultaneously. The new turbo-equalization scheme is used as a mean to simultaneously mitigate both linear and nonlinear impairments. This approach is general and applicable to both direct and coherent detection.We provide comprehensive study of LDPC codes suitable for implementation in high-speed optical transmission systems. We determine channel capacity based on the forward step of the BCJR algorithm and show that by using LDPC codes we can closely approach the maximum transmission capacity that is possible. We propose the multilevel maximum a posteriori probability (MAP) turbo equalization scheme based on multilevel BCJR algorithm and an LDPC decoder, which considers independent symbols transmitted over both polarizations as two dimensional super-symbols. The use of multilevel modulation schemes provide higher spectral efficiency, while all related signal processing is performed at lower symbol rates, where dealing with PMD compensation and fiber nonlinearities mitigation is more manageable. We show significant improvement in system performance over a system employing an equalizer that considers symbols transmitted in different polarizations as independent.

The hard-disk storage industry is at a critical time as the current technologies are incapable of achieving densities beyond 500 Gb/in2, which will be reached in a few years. Many radically new storage architectures have been proposed, which along with advanced signal processing algorithms are expected to achieve much higher densities. In this dissertation, various signal processing algorithms are developed to improve the performance of current and next-generation magnetic storage systems.Low-density parity-check (LDPC) error correction codes are known to provide excellent performance in magnetic storage systems and are likely to replace or supplement currently used algebraic codes. Two methods are described to improve their performance in such systems. In the first method, the detector is modified to incorporate auxiliary LDPC parity checks. Using graph theoretical algorithms, a method to incorporate maximum number of such checks for a given complexity is provided. In the second method, a joint detection and decoding algorithm is developed that, unlike all other schemes, operates on the non-binary channel output symbols rather than input bits. Though sub-optimal, it is shown to provide the best known decoding performance for channels with memory more than 1, which are practically the most important.This dissertation also proposes a ternary magnetic recording system from a signal processing perspective. The advantage of this novel scheme is that it is capable of making magnetic transitions with two different but predetermined gradients. By developing optimal signal processing components like receivers, equalizers and detectors for this channel, the equivalence of this system to a two-track/two-head system is determined and its performance is analyzed. Consequently, it is shown that it is preferable to store information using this system, than to store using a binary system with inter-track interference. Finally, this dissertation provides a number of insights into the unique characteristics of heat-assisted magnetic recording (HAMR) and two-dimensional magnetic recording (TDMR) channels. For HAMR channels, the effects of laser spot on transition characteristics and non-linear transition shift are investigated. For TDMR channels, a suitable channel model is developed to investigate the two-dimensional nature of the noise.