This Master thesis is focused on detailed description of the DVB-T2 system. This work deals with the description of the particular parts of models and with typical RF transmission channels for fixed and mobile reception. In order to simulate the impact of the fading transmission channels on the transmitted signal there was developed an appropriate application in MATLAB. The graphic user interface of this application allows set the transmission parameters of DVB-T2 and the parameters of the transmission channels. Results of simulations with various settings are evaluated and compared with the results, obtained from the DVB-T measurements.

This thesis is focusing on the second satellite digital TV standard, DVB-S2. It deals with the principle of the digital TV and the first standard DVB-S. It also describes the very beginning and characteristics of the DVB-S2, new technologies in use, architecture and the individual topics are then explained more in detail. The thesis also contains the program of transmission simulation of DVB-S2 in MATLAB. In the laboratory of television technology UREL, two standards were measured and compared with the values obtained from the program. The functionality of the program and the benefits of DVB-S2 were verified afterwards.

Tato diplomová práce pojednává o zmírnění bitové chybovosti bezkabelového optického spoje s užitím principu reciprocity aplikovaného na komunikační kanál, spolu s možností kódování přenášených dat. V této práci je implementováno LDPC a Reed-Solomonovo kódování pro jejich vyhovující vlastnosti. Zbytková rámcová chybovost je vypočtena a k dispozici jako výstup systému, který je implementovaný v hradlovém poli (FPGA).

This thesis comprises of two parts. In the first, we improve the performance of existing hybrid FSO/RF communication systems. Conventional hybrid RF and optical wireless communication systems make use of independent and parallel Free Space Optical (FSO) and RF channels to achieve higher reliability than individual channels. This thesis is based on the idea that true hybridization can be accomplished only when both channels collaboratively compensate the shortcomings of each other and thereby, improve the performance of the system as a whole. We believe that optimization on the combined channel capacities instead of the individual channel capacities of the FSO and RF channels can increase the system availability by a large amount. Using analysis and simulation, we show that, by using Hybrid Channel Codes, we can obtain more than two orders of magnitude improvement in bit error rates and many-fold increase in system availability over the currently existing best systems. Simulations also show that the average throughput obtained using the new system is over 35% better when compared to the present systems. The goodput is much higher because of the elimination of data repetition. Also by avoiding data duplication, we preserve to a great extent the crucial security benefits of FSO communications. The second half of the thesis deals with magnetic recording systems. Due to the insatiable and ever-increasing needs of data storage, novel techniques have to be developed to improve the capacity of magnetic recording channels. These capacity requirements translate to improving storage densities and using higher recording rates. For these channels, improvements even in the order of a tenths of a dB have a big impact on the storage densities of the recording device. Recently, LDPC codes have been constructed to achieve the independent and uniformly distributed (i.u.d.) capacity of partial response (PR) channels. The “guess algorithm” has been proposed for memoryless channels, to improve the performance of iterative belief propagation decoding to that of Maximum Likelihood (ML) decoding. In the second part of this thesis, the “guess algorithm” is extended to channels with memory. It is shown using asymptotic density evolution analysis that the gains obtained using this algorithm on these channels are more than those obtained over memoryless channels. The “guess algorithm” is further extended to magnetic recording channels which are characterized by ISI and additive white gaussian noise (AWGN). Simulations show that gains of upto one dB are possible on magnetic recording channels.

A new computing platform, the General Purpose Reprsentation and Association Machine is studied and simulated. GPRAM machines use vague measurements to do a quick and rough assessment on a task; then use approximated message-passing algorithms to improve assessment; and finally selects ways closer to a solution, eventually solving it. We illustrate concepts and structures using simple examples.

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.

Broadcast spectrum restrictions require greater efficiency from wireless transmission systems, particularly in applications where sections of spectrum previously reserved for military purposes have been sold to private interests. A joint source-channel coding system, in tandem with smart data selection techniques, is proposed as a potential solution to this problem. The workings of this joint source-channel coding system are detailed, with particular attention given to the decoding process.

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<p>Free-space optical (FSO) communication has witnessed rapid development recently in response to ever-increasing demands for greater bandwidth. FSO links provide fiberspeed with the flexibility of wireless. Commercially available systems offer transmission speeds up to 2.5 Gbps, 5 Gbps and 10 Gbps, and demonstration systems report data rates as high as 160 Gbps. Its advantages also include license free operation, high immunity to interference, and ease of deployment. However, FSO systems are sensitive to adverse weather conditions such as fog, rain and snow.</p> <p>In order to improve the availability of FSO channels degraded by atmospheric turbulence and varying weather conditions, the effects of channel gain variations must be compensated. In this thesis, two rate-adaptive techniques, punctured low-density parity-check (LDPC) codes and Raptor codes, are studied using experimental data measured over a1.87 km terrestrial FSO link.</p> <p>Rate-adaptive performances with punctured LDPC codes and Raptor codes are evaluated in terms of outage probability and throughput. In comparison to uncoded system, rate-adaptive systems with both techniques demonstrate significant improvement of throughput and mitigation of outage probability especially in rainy weather. Due to its flexible rate-adaptation and simple hardware implementation, Raptor coded systems are judged more applicable to be implemented in field-programmable gate array (FPGA) based hardware. A dedicated decoding structure is proposed and tested, showing remarkable improvement in resource efficiency as compared to traditional Gauss-Jordan (GJ) decoding structures.</p> / Master of Applied Science (MASc)