 This thesis is devoted to the development of timing recovery techniques for digital recording systems. The thesis begins with a detailed review and discussion of timing recovery structures, requirements, performance measures, timing error detector (TED) algorithms, and timing acquisition issues. The main contributions include five parts. The first part examines the timing sensitivity of read channel detectors, and develops a new analytical approach for evaluating the performance under static and random timing errors. The second part examines the TED efficiencies, develops an improved TED for jitter minimization, and studies optimality issues for timing acquisition. The third part investigates false lock and hang up problems, and develops two novel acquisition techniques. The fourth part presents the timing recovery loop design and implementation for an experimental read channel detector. The fifth part develops a new asynchronous equalizer adaptation structure with fully digital interpolative timing recovery (ITR) for digital optical recording systems.

 Abstract— The CRC or cyclic redundancy check is a widely used technique for error checking in many protocols used in data transmission. The main aim of this project is to design the CRC RTL generator or a tool that calculates the CRC equations for the given CRC polynomials and generates the Verilog RTL code .This block deals with the calculation of equations for standard polynomials like CRC-8, CRC-16, CRC-4, CRC-32 and CRC-64, CRC-32 and also user defined proprietary polynomial. Use PERL as the platform it also aims at having a simpler user interface and generate the RTLs for any data width and for any standard polynomial or user defined polynomial, and this design aims to be complete generic. RTLs generated by this tool are verified by System Verilog constrained random testing to make it more robust and reliable.

あらまし センサネットワークでは,多くのセンサノードが密集して配置されることが多く,観測により各セ ンサノードで得られるデータの間には相関がある.このような観測データがフュージョンセンターで収集される ことになる.本論文では,フュージョンセンターでの観測精度について Kullback-Leibler (KL) 情報量の観点か ら検討を行う.特に,KL 情報量すなわち観測精度を劣化させる要因として,各センサノードから無線通信路を 経て伝送される際に生じる伝送路誤りを取り上げ,その影響と低減手法について検討していく.本論文では,観 測データ間の相関がすべて等しい場合,及び,相関が一様ランダムとなる場合における,伝送路誤りがあると きのフュージョンセンターで得られる KL 情報量について検討を行う.フュージョンセンターにおいて,誤った データの推定に観測データの相関を利用することで KL 情報量の劣化を低減できることを示す.また,相関を利 用する上でのフュージョンセンターにおける観測データ間の相関の推定と,相関を利用した誤りデータの推定に ついての一例を示す. キーワード センサネットワーク,相関,Kullback-Leibler 情報量

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.

— We present methods to compute confidence intervals for the codeword error rate (CWER) and bit error rate (BER) of a coded communications link. We review several methods to compute exact and approximate confidence intervals for the CWER, and specifically consider the situation in which the true CWER is so low that only a handful, if any, codeword errors are able to be simulated. In doing so, we answer the question of how long an error-free simulation must be run in order to certify that a given CWER requirement is met with a given level of confidence, and discuss the bias introduced by aborting a simulation after observing the first codeword error. Next, we turn to the lesser studied problem of determining confidence intervals for the BER of coded systems. Since bit errors in systems that use coding or higher-order modulation do not occur independently, blind application of a method that assumes independence leads to inappropriately narrow confidence intervals. We present a new method to compute the confidence interval properly, using the first and second sample moments of the number of bit errors per codeword. This is the first method we know of to compute a confidence interval for the BER of a coded or higher-order modulation system.

–Generalized low-density parity-check (GLDPC) codes, where single parity-check (SPC) constraint nodes are replaced with generalized constraint (GC) nodes, are a promising class of codes for low latency communication. In this paper, a practical construction of quasi-cyclic (QC) GLDPC codes is proposed, where the proportion of generalized constraints is determined by an asymptotic analysis. We analyze the message passing process and complexity of a GLDPC code over the additive white gaussian noise (AWGN) channel and present a constraint-to-variable update rule based on the specific codewords of the component code. The block error rate (BLER) performance of the GLDPC codes, combined with a complementary outer code, is shown to outperform a variety of state-of-the-art code and decoder designs with suitable lengths and rates for the 5G Ultra Reliable Communication (URC) regime over an additive white gaussian noise (AWGN) channel with quadrature PSK (QPSK) modulation.

­—In this paper a robust, spatial domain watermarking scheme using simple error control coding technique is proposed. The idea of this scheme is to embed an encoded watermark using (5,1) repetition code inside the cover image pixels by LSB (Least Significant Bit) embedding technique. The proposed algorithm is simple, more robust against Salt and Pepper Noise than LSB only watermarking techniques. In this paper comparison is made between embedding different watermark encoding schemes such as (7, 4) Hamming code, (3, 1) repetition code, (5,1) repetition code and without encoding for different noise density of salt and pepper noise. Result shows watermark encoding scheme using (5,1) repetition code provides better robustness towards random error compared to other said scheme, without much degradation in cover image.

|In this work we studied the performance of the hybrid type-II Automatic Repeat reQuest (ARQ) system on Rayleigh fading channels. This system is based on High Rate Optimized Rate Compatible Punctured Convolutional (HRO-RCPC) codes combined with simple repetition codes. The performance is investigated for di erent packet sizes and constraint lengths of the convolutional encoder. Additionally the e ect of packet size on the performance in di erent fading environments is studied in more detail. We have also studied the performance of the HRO-RCPC codes combined with optimized Rate Compatible Repetition Convolutional (RCRC) codes as another alternative for channel coding in hybrid type-II ARQ schemes. The simulation results show that HRO-RCPC codes combined with optimized RCRC codes with high parent code rate perform almost as good as the HRO-RCPC codes with simple repetition codes at lower parent code rate. Also a tailbiting decoder using Circular Viterbi Algorithm (CVA) is examined for di erent hybrid type-II ARQ schemes and packet sizes. It is shown that the improvement of the performance due to tailbiting is noticeable for only short packets. For long packets, the sub-optimality of CVA decoding compared to the General Viterbi Algorithm (GVA) degrades the performance considerably. Keywords|Rayleigh fading channels, BPSK modulation, Rate compatible convolutional codes, hybrid type-II ARQ, tailbiting decoder.

|In this paper we present a way to regard the combined face detection and facial feature extraction problem as an optimization problem. This problem is of too high computational complexity to be of practical use, and we investigate diierent methods to reduce the complexity. Our proposed system uses techniques known from the literature (skin colour classifca-tion, statistical pattern matching, ...) as well as a novel method based on a deformable graph and an extended Viterbi algorithm.

{ To support multimedia applications, future PCS networks will likely involve an advanced interconnected wireless and wireline network. This paper focuses on how a PCS network can compensate for and mitigate the eeects of wireless channel errors. An error control architecture for wireless ATM that utilizes interleaving in the physical layer, forward error correction (FEC) code in the wireless ATM adaptation layer (AAL), and Selective Repeat automatic repeat request (ARQ) in the network layer is proposed. Moreover the FEC scheme in the AAL not only provides header error correction, but also includes error protection for the payload, which is a strong distinction from the traditional ATM implementation to combat channel error.

xxiii 1 Work Context 1 1.1 Definitions and system model . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Overview and contribution of thesis . . . . . . . . . . . . . . . . . . . . 9 2 Information Theory and State of the Art 13 2.1 Information theory viewpoint . . . . . . . . . . . . . . . . . . . . . . . 14 2.1.1 Capacity of the noiseless K-user adder channel . . . . . . . . . . 14 2.1.2 Capacity of the Gaussian multiple access channel . . . . . . . . 14 2.1.3 Capacity of known systems . . . . . . . . . . . . . . . . . . . . . 16 2.1.4 Capacity of multi-antenna system . . . . . . . . . . . . . . . . . 19 2.2 State of the art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2.1 Multi-user detection . . . . . . . . . . . . . . . . . . . . . . . . 22 2.2.2 Multi-user coding . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.2.3 Multi-antenna and space-time codes . . . . . . . . . . . . . . . . 23 3 Joint Multi-user Decoding 25 3.1 Uncoded two users . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.1.1 The Gaussian channel . . . . . . . . . . . . . . . . . . . . . . . 26 3.1.2 The Rayleigh fading channel . . . . . . . . . . . . . . . . . . . . 27 3.2 Convolutional coded systems . . . . . . . . . . . . . . . . . . . . . . . . 30

xxi measures. Comparison is made with the equivalent ML decoding schemes using both equal and unequal error protection. The performance of the MAP schemes show that the use of source redundancy gives significant gains, corresponding to the amount of residual redundancy present. In addition to the issue of robustness, a continuous modulation technique termed Analogue Phase Modulation (APM) is presented. Exploration into the possibilities of APM, in comparison to digital modulation and capacity bounds is performed. Both ML and MAP decoding of the APM schemes are examined.

xx 1 INTRODUÇÃO 1 1.1 Motivação e objetivo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Trabalhos relacionados . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3 Estrutura da dissertação . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2 REVISÃO DE CONCEITOS 10 2.1 Introdução . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2 Sistemas multiportadoras . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 ii 2.3 O sistema OFDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3.1 Discretização . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.2 Intervalo de guarda . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.3.3 Sincronismo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.4 O canal de transmissão . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.4.1 Modelagem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.5 Considerações finais . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3 O SISTEMA ISDB-T 26 3.1 Introdução . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.2 Remultiplexador . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.3 Codificação externa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.4 Dispersor de energia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.5 Ajuste de atrasos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.6 Codificador interno . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.7 Mapeadores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.7.1 Detecção coerente e não-coerente . . . . . . . . . . . . . . . . . . . 36 3.8 Estratégias de decisão dos demoduladores . . . . . . . . . . . . . . . . . . 38 3.9 O quadro OFDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.9.1 Modos de operação . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.9.2 Estrutura do quadro OFDM . . . . . . . . . . . . . . . . . . . . . . 40 3.9.3 Divisão hierárquica . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.9.4 Sinais pilotos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 iii 3.10 Entrelaçadores . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.10.1 Bloco de entrelaçamento de byte . . . . . . . . . . . . . . . . . . . 46 3.10.2 Bloco de entrelaçamento de bit . . . . . . . . . . . . . . . . . . . . 47 3.10.3 Bloco de entrelaçamento no tempo . . . . . . . . . . . . . . . . . . 48 3.10.4 Bloco de entrelaçamento na frequência . . . . . . . . . . . . . . . . 49 3.11 Considerações finais . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4 METODOLOGIA DO SIMULADOR 51 4.1 Introdução . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.2 Considerações feitas a respeito do ISDB-T . . . . . . . . . . . . . . . . . . 53 4.3 Fontes de dados para transmissão . . . . . . . . . . . . . . . . . . . . . . . 54 4.3.1 Dados gerados pelo simulador . . . . . . . . . . . . . . . . . . . . . 55 4.3.2 Dados de arquivos externos . . . . . . . . . . . . . . . . . . . . . . 57 4.4 Estrutura do simulador . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 4.5 Modelos de canais utilizados . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.6 Estimação de canal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.7 Considerações finais . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 5 RESULTADOS 77 5.1 Introdução . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5.2 Validação . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 5.3 Bloco de estimação de canal . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.4 Curvas de desempenho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 5.5 Resultados complementares . . . . . . . . . . . . . . . . . . . . . . . . . . 90 iv 5.5.1 Figura da distribuição de segmentos e intervalo de guarda . . . . . 91 5.5.2 Figura dos TSPs remultiplexados . . . . . . . . . . . . . . . . . . . 91 5.5.3 Imagens transmitidas . . . . . . . . . . . . . . . . . . . . . . . . . . 92 5.5.4 V́ıdeos das constelações . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.6 Considerações finais . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 6 O SOFTWARE CRIADO 95 6.1 Introdução . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 6.2 Estrutura geral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 6.3 O ISDB-T Analyser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 6.4 Vantagens e Desvantagens . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 6.5 Considerações finais . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

wireless, satellite, and space communication systems, reducing error is critical. High bit error rates of the wireless communication system require employing various coding methods on the data transferred. Channel coding for error detection and correction helps the communication system designers to reduce the effects of a noisy transmission channel. The purpose of this paper is to study and investigate the performance of Reed-Solomon code that is used to encode the data stream in digital communication. The performances were evaluated by applying to binary phase sift keying modulation scheme in symmetric Additive White Gaussian Noise channel. Reed-Solomon codes are best for correcting burst errors and find wide range of applications in digital communications and data storage. Keywords-Solomon codes (RS), Forward Error Correction (FEC), Additive White Gaussian Noise (AWGN), Binary Phase Shift Keying (BPSK).

viii List of Figures viii

vii

v

utterance plan physical optimised perception high-level low-level acoustic signal [speech judged cognitive rendering to be natural] processes processes internal perceptual external environmental trialling environmental factors within factors the speaker In the diagram we see that high-level cognitive processes provide an utterance plan for low-level rendering. Part of the rendering process involves perceptually trialling a hypothesised acoustic signal: this is done within the human speaker’s mind. Adjustments are made to rendering in an iterative fashion so that the final acoustic signal can be optimised for perception. The speaker, by pre-trialling the ‘sound’ has ensured that it is appropriate for perception. Or, the synthesiser has ensured that the signal will be judged natural (at least from this point of view).

the probability of an undetected error for these codes is presented. This method is then used to evaluate the error-detection performance of the shortened codes obtained from the two distance-4 Hamming codes adopted by CCITT X.25 for error control for packet-switched networks. We show that shortening a code does affect its error-detection performance.