Channel Coding

Reducing the decoding latency of the turbo codes is important to real-time applications. Conventionally, the decoding of the turbo codes (TC) runs in serial fashion, which means only one of the constituent soft decoders runs at a time. Parallel decoding (PD) refers to running the soft decoders in parallel. Although it delivers the output faster (compared to the serial decoding (SD)), it affects the bit- and frame-error rates. This paper proposes a decoding procedure that combines both PD and SD. It bridges the two decoding modes to determine the best combination scheme to achieve the re quired level of performance at an acceptable decoding latency. Presented results show how this procedure can mitigate the performance degradation at a slight increase in the decoding latency.

Indoors wireless infrared transmission is severely impaired by ambient noise. In addition, in a multiple user network, since many users share the same physical channel, considerable amount of multi-user interference will also be introduced. In this paper, Infrared CDMA techniques are proposed to combat the effect of ambient and multi-user interference. Our analysis is based on Photon-Counting approach and Bit Error Rate is given versus signal power. The results show that using infrared CDMA techniques, transmission can be performed well below ambient noise power with transmission power that satisfies eye-safety power regulations.

In this paper, we study the performance of optical code-division multiple access (CDMA) systems using various receivers structures. Two general classes of receivers based on required electronic bandwidth are studied. Optical orthogonal codes (OOCs) are utilized as signature sequences and the performance studied in this paper takes into account the effect of all major noise sources, i.e., quantum shot-noise, dark current noise, and Gaussian circuit noise. Furthermore, this paper introduces a generalized method of analyzing the performance of various optical CDMA receiver structures. Required mean number of photon count per chip time for reliable transmission of data bits for various receiver structures is investigated. Finally, the advantages and disadvantages of various receiver structures are discussed.

In ], an ultra-wide bandwidth time-hopping spread-spectrum code division multiple-access system employing a binary PPM signaling has been introduced, and its performance was obtained based on a Gaussian distribution assumption for the multiple-access interference. In this paper, we begin first by proposing to use a practical low-rate error correcting code in the system without any further required bandwidth expansion. We then present a more precise performance analysis of the system for both coded and uncoded schemes. Our analysis shows that the Gaussian assumption is not accurate for predicting bit error rates at high data transmission rates for the uncoded scheme. Furthermore, it indicates that the proposed coded scheme outperforms the uncoded scheme significantly, or more importantly, at a given bit error rate, the coding scheme increases the number of users by a factor which is logarithmic in the number of pulses used in time-hopping spread-spectrum systems.

Facing the challenge of enormous data sets variety, several machine learning-based algorithms for prediction (e.g, Support vector machine, multi layer perceptron and logistic regression) have been highly proposed and used over the last years in many fields. Error correcting codes (ECCs) are extensively used in practice to protect data against damaged data storage systems and against random errors due to noise effects. In this paper, we will use machine learning methods, especially multi-class logistic regression combined with the famous syndrome decoding algorithm. The main idea behind our decoding method which we call logistic regression decoder (LRDec) is to use the efficient multi-class logistic regression models to find errors from syndromes in linear codes such as bose, ray-chaudhuri and hocquenghem (BCH), and the quadratic residue (QR). Obtained results of the proposed decoder have a significant benefit in terms of bit error rate (BER) for random binary codes. The comparison of our decoder with many competitors proves its power. The proposed decoder has reached a success percentage of 100% for correctable errors in the studied codes.

A systematic construction of capacity achieving lowdensity parity-check(LDPC) code ensemble sequences over the Binary Erasure Channel (BEC) has been proposed by Saeedi et al. based on a method, here referred to as Successive Maximization (SM). In SM, the fraction of degree-𝑖 nodes are successively maximized starting from 𝑖 = 2 with the constraint that the ensemble remains convergent over the channel. In this paper, we propose SM to design universally capacity approaching rate-compatible LDPC code ensemble sequences over the general class of Binary-Input Output-Symmetric Memoryless (BIOSM) channels. This is achieved by first generalizing the SM method to other BIOSM channels to design a sequence of capacity approaching ensembles called the parent sequence. The SM principle is then applied to each ensemble within the parent sequence, this time to design rate-compatible puncturing schemes. As part of our results, we extend the stability condition which was previously derived for degree-2 variable nodes to other variable node degrees as well as to the case of ratecompatible codes. Consequently, we prove that using the SM principle, one is able to design universally capacity achieving rate-compatible LDPC code ensemble sequences over the BEC. Unlike the previous results in the literature, the proposed SM approach is naturally extendable to other BIOSM channels. The performance of the rate-compatible schemes designed based on our method is comparable to those designed by optimization.

Digital Video Broadcasting-Terrestrial second generation (DVB-T2) systems are increasingly deployed for high quality terrestrial broadcasting. However, low Signal-to-Noise Ratio (SNR) conditions in urban and fringe coverage areas pose significant challenges, resulting in elevated Bit Error Rates (BER) and degraded service reliability. Forward Error Correction (FEC) techniques, particularly Low-Density Parity-Check (LDPC) and Bose Chaudhuri Hocquenghem (BCH) codes, play a crucial role in mitigating transmission errors and ensuring robust communication. This study investigates a systematic approach to optimizing LDPC and BCH FEC schemes to enhance transmission reliability and minimize BER under low-SNR conditions in DVB-T2 networks. Using simulation-based analyses, the study evaluates multiple LDPC code rates (e.g., 1/2, 2/3, 3/4) in combination with BCH codeword lengths and error-correcting capabilities. Results indicate that an optimized LDPC (64800, 32400) configuration combined with a BCH (255, 239) code significantly reduces BER, achieving approximately 10⁻⁵ at an SNR of 2 dB, compared to a BER of 10⁻³ using standard DVB-T2 FEC configurations. Additionally, iterative decoding algorithms for LDPC were fine-tuned to balance convergence speed and error correction performance, demonstrating a 25% reduction in decoding iterations without compromising reliability. The analysis also explores trade-offs between redundancy, throughput and latency, highlighting the practical considerations for real-world deployment. The findings underscore that strategic optimization of LDPC/BCH FEC parameters is critical for maintaining broadcast quality in low-SNR scenarios. By enhancing error resilience and reducing BER, the proposed approach improves signal integrity, supports consistent reception in fringe areas and maximizes spectrum efficiency. This work provides a foundation for adaptive FEC strategies in future DVB T2 systems, enabling broadcasters to deliver reliable high-definition content even under challenging channel conditions.

The rapid growth of High-Definition (HD) and Ultra-High-Definition (UHD) content, ranging from 2K to 10K resolutions, presents significant challenges for terrestrial broadcasting systems, particularly regarding spectrum utilization and reliable transmission. Digital Video Broadcasting-Terrestrial second generation (DVB-T2) with Multi-Physical Layer Pipes (M-PLP) offers a flexible framework to deliver heterogeneous content streams efficiently. This study investigates spectrum-aware adaptive transmission strategies to optimize multi-PLP DVB-T2 networks for high-resolution streaming, focusing on efficient multiplexing, error resilience and bandwidth management. Simulation analyses evaluate the performance of various multi-PLP configurations under different channel conditions, including low Signal to Noise Ratio (SNR) environments. Key metrics, such as throughput, Bit Error Rate (BER) and spectral efficiency, were assessed.

Code division multiple access (CDMA) suffers from intersymbol interference (ISI) and multi-user interference (MUI) in a frequency-selective multipath fading channel, but when properly designed, it enjoys multipath diversity. Orthogonal frequency division multiple access ...

The performance of data link layer (OSI Layer 2) protocols is critically affected by channel noise, electromagnetic interference (EMI), and propagation delay across diverse communication environments. This paper presents a rigorous mathematical framework for modeling and optimizing the throughput of Automatic Repeat reQuest (ARQ) protocols, namely Stop-and-Wait (SAW), Go-Back-N (GBN), and Selective Repeat (SR), operating over noisy channels. Analytical closed-form expressions for throughput efficiency η and effective goodput V are derived as functions of the Bit Error Rate (BER), frame size N , channel overhead C, transmission rate R, and normalized propagation delay a. We further develop an exact optimization condition and an approximate closedform solution for the optimal frame size Nopt ≈ √ C/p b that maximizes system goodput. The integration of Cyclic Redundancy Check (CRC) for error detection and convolutional coding with Viterbi decoding for Forward Error Correction (FEC) is incorporated into the performance model, yielding a unified cross-layer analysis. Numerical results are validated against simulation data and applied to high-EMI railway communication standards (GSM-R, TETRA, FRMCS), alongside constrained IoT networks (LPWAN) and ultra-high-speed Data Center Networks (DCNs). The results demonstrate that adaptive frame sizing and robust error control can increase goodput by up to 47% in high-EMI environments compared to fixed-size frame strategies.

Two extension tools for enhancing the compression performance of prediction-based lossless audio coding are proposed. One is progressive-order prediction of the starting samples at the random access points, where the information of previous samples is not available. The first sample is coded as is, the second is predicted by first-order prediction, the third is predicted by second-order prediction, and so on. This can be efficiently carried out with PAR-COR (PARtial autoCORrelation) coefficients. The second tool is inter-channel joint coding. Both predictive coefficients and prediction error signals are efficiently coded by inter-channel differential or three-tap adaptive prediction. These new prediction tools lead to a steady reduction in bit rate when random access is activated and the inter-channel correlation is strong.

In this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (STBC) MIMO systems. The proposed scheme employs a block transmission strategy where an N t × Nt pilot matrix is sent (for training purposes) followed by several N t × Nt square data STBC matrices, where N t is the number of transmit antennas. At the receiver, we iterate between channel estimation (using an MMSE estimator) and detection (using a low-complexity likelihood ascent search (LAS) detector) till convergence or for a fixed number of iterations. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. The fact that we could show such good results for large STBCs (e.g., 16×16 STBC from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.

In this paper, we study the achievable rate region of two-user Gaussian broadcast channel (GBC) when the messages to be transmitted to both the users take values from finite signal sets and the received signal is quantized at both the users. We refer to this channel as quantized broadcast channel (QBC). We first observe that the capacity region defined for a GBC does not carry over as such to QBC. Also, we show that the optimal decoding scheme for GBC (i.e., high SNR user doing successive decoding and low SNR user decoding its message alone) is not optimal for QBC. We then propose an achievable rate region for QBC based on two different schemes. We present achievable rate region results for the case of uniform quantization at the receivers. We find that rotation of one of the user's input alphabet with respect to the other user's alphabet marginally enlarges the achievable rate region of QBC when almost equal powers are allotted to both the users.

In this paper, we address the design of codes which achieve modulation diversity in block fading singleinput single-output (SISO) channels with signal quantization at the receiver. With an unquantized receiver, coding based on algebraic rotations is known to achieve maximum modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee gains in diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder and perfect channel knowledge. Relaxing the perfect channel knowledge assumption we propose a novel channel training/estimation technique to estimate the channel. We show that our coding/training/estimation scheme and minimum distance decoding achieves an error probability performance similar to that achieved with perfect channel knowledge.

We consider Gaussian multiple-input multiple-output (MIMO) channels with discrete input alphabets. We propose a non-diagonal precoder based on the X-Codes in to increase the mutual information. The MIMO channel is transformed into a set of parallel subchannels using Singular Value Decomposition (SVD) and X-Codes are then used to pair the subchannels. X-Codes are fully characterized by the pairings and a 2 × 2 real rotation matrix for each pair (parameterized with a single angle). This precoding structure enables us to express the total mutual information as a sum of the mutual information of all the pairs. The problem of finding the optimal precoder with the above structure, which maximizes the total mutual information, is solved by i) optimizing the rotation angle and the power allocation within each pair and ii) finding the optimal pairing and power allocation among the pairs. It is shown that the mutual information achieved with the proposed pairing scheme is very close to that achieved with the optimal precoder by Cruz et al., and is significantly better than Mercury/waterfilling strategy by Lozano et al.. Our approach greatly simplifies both the precoder optimization and the detection complexity, making it suitable for practical applications.

The use of semiconductor amplifier in integrated transceivers increases sensitivity, but changes the noise statistics in pulse amplitude modulation (PAM) intensity modulation with direct detection. Using a straight-forward, mixed noise model, we optimize constellations for these systems with an autoencoderbased neural network (NN). We improve required signal-to-noise ratio (SNR) by 4 dB for amplified spontaneous emission (ASE)limited PAM4 and PAM8, without increasing system complexity. Performance can also be improved in O-band wavelength division multiplexing systems with semiconductor optical amplification and chromatic dispersion (CD). At 53 Gbaud, our simulations show we can extend the reach of PAM4 by 4 to 8 km when combining an optimized constellation with a NN decoder. We present an experimental validation of 4 dB improvement of an ASE-limited PAM4 back-to-back transmission at 60 Gbaud using an optimized constellation and a NN decoder.

This foundational paper, published as Shannon (1959), introduced rate-distortion theory, a cornerstone of information theory that formalizes lossy source coding under a fidelity (distortion) constraint. It extends Shannon’s 1948 channel coding and source coding theorems to scenarios where perfect reconstruction is neither possible nor required, quantifying the minimal rate needed for a source to achieve a specified average distortion level. The work is remarkable for its depth, generality, and prescience, laying the mathematical groundwork for modern lossy compression, vector quantization, perceptual coding, and even applications in machine learning and cognitive science. This review provides a thorough technical summary, analyzes the paper’s contributions from multiple angles (theoretical, computational, applicative), contrasts it with contemporaneous and prior works, and documents key advances over the subsequent 65+ years. Nuances, edge cases, implications, and open questions are highlighted for completeness.

In this work, security evaluation and efficiency implementation of the keystream generator of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written with MATLAB.7.5. First of all, two different original images are used to validate the proposed design. The developed program is used to transform the original images data into digital image file. Finally, the proposed program is implemented to encrypt and decrypt images data. Several tests are done to prove the design performance, including visual tests and security evaluation. Key–Words: Achterbahn-128, Keystream Generator, Stream Cipher, Image Encryption, Security Analysis.

In this paper, we address the problem of QoS (Quality of Service) provisioning for multi-user video streaming over multiple heterogeneous wireless networks based on the distributed, cross-layer design framework. By jointly considering the rate allocation and the Joint Source-Channel Coding (JSCC), our proposal aims at maximizing the QoS provisioning under the given resource constraint. At first, we develop and evaluate a framework for optimal video rate allocation over multiple networks based on the observed Available Bit Rate (ABR) and the Round Trip Time (RTT) over each access network, as well as the video rate-distortion characteristics. The rate allocation is formulated as a convex optimization problem that minimizes the sum of all video streams expected distortion. Then, we propose an analytical JSCC scheme for error-resilient scalable encoded video, and integrate the JSCC with the specific rate allocation algorithm to improve the constructed video quality by optimally applying the appropriate channel coding rate given the constraints imposed by the transmission rate and the prevailing channel conditions. Objective and subjective simulation results are provided which demonstrate the effectiveness of our proposed joint scheme.

We consider a Gelfand-Pinsker discrete memoryless channel (DMC) model and provide a strong converse for its capacity. The strong converse is then used to obtain an upper bound on the reliability function. Instrumental in our proofs is a new technical lemma which provides an upper bound for the rate of codes with codewords that are conditionally typical over large message dependent subsets of a typical set of state sequences. This technical result is a nonstraightforward analog of a known result for a DMC without states that provides an upper bound on the rate of a good code with codewords of a fixed type (to be found in, for instance, the Csiszár-Körner book).

In order to achieve the ultimate capacity limit of a communication channel, Shannon demonstrated the use of infinitely long sequence of random codes. However, these codes are impractical as a result of their astronomical number of codewords. The performance of the different rates Low Density Parity Check (LDPC) codes together with the various modulation techniques defined for the IEEE 802.16e standard over the Binary Input Additive White Gaussian Noise (BI-AWGN) channel is investigated in this paper. The Bit error rate (BER) results obtained showed that reliable transmission of information can be achieved in proximity to the capacity of the BI-AWGN channel through the use LDPC codes.

In this paper, two decision methods for the conventional and spread frequency shift keying (FSK and SFSK) are detailed and their extension to the coded FSK using the permutation coding are proposed. The performance results of the different methods are compared under the real indoor narrowband PLC (NB PLC) channel attenuation and impulse noise. The decision schemes are mainly the probability density function PDF-based system for the SFSK and the Non-PDF-based system (select largest) for the conventional FSK. The BER performances of the different techniques prove that the coded FSK using the Select Largest method achieves good performance results in the PLC constraints while having a low complexity, in comparison with SFSK system. The coded FSK Select Largest gives an error floor equal to 6×10 under impulse noise and channel effect compared to 2×10achieved by the coded SFSK. Index Terms FSK, SFSK, coded modulation, permutation codes, channel attenuation, impulse noise, BER.

Compression of a noisy source is usually a two stage problem, involving the operations of estimation (denoising) and quantization. A survey of literature on this problem reveals that for the squared error distortion measure, the best possible compression strategy is to subject the noisy source to an optimal estimator followed by an optimal quantizer for the estimate. What we present in this paper is a simple but sub-optimal vector quantization (VQ) strategy that combines estimation and compression in one efficient step. The idea is to train a VQ on pairs of noisy and clean images. When presented with a noisy image, our VQ-based system estimates the noise variance and then performs joint denoising and compression. Simulations performed on images corrupted by additive, white, Gaussian noise show significant denoising at various bit rates. Results also indicate that our system is robust enough to handle a wide range of noise variations, while designed for a particular noise variance.

Wireless is a term used to describe telecommunications in which electromagnetic waves (rather than some form of wire) carry the signal over part or all of the communication path. Quite a few popular applications over the wireless communication networks get emerged just lately including, cellular telephony, SMS, MMS, world-wide-web browsing as well as video conferencing, to name a few. Data might be damaged during transmission. For reliable communication, error must be detected and corrected. Joint Channel Coding and Cryptography has been analyzed and simulated in this paper. The method is an extension of Soft Input Decryption with feedback, which is used for improvement of channel decoding of secured messages. we utilize the methods for data security as a tool for the detection and correction of transmission errors. Streaming applications are gaining popularity over not only the fixed Internet but also mobile handheld devices. Growth in wireless access technologies along with the advanced coding schemes show the promise of better streaming service for the mobile users. However, wireless channels are characterized by fluctuating bandwidth, thereby making it challenging for streaming applications to ensure good quality of user experience (QoE). In this paper, we adopt an objective approach and propose a cross-layer adaptive streaming technique, where we make use of the channel loss information to update the application layer encoding at a slower rate and the link layer modulation and coding scheme at a faster rate. In our adaptive scheme, we focus on a pause-free playback by preventing buffer underflow at the receiver. Our simulation experiments show that, the proposed adaptive technique improves the QoE of the streaming significantly by gracefully degrading quality in the face of pathological cases such as wireless channel error, while ensuring an uninterrupted services.

An error resilient video coding scheme based on unequal error protection over error prone channels is proposed. Due to the sensitivity of VLC to channel errors, a single bit error can cause loss of synchronization at the receiver, leading to catastrophic degradation of image quality. Multiplexed codes are an effective approach to combat losses of synchronization. In this paper, multiplexed codes appropriate to video coding are designed and then integrated into a block based motion compensated video coder. We compared performances of this structure with one of the most used codes: Huffman code. Results show that the proposed scheme achieves high error resilience at almost no cost in compression efficiency.

Summary In this paper, we dealt with an unequal error protection (UEP) solution for visual-based quantized JPEG images coded and transmitted over time-varying channels by focusing our purpose on the question of how to improve the total rate-distortion performances of a given UEP scheme. In consequence, over an UEP scheme, a packet transmission solution is proposed with a retransmission protocol using rate-compatible punctured convolutional codes (RCPC codes). The simulated time-varying channel is a Rayleigh fading type where the transmitted packets do not always experience the channel distortion with the same intensity. Attractive results are issued from our simulations.

In this paper, we present a new Multiple Description Coding (MDC) system that enables the progressive transmission of images over unreliable channels with variable bandwidth. The proposed system employs a new type of quantizers, called Embedded Multiple Description Scalar Quantizers (EMDSQ). The system relies on wavelet-based QuadTree (QT) coding of the significance maps to encode the quantizers' output, and is referred to as Multiple Description-QT (MD-QT) coding. The EMDSQ enables the MD-QT coder to provide bit-streams that meet the desired features consisting of a high redundancy level, fine-grain rate adaptation and progressive transmission of each description. Experimental results show that the proposed MD-QT system based on EMDSQ yields better ratedistortion performance in comparison to MD-QT employing the embedded Multiple Description Uniform Scalar Quantizers (MDUSQ) previously proposed in the literature. Communication systems based on diversity techniques have become an attractive solution for robust transmission over error-prone bandwidth-limited channels. Multiple Description Coding (MDC) addresses the problem of coding a source in order to be transmitted over a communication network with diversity, and, at the decoder level, it allows for extracting meaningful information from a subset of the bit-stream. Previous research focused on finding the optimal achievable rates-distortion regions . Lately, practical compression systems that rely on quantization techniques, as proposed in [2], [3], were designed in order to meet those theoretical boundaries. The design of multiple description scalar quantizers (MDSQ) was pioneered in [2], under the assumption of fixed-length codes and fixed codebook sizes. Significant improvements are reported in in which the quantizers' design is made under a given entropy-constraint, and not on a given codebook size. The communication robustness over unreliable channels provided by the MDC system is strongly correlated with the delivery of highly error-resilient bit-streams, a feature achievable with a corresponding high level of redundancy. Furthermore, for bandwidth-varying channels, it is desirable to transmit fine-grain scalable bit-streams. Such a system is described in where the progressive MDC algorithm is based on multiple description uniform scalar quantizers (MDUSQ). For a high level of redundancy and for low bitrates, the approach of [4] outperforms the embedded MDC algorithm of [5] based on the polyphase transform. In the same context, we proposed in [6], [7] a new type of embedded multiple description scalar quantizer (EMDSQ), providing a fine-grain refinable representation of the input data and targeting a high level of redundancy. The embedded quantizer design follows the constraint of constructing double-deadzone central quantizers for each quantization level. In this paper we propose a new wavelet-based MDC system that employs the EMDSQ and a customized version of the QuadTree (QT) coding of the significance maps algorithm of . The system will be referred to as Multiple Description-QT (MD-QT) coding. The EMDSQ, by their features, allow the MD-QT coder to provide bit-streams that meet the desired features consisting of a high redundancy level, fine-grain rate adaptation and progressive transmission of each description. Moreover, the generalized form of EMDSQ targeting an arbitrary number of channels offers the possibility of designing realistic coders for practical multi-channel communication systems. Such systems reconstruct the central channel by using techniques such as synchronization markers to isolate the undamaged data from a partially damaged received side channel. In this context, for an erasure channel model with burst errors, progressive transmission is providing quality scalability for the central-channel reconstruction. The MDUSQ of [4] and our EMDSQ [6], are incorporated in the proposed MD-QT coding scheme. The rate-distortion performances of both MDC systems are compared when applied on a common dataset. The results demonstrate that the MDC system based on EMDSQ achieves systematically better rate-distortion performance on a broad range of bit-rates. The paper is structured as follows. In Section 2 the EMDSQ generalized form for M-channels is introduced. The MD-QT coding system is described in Section 3. In Section 4 comparative coding results are provided, and finally, Section 5 draws the conclusions of our work.

The consequence of simultaneous transmissions by nodes in inter-working multi-hop wireless networks is inter-node interference. Inter-node interference is a metric that is important for the performance evaluation of inter-working wireless networks. Several interference models exist in literature, however, these models are for specific wireless networks and MAC protocols. Due to the heterogeneity of link-level technologies in interworking multi-hop wireless networks, it is desirable to have generic models for the evaluation of interference on links in such networks. A generic model can provide information about the interference level on a link irrespective of the MAC protocol in use. This paper presents a generic interference model. The model evaluates the probability of interference and uses the negative second moment of the distance between a receiver-node and interfering-nodes to evaluate the interference power on a link in an inter-working multi-hop wireless network. Numerical results of the performance of the model are presented.

There are some video standards that are used in the digital life. The video standard is used for respective purposes such as storage, video streaming, or video transmission. In order to encode the video files into some specific standard video, the video encoder software is required to perform the video processing. For the well-established video coding standard, the video encoder software is coming on ready used software packages. But for SVC, as an ongoing video standard, the available encoder software is the reference software which ...

Design of low-energy communications systems requires attention to power consumption in the overall system design and the algorithm implementations. We consider design of a communications system incorporating digital transmission and receiver filters, and error-control coding. Various well-known channel codes including turbo codes, block codes, and convolutional codes are studied. For each of these decoders, its decoding performance and power consumption are evaluated from VLSI chip designs. We then demonstrate optimization of a simple design from a total system perspective.

Materi ini menyajikan panduan lengkap mengenai penggunaan flowchart sebagai alat bantu visual untuk memahami alur logika pemrograman, khususnya bagi siswa kelas VII. Flowchart didefinisikan sebagai representasi grafis yang menggunakan simbol standar untuk menggambarkan urutan langkah, tugas, atau keputusan dalam suatu proses. Dalam konteks koding, flowchart berfungsi untuk memvisualisasikan algoritma yang kompleks, mendeteksi kesalahan logika sejak dini, serta menjadi dokumentasi program yang jelas.
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Presentasi ini merinci simbol-simbol dasar seperti terminator, process, decision, dan input/output, serta memberikan panduan langkah demi langkah dalam menyusun alur yang logis . Melalui contoh konkret penentuan bilangan ganjil atau genap, dijelaskan perbedaan antara flowchart sebagai alat visual dan algoritma sebagai urutan langkah sistematis. Penguasaan materi ini diharapkan dapat membantu siswa membangun fondasi berpikir sistematis dan memahami logika dasar pemrograman sebelum memasuki tahap penulisan kode yang sebenarnya.

Kata Kunci: Flowchart, Logika Pemrograman, Algoritma, Koding Kelas VII, Visualisasi Proses.

In this work, we propose structured Root-Check Low-Density Parity-Check (LDPC) codes and design techniques for block-fading channels. In particular, Quasi-Cyclic Root-Check LDPC codes, Irregular repeat-accumulate Root-Check LDPC codes and Controlled Doping Root-Check LDPC codes based on Progressive Edge Growth (PEG) techniques for block-fading channels are proposed. The proposed Root-Check LDPC codes are both suitable for channels under F = 2, 3 and 4 independent fading per codeword. The performance of the proposed codes is investigated in terms of Frame Error Rate (FER). The proposed Root-Check LDPC codes are capable of achieving the channel diversity and outperform standard LDPC codes. For block-fading channel with F = 2 our proposed PEG-based Root-Check LDPC codes outperform PEG-based LDPC codes by 7.5dB.

— Fault-tolerance and data fusion have been considered as two fundamental functions in wireless sensor networks. In this paper, we propose a novel approach for distributed multiclass classi cation using a fault-tolerant fusion rule for wireless sensor networks. Binary decisions from local sensors, possibly in the presence of faults, are forwarded to the fusion center that determines the nal classi cation result. Classi cation fusion in our approach is implemented via error correcting codes to incorporate fault-tolerance capability. This new approach not only provides an improved fault-tolerance capability but also reduces computation time and memory requirements at the fusion center. Code matrix design is essential for the design of such systems. Two ef cient code matrix design algorithms are proposed in this paper. The relative merits of both algorithms are also studied. We also develop suf cient conditions for asymptotic detection of the correct hypothesis by the proposed approach...

In this work, the priority-first sequential-search decoding algorithm proposed in is revisited. By replacing the conventional Fano metric by one that is derived based on the Wagner rule, the sequentialsearch decoding in guarantees the maximum-likelihood (ML) performance, and hence, was named the maximum-likelihood sequential decoding algorithm (MLSDA). It was then concluded by simulations that the software computational complexity of the MLSDA is in general considerably smaller than that of the Viterbi algorithm. A common problem on sequential-type decoding is that at the signal-to-noise ratio (SNR) below the one corresponding to the cutoff rate, the average decoding complexity per information bit and the required stack size grow rapidly with the information length . This problem to some extent prevent the practical use of sequential-type decoding from convolutional codes with long information sequence at low SNRs. In order to alleviate the problem in the MLSDA, we propose to directly eliminate the top path whose end node is ∆-trellis-level prior to the farthest one among all nodes that have been expanded thus far by the sequential search, which we termed the early elimination. Following random coding argument, we analyze the early-elimination window ∆ that results in negligible performance degradation

The ongoing development of wireless sensor networks (WSNs) demands not only low-power sensors and less system cost but also good performance. Considering this background, investigating a new technology to satisfy both requirements is an important issue for current development of wireless sensor network systems. In this paper, we consider the situation that the sensor nodes in WSNs are deployed in a harsh environment such that both channel fading and unexpected sensor faults may occur. This work then proposes to combine channel estimation and sensorfault protection using error-correcting coding technique so as to free the costly devices of channel estimation and equalization from fusion centers. Simulations, performed to examine the performance of our proposed blind-detection scheme, show that it can compete with the conventional training-sequence-based fusion in performance when the training sequences are retained for information bearing. By this new approach, the complexity in fusion centers can be reduced and the transmitted power of sensors decreased without sacrificing the performance.

Many of the standard compression methods are based, at their lowest level, in coding digital words of variable length or VLC, Huffman type, designed in 1952 or in any of its versions, as canonical. This article presents an VLC with greater efficiency than Huffman encoding, named as "Leveling", which uses two variants, "Leveled Reordering" for low redundancy, e.g. for text and, "Segmented Leveling" for middle and high redundancy, for image processing. Leveling, developed by Javier Joglar in 1995, uses the concepts of "meaning" and "ordering" of the VLC codes generated, to get optimum performance in terms of "compression ratio", higher than any other non-adaptive VLC.

Many of the standard compression methods are based, at their lowest level, in coding digital words of variable length or VLC, Huffman type, designed in 1952 or in any of its versions, as canonical. This article presents an VLC with greater efficiency than Huffman encoding, named as "Leveling", which uses two variants, "Leveled Reordering" for low redundancy, e.g. for text and, "Segmented Leveling" for middle and high redundancy, for image processing. Leveling, developed by Javier Joglar in 1995, uses the concepts of "meaning" and "ordering" of the VLC codes generated, to get optimum performance in terms of "compression ratio", higher than any other non-adaptive VLC.

Given a number of available layers of source data and a transmission bit budget, we propose an algorithm that determines how many layers should be sent and how many protection bits should be allocated to each transmitted layer such that the expected distortion at the receiver is minimum. The algorithm is used for robust transmission of progressively compressed 3D models over a packet erasure channel. In contrast to the previous approach, which uses exhaustive search, the time complexity of our algorithm is linear in the transmission bit budget.

We consider live unicast video streaming over a packet erasure channel. To protect the transmitted data, previous solutions use forward error correction (FEC), where the channel code rate is fixed in advance according to an estimation of the packet loss rate. However, these solutions are inefficient under dynamic and unpredictable channel conditions because of the mismatch between the estimated packet loss rate and the actual one. We introduce a new approach based on rateless codes and receiver feedback. For every source block, the sender keeps on transmitting the encoded symbols until it receives an acknowledgment from the receiver indicating that the block was decoded successfully. Within this framework, we provide an efficient algorithm to minimize bandwidth usage while ensuring successful decoding subject to an upper bound on the packet loss rate. Experimental results showed that compared to traditional fixed-rate FEC, our scheme provides significant bandwidth savings for the same playback quality.

Video streaming over the Internet and packet-based wireless networks is sensitive to packet loss, which can severely damage the quality of the received video. To protect the transmitted video data against packet loss, application-layer forward error correction (FEC) is commonly used. Typically, for a given source block, the channel code rate is fixed in advance according to an estimation of the packet loss rate. However, since network conditions are difficult to predict, determining the right amount of redundancy introduced by the channel encoder is not obvious. To address this problem, we consider a general framework where the sender applies rateless erasure coding to every source block and keeps on transmitting the encoded symbols until it receives an acknowledgment from the receiver indicating that the block was decoded successfully. Within this framework, we design transmission strategies that aim at minimizing the expected bandwidth usage while ensuring successful decoding subject to an upper bound on the packet loss rate. In real simulations over the Internet, our solution outperformed standard FEC and hybrid ARQ approaches. For the QCIF Foreman sequence compressed with the H.264 video coder, the gain in average peak signal to noise ratio over the best previous scheme exceeded 3.5 decibels at 90 kilobits per second.