Channel Coding Parameters Research Articles

Blind recognition of channel codes based on a multiscale dilated convolution neural network

Channel coding is an essential part of communication. In a non-cooperative communication system, the receiver has to recover the signal without any priori knowledge. Therefore, it is important to recognize channel code types and parameters. At present, only a few studies focus on channel code type recognition. In this paper, a multiscale dilated convolution neural network (MSDCNN) is proposed to achieve fine-grained recognition of seven commonly used channel code types. MSDCNN has three multiscale modules. Based on the characteristics of each channel code type, the first two identical modules are designed to extract the overall features of codewords with unit convolution and three parallel regular convolution layers. To lower complexity, the third module uses dilated convolution instead of regular convolution to extract features between codewords. Simulation results show that MSDCNN has higher average recognition accuracy than other neural networks. More importantly, MSDCNN lowers complexity, making it more suitable for deployment so that it can be applied in practical non-cooperative receivers.

Analysis and application research on key issues of channel coding

Channel coding plays a crucial role in enhancing the reliability and efficiency of communication systems, particularly when transmission channels are disrupted by noise and interference. This paper presents an in-depth review of various channel coding techniques, their applications, and future research directions. Key topics discussed include prevalent channel coding methods, such as repetition codes, convolutional codes, LDPC codes, turbo codes, and polar codes. The paper also delves into the selection of suitable channel coding parameters and their applications in digital TV, mobile and satellite communications, unmanned aerial vehicle data links, speech communication, and underwater acoustic channels. Moreover, the paper explores the performance analysis and comparison of different channel coding techniques, shedding light on their strengths and weaknesses. Lastly, the paper identifies emerging trends and challenges in channel coding research, providing valuable insights for researchers and practitioners in the field of communication systems. By examining these techniques and future directions, this comprehensive overview aims to contribute to the development of more robust and efficient channel coding schemes for a wide range of communication applications.

3GPP 5G V2X Scenarios: Performance of QoS Parameters Using Turbo Codes

Cellular vehicle-to-everything (C-V2X) communication has recently gained attention in industry and academia. Different implementation scenarios have been derived by the 3rd Generation Partnership Project (3GPP) 5th Generation (5G) Vehicle-to-Everything (V2X) standard, Release 16. Quality of service (QoS) is important to achieve reliable communication and parameters which have to be considered are reliability, end-to-end latency, data rate, communication range, throughput and vehicle density for an urban area. However, it would be desirable to design a dynamic selecting system (with emphasis on channel coding parameters selection) so that all QoS parameters are satisfied. Having this idea in mind, in this work we examine nine V2X implementation scenarios using Long Term Evolution (LTE) turbo coding with a geometry−based efficient propagation model for vehicle-to-vehicle communication (GEMV), where we consider the above QoS parameters for SOVA, log-MAP and max-log-MAP decoding algorithms. Our study is suitable for 3GPP cooperative sensing, for the eight scenarios considering medium and large signal-noise-ratio (SNR) values. The proposed model is sustainable despite a doubled data rate, which results in a minimal bit error rate (BER) performance loss up to 1.85 dB. In this case tripling the data rate results in a further 1 dB loss. Moreover, a small loss up to 0.4 dB is seen for a vehicle speed increase from 60 km/h to 100 km/h. Finally, increasing vehicle density has no effect on the implemented 3GPP scenario considering end-to-end latency, irrespectively from the decoding algorithm.

Performance Analysis of Coded OTFS Systems Over High-Mobility Channels

Orthogonal time frequency space (OTFS) modulation is a recently developed multi-carrier multi-slot transmission scheme for wireless communications in high-mobility environments. In this paper, the error performance of coded OTFS modulation over high-mobility channels is investigated. We start from the study of conditional pairwise-error probability (PEP) of the OTFS scheme, based on which its performance upper bound of the coded OTFS system is derived. Then, we show that the coding improvement for OTFS systems depends on the squared Euclidean distance among codeword pairs and the number of independent resolvable paths of the channel. More importantly, we show that there exists a fundamental trade-off between the coding gain and the diversity gain for OTFS systems, i.e., the diversity gain of OTFS systems improves with the number of resolvable paths, while the coding gain declines. Furthermore, based on our analysis, the impact of channel coding parameters on the performance of the coded OTFS systems is unveiled. The error performance of various coded OTFS systems over high-mobility channels is then evaluated. Simulation results demonstrate a significant performance improvement for OTFS modulation over the conventional orthogonal frequency division multiplexing (OFDM) modulation over high-mobility channels. Analytical results and the effectiveness of the proposed code design are also verified by simulations with the application of both classical and modern codes for OTFS systems.

Deep-Learning-Based Blind Recognition of Channel Code Parameters Over Candidate Sets Under AWGN and Multi-Path Fading Conditions

We consider the problem of recovering channel code parameters over a candidate set by merely analyzing the received encoded signals. We propose a deep learning-based solution that I) is capable of identifying the channel code parameters for any coding scheme (such as LDPC, Convolutional, Turbo, and Polar codes), II) is robust against channel impairments like multi-path fading, III) does not require any previous knowledge or estimation of channel state or signal-to-noise ratio (SNR), and IV) outperforms related works in terms of probability of detecting the correct code parameters.

Reverse recognition of LDPC codes based on log-likelihood ratio

With the development of Adaptive Modulation and Coding (AMC) technology, blind identification of channel coding parameters has recently attracted more attention. To reduce the computational complexity of the closed set recognition of problem low-density parity-check (LDPC) codes, this paper improves a closed set reverse recognition algorithm based on the maximum mean log-likelihood ratio. Before using soft decision information to make a decision, the check vector is first filtered to select some check vectors to reduce the computational complexity. The experimental results show that this method can complete the inverse identification of closed sets of LDPC codes in the case of low signal-to-noise ratio. Compared with the previous algorithm, the time complexity of the proposed algorithm is significantly reduced.

Reliable OFDM Data Transmission with Pilot Tones and Error-Correction Coding in Shallow Underwater Acoustic Channel

The performance of Underwater Acoustic Communication (UAC) systems are strongly related to the specific propagation conditions of the underwater channel. Horizontal, shallow-water channels are characterised by extremely disadvantageous transmission properties, due to strong multipath propagation and refraction phenomena. The paper presents the results of communication tests performed during a shallow, inland-water experiment with the use of a laboratory model of a UAC system implementing the Orthogonal Frequency-Division Multiplexing (OFDM) technique. The physical layer of data transmission is partially configurable, enabling adaptation of the modulation and channel coding parameters to the specific propagation conditions. The communication tests were preceded by measurement of the UAC channel transmission properties. Based on the estimated transmission parameters, four configurations of OFDM modulation parameters were selected, and for each of them, communication tests were performed with the use of two Error-Correction Coding (ECC) techniques. In each case, the minimum coding rate was determined for which reliable data transmission with a Bit Error Rate (BER) of less than 10 − 4 is possible.

Blind recognition of LDPC code parameters over erroneous channel conditions

Blind reconstruction of channel coding parameters plays a significant role in non-cooperative military and spectrum surveillance applications. Further, it also gives additional advantages in applications such as cognitive radio, adaptive modulation and coding, and so on. In this study, blind estimation algorithms are proposed to identify code dimension and codeword length parameters of low-density parity-check (LDPC) codes at the receiver over noisy or erroneous channel conditions assuming a non-cooperative scenario. The proposed algorithms are validated using different test cases. Moreover, the accuracy of estimation of code dimension and codeword length parameters of LDPC codes using the proposed algorithms is also given for different M -ary phase-shift keying schemes. From the simulation results, it is observed that the accuracy of estimation improves with decrease in code rate, codeword length, and modulation order.

Energy-Efficient Channel Coding Strategy for Underwater Acoustic Networks.

Underwater acoustic networks (UAN) allow for efficiently exploiting and monitoring the sub-aquatic environment. These networks are characterized by long propagation delays, error-prone channels and half-duplex communication. In this paper, we address the problem of energy-efficient communication through the use of optimized channel coding parameters. We consider a two-layer encoding scheme employing forward error correction (FEC) codes and fountain codes (FC) for UAN scenarios without feedback channels. We model and evaluate the energy consumption of different channel coding schemes for a K-distributed multipath channel. The parameters of the FEC encoding layer are optimized by selecting the optimal error correction capability and the code block size. The results show the best parameter choice as a function of the link distance and received signal-to-noise ratio.

Delay–Rate–Distortion Optimized Rate Control for End-to-End Video Communication Over Wireless Channels

In addition to the rate-distortion (R-D) behavior, in a real-time wireless video communication system, the end-to-end delay would also significantly affect the overall video reception quality. To analyze, control, and optimize the R-D behavior under the end-to-end delay constraint, in this paper we extend the traditional R-D optimization (RDO) for the wireless video communication system and formulate a novel delay-RDO-based rate control problem, by investigating the allocation of end-to-end delay to different delay components. It aims at minimizing the average total end-to-end distortion under the transmission rate and end-to-end delay constraints, by a joint selection of both the source coding and the channel coding parameters. The wireless channel is represented by a finite-state Markov channel model characterizing the time-varying process and predicting the future channel condition. As applicable solutions, a practical algorithm based on the Lagrange multiplier approaches, Karush-Kuhn-Tucker conditions, and sequential quadratic programming methods is developed. The experimental results demonstrate the superiority of the proposed algorithm over the existing schemes.

An Improved Algorithm of RS Codes Blind Recognition

The acquisition of information about channel coding sequences is the research emphasis and difficulties at present, and recognizing the channel coding parameters is the prerequisite for information acquisition. RS Codes are a class of linear block codes as well as a special class of BCH Codes and cyclic codes. It regards a group of symbols with a length of n as a unit to process with, and the n symbols are generated by k transmitting information symbols under some proper associated rules. RS Codes are widely used in various communication systems. In this paper, an algorithm of RS Codes blind recognition is researched. And a blind recognition model is established on MATLAB. At last, the paper presents the recognition rates of situations with different error rates.

BCH 부호 식별 및 생성 파라미터 추정 기법

잡음이 존재하는 채널을 통하여 디지털 통신을 하는 경우 일반적으로 채널 부호를 사용한다. 만약 수신측에서 채널 부호의 생성 파라미터를 모르는 경우, 채널 부호의 복호는 매우 어렵다. 이러한 경우에 수신데이터의 정확한 복호를 위해서는 채널부호의 종류 및 생성 파라미터를 알아내는 방법이 필요하다. 본 논문에서는 BCH(Bose-Chaudhuri-Hocquenghem) 부호의 생성 파라미터인 생성다항식을 추정하는 기법을 소개한다. 이 방법은 생성다항식이 최소다항식으로 구성된다는 특징과 순회부호의 특성을 이용한 방법이다. 그리고 종래 방법에 비해 생성다항식 추정 성능을 향상 시킬 수 있는 결정 확률 변수 보상 기법을 제안한다. 제안한 기법은 랜덤데이터 패턴이 생성다항식을 구성하는 최소다항식으로 나누어지는 특성을 이용한 기법이다. 또한 컴퓨터 시뮬레이션을 통해 제안한 알고리즘의 우수성을 검증한다. The use of an error-correcting code is essential in communication systems where the channel is noisy. When channel coding parameters are unknown at a receiver side, decoding becomes difficult. To perform decoding without the channel coding information, we should estimate the parameters. In this paper, we introduce a method to reconstruct the generator polynomial of BCH(Bose-Chaudhuri-Hocquenghem) codes based on the idea that the generator polynomial is compose of minimal polynomials and BCH code is cyclic code. We present a probability compensation method to improve the reconstruction performance. This is based on the concept that a random data pattern can also be divisible by a minimal polynomial of the generator polynomial. And we confirm the performance improvement through an intensive computer simulation.

Stochastic-Resonance Based Iterative Detection for Serially-Concatenated Turbo Codes

In this letter, the concept of multiple serially-concatenated codes is invoked in the context of stochastic resonance (SR), where the achievable performance is improved by increasing noise power. More specifically, the receiver's iterative decoding process is characterized with the aid of extrinsic information transfer (EXIT) charts, such that the SR effect induced by a non-linear component is taken into account. Our simulation results demonstrate that although the SR demodulator's log-likelihood ratio (LLR) outputs are not Gaussian distributed, the corresponding EXIT trajectory matches the prediction from the associated inner- and outer-codes' EXIT curves, while reaching the perfect convergence point in terms of mutual information. Therefore, an infinitesimally low bit-error ratio (BER) is attained by appropriately designing the channel code's parameters based on EXIT charts.

길쌈 부호 복원 및 성능 분석

The use of an error-correcting code is essential in communication systems where the channel is noisy. Unless a receiver has accurate channel coding parameters, it becomes difficult to decode the digitized encoding bits correctly. In this paper, we propose two algorithms for reconstructing convolutional codes: one for general convolutional codes and the other for punctured convolutional codes. And we also verify the algorithms by performing intensive computer simulation in additive white gaussian noise (AWGN) channel.

FHT를 이용한 RM부호 인식 알고리즘

The use of an error-correcting code is essential in digital communication systems where the channel is noisy. Unless a receiver has accurate channel coding parameters, it becomes difficult to decode the digitized encoding bits correctly. In this paper, estimation algorithm for RM(Reed-Muller) codes using FHT (Fast Hadamard algorithm) is proposed. The proposed algorithm estimates the channel coding parameters of RM codes and then decodes the codes using the characteristic of FHT. And we also verify the algorithm by performing intensive computer simulation in additive white gaussian noise (AWGN) channel.

Coded Hierarchical Modulation for Wireless Progressive Image Transmission

A robust coded scheme for progressive multimedia transmission is proposed for additive white Gaussian noise, flat Rayleigh fading channels, and frequency-selective channels using different unequal error protection methods in combination. Hierarchical modulation is coupled with a packetization/combining strategy and an efficient channel encoder consisting of a cyclic redundancy check outer coder concatenated with an inner rate-compatible punctured convolutional coder. Distortion-optimal hierarchical parameters are jointly chosen with the set of channel coding parameters on a packet-switched wireless network with fixed length packets. A lower bound for the performance improvement of the proposed system is derived and shown to give significant gains at lower packet sizes and higher transmission rates. The proposed system is also shown to outperform several existing schemes for realistic wireless channels.

Joint coding rate control for audio streaming in short range wireless networks

Streaming high quality audio/video (AV) from home media sources to TV sets and audio speakers over a wireless local area network (WLAN) is a challenging problem because of the fluctuating bandwidth caused by interference and fading. Retransmission and data buffering, as common techniques in data transfer over error-prone channels, are not adequate for delay sensitive applications such as high quality audio streaming. Our approach is to adjust the audio data rate dynamically in order to improve the perceptual quality of audio according to wireless channel quality. In this paper we specifically focus on robust audio streaming over short range wireless channels. The major strength of the proposed algorithm is in its ability to match the source and channel coding parameters to the given channel conditions, thus providing better quality and lower latency of audio in home networking.