Information Theory and Channel Coding

2021 ◽  
pp. 427-541
Author(s):  
Stevan Berber
Keyword(s):  
Information Theory ◽  
Channel Capacity ◽  
Gaussian Noise ◽  
Channel Coding ◽  
Signal Transmission ◽  
Convolutional Codes ◽  
Turbo Coding ◽  
Supplementary Material ◽  
Measure Entropy ◽  
Hard Decision

Chapter 9 presents the fundamentals of information theory and coding, which are required for understanding of the information measure, entropy and limits in signal transmission including the definition and derivative of the communication channel capacity. The coding theorem is separtelly presented. The chapter contains a part that defines the entropy of continuous and discrete Gaussian and uniform stochastic processes. The results of this unique analysis is essential to understand the notion of the continuous and discrete white Gaussian noise process. The block and convolutional codes, including hard decision Viterbi algorihthm are presented. The theory of iterative and turbo coding is presented in a form of a Project in the supplementary material, where several topics are defined and the related solutions are offered.

scholarly journals CCSDS telemetry channel coding: the turbo coding option

1998 ◽  
Author(s):  
G.-P. Calzolari ◽  
E. Vassallo ◽  
S. Habinc
Keyword(s):  
Channel Coding ◽  
Turbo Coding

The Capacity of the White Gaussian Noise Channel

1990 ◽  
Vol 4 (3) ◽  
pp. 345-353
Author(s):  
Jerome R. Bretienbach
Keyword(s):  
Channel Capacity ◽  
Gaussian Noise ◽  
White Gaussian Noise ◽  
General Sense ◽  
Infinite Dimensional ◽  
Band Limited ◽  
Arbitrary Noise ◽  
Noise Sequence

The capacity of the white Gaussian noise (WGN) channel is widely stated asS/N0nats/unit time. This conclusion is commonly derived either formally, or from the capacity,Wln(l +S/N0W), of the corresponding band-limited channel with bandwidthW, by takingW→8. In this paper, the WGN channel capacity is instead found directly by treating WGN as an arbitrary noise sequence that whitens in a general sense. In addition, the coding theorems proved make explicit the class of allowable receivers, either finite- or infinite-dimensional correlation receivers, or unconstrained. The capacities for these three receiver classes are found to be, respectively:S/N0forS> 0, and 0 forS= 0; and 8 for allS≥ 0. In those cases where the capacity is infinite, actual transmitter–receiver pairs are specified that achieve capacity.

scholarly journals Técnicas para la implementación de turbo decodificadores con baja latencia

2019 ◽  
pp. 29-41
Author(s):  
Lennin Conrado Yllescas-Calderon ◽  
Ramón Parra-Michel ◽  
Luis F Gonzalez-Pérez
Keyword(s):  
Channel Coding ◽  
Iterative Decoding ◽  
Turbo Coding ◽  
Processing Capacity ◽  
Turbo Decoding ◽  
Turbo Decoder ◽  
Transmission Rates ◽  
Communications Systems ◽  
Lte Advanced ◽  
Turbo Decoders

Turbo coding is a channel coding technique that increases the capacity of communications systems, especially wireless and mobile. Due to its high correction capability, this technique is used in modern wireless communication standards such as 3GPP and LTE/LTE-Advanced. One of the features of these systems is the increase in data processing capacity, where transmission rates of up to 1 Gbps are specified. However, the turbo coding technique inherently presents a limited performance as a consequence of the turbo decoding process at the reception stage. The turbo decoder presents a high operation latency mainly caused by the iterative decoding process, the interleaver and deinterleaver stage and the estimation process of the information bits. In this work, we show the techniques used to implement modern low-latency turbo decoders suitable for 3G and 4G standards.

scholarly journals Rate-compatible LDPC convolutional codes over non-gaussian noise channel

2020 ◽  
Vol 309 ◽  
pp. 01010
Author(s):  
Qiang Liu
Keyword(s):  
Gaussian Noise ◽  
Iterative Decoding ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Convolutional Codes ◽  
Gaussian Mixture ◽  
Performance Study ◽  
Shift Keying ◽  
Non Gaussian ◽  
The Impact

This paper is aimed to study the characteristics of the underwater acoustic channel with non-Gaussian noise channel. And Gaussian mixture model (GMM) is utilized to fit the background noise over the non-Gaussian noise channel. Furthermore, coding techniques which use a sequence of rate-compatible low-density parity-check (RC-LDPC) convolutional codes with separate rates are constructed based on graph extension method. The performance study of RC-LDPC convolutional codes over non-Gaussian noise channel and the additive white Gaussian noise (AWGN) channel is performed. Study implementation of simulation is that modulation with binary phase shift keying (BPSK), and iterative decoding based on pipeline log-likelihood rate belief propagation (LLRBP) algorithm. Finally, it is shown that RC-LDPC convolutional codes have good bit-rate-error (BER) performance and can effectively reduce the impact of noise.

Model- and Information Theory-Based Diagnostic Method for Induction Motors

2005 ◽  
Vol 128 (3) ◽  
pp. 584-591 ◽  
Author(s):  
Sanghoon Lee ◽  
Michael D. Bryant ◽  
Lalit Karlapalem
Keyword(s):  
Information Theory ◽  
Induction Motor ◽  
Channel Capacity ◽  
Diagnostic System ◽  
Functional Health ◽  
State Equations ◽  
Two Phase ◽  
Squirrel Cage ◽  
Three Phase ◽  
Cage Induction Motor

Introduced is a model-based diagnostic system for motors, that also employs concepts of information theory as a health metric. From an existing bond graph of a squirrel cage induction motor, state equations were extracted and simulations performed. Simulated were various cases, including the response of an ideal motor, which functions perfectly to designer’s specifications, and motors with shorted stator coils, a bad phase capacitor, and broken rotor bars. By constructing an analogy between the motor and a communication channel, Shannon’s theorems of information theory were applied to assess functional health. The principal health metric is the channel capacity, which is based on integrals of signal-to-noise ratios. The channel capacity monotonically reduces with degradation of the system, and appears to be an effective discriminator of motor health and sickness. The method was tested via simulations of a three-phase motor; and for experimental verification, a two-phase induction motor was modeled and tested. The method was able to predict impending functional failure, significantly in advance.

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