Source Coding and Channel Coding

Source Coding and Channel Coding Techniques in Digital Communication

Higher transmission rates and excellent dependability are two major desirable aspects in any digital communication system (ie., low probability of error). Baseband coding methods are utilized to achieve these qualities. Baseband coding may be divided into two categories. Source coding and channel coding are the two types of coding.

For an efficient representation of data generated by a discrete source, source coding is used. By minimizing the duplication of the information source, source coding reduces the average bit rate required for the representation of the source.

Digital information is reliably sent over the channel via channel coding. Channel coding increases communication performance by allowing transmitted signals to survive different channel impairments such as noise, interference, and fading. To give error detection and correction capabilities to the data being broadcast, channel coding schemes include controlled redundancy. As a result, error control coding is another name for channel coding. 

RATIONALE FOR CODING (NEED FOR CODING)

• The transmitted signal power and channel bandwidth are the fundamental communication resources, and these two factors, along with the power spectral density of receiver noise, determine the signal energy per bit-to-noise power density ratio, Eb/No.

• For a given modulation scheme, the Eb/No ratio indicates the probability of error (Pe) or bit error rate (BER).

• Noise generated by the channel might cause mistakes in binary data transmission. i.e., a bit 0 might become a bit 1 and vice versa. These faults have a significant impact on the data transmission's reliability.

• As a result, in reality, it is not possible to deliver adequate data quality with low error performance using the known modulation techniques. In addition, the maximum value of the Eb/No ratio that may be attained is limited.

• As a result, using coding to change data quality from problematic to acceptable is the only feasible option for a fixed Eb/No.

• Reducing the needed Eb/No for a fixed bit error rate is another practical reason for using coding. The needed transmission power will be reduced when the Eb/No ratio is reduced. As a result, hardware costs are reduced by needing a smaller antenna size.

• Figure 1 represents a digital communication system that employs channel coding.

  Figure 1: Digital Communication System with Channel Coding

In a controlled manner, the channel encoder adds additional bits (redundancy) to the message bits. 

• The encoded signal is modulated before being sent across a noisy channel. The channel decoder finds the superfluous bits after demodulation and utilizes them to detect and rectify faults in the message bits. As a result, channel coding reduces the mistakes caused by channel noise.

Drawbacks of channel coding

• Coding adds complexity to the communication system by including redundant bits in coded signals, which increases the necessary transmission capacity.

As a result, consideration of bandwidth and system complexity must be factored into the design trade-offs when using error control coding to obtain acceptable error performance.

TYPES OF CODES:

For error control coding, a variety of codes can be used. The following is a list of the various code classifications.

I. Based on Methodology / Architecture

1. Block Codes:

The channel encoder receives data in k-bit blocks to create an (n, k) block code. It adds (n-k) redundant bits to each block, resulting in an encoded block of n bits. Memory isn't required for block codes.

2. Convolutional Codes:

The discrete-time convolution of the input sequence with the encoder's impulse response is the encoding process in a convolutional code. The message bits are constantly accepted by the convolutional encoder, which then constructs the encoded sequence. Memory is required when using convolutional coding. Tree codes are subdivided into convolutional codes.

II. Based on hardware mechanization required to generate

1. Linear Code:

A linear code has the feature that any two of its codewords may be put together in modulo-2 arithmetic to provide a third codeword. Linear codes are almost commonly employed in practical applications.

2. Nonlinear code:

The Modulo-2 addition of nonlinear codewords does not always result in the production of a third codeword. Nonlinear codes have had a smaller role.

III. Based on the structure of Architecture (Tree / Block)

In block codes, this classification relates to the way redundant bits (check bits) are added to the message (information) bits.

1. Systematic Code:

The redundant (check) bits are introduced in a systematic block code in such a way that the message bits appear first, followed by the redundant (check) bits.

2. Non-Systematic Code:

It is impossible to distinguish between message bits and redundant (check) bits in a non-systematic block coding. They're mixed in the block.

The following is a list of the many error correction/detection codes in the linear coding class.

                                                 Figure 2: Classification of Linear Codes

Sreejith Hrishikesan

Sreejith Hrishikesan is a ME post graduate and has been worked as an Assistant Professor in Electronics Department in KMP College of Engineering, Ernakulam. For Assignments and Projects, Whatsapp on 8289838099.

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