Breaking News

Meaning of Systematic and Non-systematic code

In coding theory, systematic and non-systematic codes refer to ways of organizing the bits of a message in a code.

Systematic code: If the check bits (the redundancy bits added with message bits to create codeword) and the message bits can be separated or identified from the codewords then it is called systematic code. Examples of systematic codes include Hamming codes, Reed-Solomon codes, and convolutional codes.

Non-systematic code: If the check bits (the redundancy bits added with message bits to create codeword) and the message bits can not be separated or identified from the codewords then it is called non-systematic code. They are mixed in the block of the codeword. Examples of non-systematic codes include cyclic codes and turbo codes.
Read more ...

Line code or coding: their properties

What is Line Coding?

Generally in a digital communication system, the data transmission capacity of a practical channel is much larger than the individual sources. To utilize the channel capacity effectively , we combine several sources through a digital multiplexer using the process of interleaving. The output of a multiplexer is coded into electrical pulses or waveform to transmit data over the channel. This process is called line code/coding or transmission coding. 

Properties of various Line Coding: 

Digital data signal can be transmitted by various line coding. A line code should have the following properties:
1. Transmission power and bandwidth should be as small as possible.
2. It should be possible to detect and correct errors.
3. It should be possible to extract timing or clock information from the signal.
4. The code must be transparent ( receiving every possible sequence of data of the coded signal faithfully).  
Read more ...

What is Aperture effect in digital communication?

The term "aperture effect" is often used in the context of digital communication and refers to the phenomenon where a signal's frequency components are lost during the process of sampling and reconstruction.

In digital communication, analog signals are converted into digital signals through a process called sampling. During sampling, the analog signal is measured at regular intervals, and each sample is represented as a binary code. The samples are then reconstructed into an analog signal at the receiver using a process called reconstruction.

However, there are limitations to the accuracy of the reconstructed signal due to the finite number of samples used. The accuracy is affected by the sampling rate, the bandwidth of the signal, and the reconstruction filter used.

The aperture effect occurs when the bandwidth of the signal exceeds the Nyquist frequency, which is half the sampling rate. In this situation, the high-frequency components of the signal are lost during sampling, resulting in a distorted reconstructed signal. This distortion is known as the aperture effect.
The aperture effect is caused by high-frequency components of the analog signal that are lost during the sampling process when the signal's bandwidth exceeds the Nyquist frequency. 
To reduce or remove the aperture effect, an anti-aliasing filter can be used to remove the high-frequency components of the signal before sampling.

An anti-aliasing filter is a low-pass filter that is placed before the analog-to-digital converter (ADC) in the signal chain. Its purpose is to attenuate the high-frequency components of the analog signal above the Nyquist frequency, so that they do not interfere with the sampling process. By removing these high-frequency components, the anti-aliasing filter ensures that the analog signal is properly sampled and reconstructed with minimal distortion.

The cutoff frequency of the anti-aliasing filter should be set to slightly below the Nyquist frequency of the sampling system. The filter should also have a steep roll-off characteristic to ensure that it effectively removes high-frequency components while minimizing the attenuation of lower frequency components.

In summary, the aperture effect can be reduced or removed by using an anti-aliasing filter to remove high-frequency components of the analog signal before it is sampled. The filter should be designed with a cutoff frequency slightly below the Nyquist frequency and a steep roll-off characteristic to ensure optimal performance.
Read more ...

What is Aliasing in digital communication ?

When the signals are sampled at the rate less than Nyquist rate ( sampling frequency > 2W ), then aliasing take place. [ The sampling rate of 2W samples per second, for a signal bandwidth of W Hz, is called the Nyquist rate; its reciprocal .5W (measured in seconds) is called the Nyquist interval.] Frequencies higher than 'W' takes the form of lower frequencies in sampled spectrum. This is called aliasing.
Aliasing can be reduced by sampling at a rate higher than Nyquist rate.

.
Read more ...
Designed By