Symbol Rate Solution

STEP 0: Pre-Calculation Summary
Formula Used
Symbol Rate = Information Rate/Entropy
rs = R/H[S]
This formula uses 3 Variables
Variables Used
Symbol Rate - (Measured in Bit per Second) - Symbol Rate refers to the number of symbols transmitted per second in a digital communication system.
Information Rate - (Measured in Bit per Second) - The Information rate is defined as the product of the average information content per symbol and the message symbol rate.
Entropy - (Measured in Bit per Second) - Entropy is a measure of the uncertainty of a random variable. Specifically, it measures the average amount of information contained in each possible outcome of the random variable.
STEP 1: Convert Input(s) to Base Unit
Information Rate: 1800 Bit per Second --> 1800 Bit per Second No Conversion Required
Entropy: 1.8 Bit per Second --> 1.8 Bit per Second No Conversion Required
STEP 2: Evaluate Formula
Substituting Input Values in Formula
rs = R/H[S] --> 1800/1.8
Evaluating ... ...
rs = 1000
STEP 3: Convert Result to Output's Unit
1000 Bit per Second --> No Conversion Required
FINAL ANSWER
1000 Bit per Second <-- Symbol Rate
(Calculation completed in 00.004 seconds)

Credits

Creator Image
Created by Aman Dhussawat
GURU TEGH BAHADUR INSTITUTE OF TECHNOLOGY (GTBIT), NEW DELHI
Aman Dhussawat has created this Calculator and 50+ more calculators!
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Verified by Parminder Singh
Chandigarh University (CU), Punjab
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Continuous Channels Calculators

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Noise Power of Gaussian Channel
​ LaTeX ​ Go Noise Power of Gaussian Channel = 2*Noise Power Spectral Density*Channel Bandwidth
Information Rate
​ LaTeX ​ Go Information Rate = Symbol Rate*Entropy
Nyquist Rate
​ LaTeX ​ Go Nyquist Rate = 2*Channel Bandwidth

Symbol Rate Formula

​LaTeX ​Go
Symbol Rate = Information Rate/Entropy
rs = R/H[S]

What is meant by noise spectral density?

The noise spectral density of an ADC can be defined easily as the full-scale signal power of an ADC less the noise power, spread across 1 Hz bandwidth unit increments. A changing FFT sampling depth does not alter an ADC's spectral noise density. It only spreads the noise across different unit bandwidths of frequency.

How to Calculate Symbol Rate?

Symbol Rate calculator uses Symbol Rate = Information Rate/Entropy to calculate the Symbol Rate, The Symbol Rate formula is defined as the number of symbol changes or transitions that occur per second in a digital communication system. In other words, it represents the rate at which symbols are transmitted over a communication channel. Symbol Rate is denoted by rs symbol.

How to calculate Symbol Rate using this online calculator? To use this online calculator for Symbol Rate, enter Information Rate (R) & Entropy (H[S]) and hit the calculate button. Here is how the Symbol Rate calculation can be explained with given input values -> 1000 = 1800/1.8.

FAQ

What is Symbol Rate?
The Symbol Rate formula is defined as the number of symbol changes or transitions that occur per second in a digital communication system. In other words, it represents the rate at which symbols are transmitted over a communication channel and is represented as rs = R/H[S] or Symbol Rate = Information Rate/Entropy. The Information rate is defined as the product of the average information content per symbol and the message symbol rate & Entropy is a measure of the uncertainty of a random variable. Specifically, it measures the average amount of information contained in each possible outcome of the random variable.
How to calculate Symbol Rate?
The Symbol Rate formula is defined as the number of symbol changes or transitions that occur per second in a digital communication system. In other words, it represents the rate at which symbols are transmitted over a communication channel is calculated using Symbol Rate = Information Rate/Entropy. To calculate Symbol Rate, you need Information Rate (R) & Entropy (H[S]). With our tool, you need to enter the respective value for Information Rate & Entropy and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.
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