Simulating Intersymbol Interference on channels

  • Thread starter maverick280857
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In summary, the conversation revolves around a Bayesian metric for detecting maximum likelihood sequences on a channel corrupted by ISI. The question is how to use MATLAB to simulate the channel and find the bit error rate, and if there are any recommended resources for simulation methods. There is also mention of a spring cleaning workshop for old threads.
  • #1
maverick280857
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Hi

I'd appreciate help with the following problem:

Suppose I have a Bayesian metric for navigating a trellis to detect the maximum likelihood sequence on a channel corrupted by ISI. The usual Viterbi algorithm works on the usual ML (nonstochastic channel) metric. Now, given the expression for this metric, how can I use MATLAB to simulate the channel? What is the approach to solve such a problem?

Any pointers to existing books or papers on elementary simulation methods would be appreciated too.

Thanks in advance.

EDIT: Given the expression for the metric, how do I find the bit error rate?
 
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ping @jedishrfu Do you know what he's talking about? Spring clean.
 
  • #3
The jedi is in. What's up here?

Greg initiated an old threads cleanup a few months ago and Wrichik and others have been at work cleaning up or deleting the old threads. Basically we add more commentary or references to help future readers who may stumble upon the thread during a google search.
 
  • #4
jedishrfu said:
The jedi is in. What's up here?

Greg initiated an old threads cleanup a few months ago and Wrichik and others have been at work cleaning up or deleting the old threads. Basically we add more commentary or references to help future readers who may stumble upon the thread during a google search.
Yes, this thread is one of those spring cleaning workshop ones. I was hoping you could comment technically on the OP's question.
 

1. What is intersymbol interference (ISI) and why is it a problem in channel communication?

Intersymbol interference is a phenomenon in which symbols or data bits transmitted over a channel overlap with each other, leading to errors in the received data. This is a problem because it can cause a loss of information and decrease the overall reliability of the communication system.

2. How is ISI simulated in communication systems?

ISI can be simulated using mathematical models and computer simulations. These simulations take into account factors such as channel characteristics, modulation techniques, and noise to accurately replicate the effects of ISI on a communication system.

3. What are some common methods used to mitigate ISI in communication systems?

Some common methods to mitigate ISI include equalization techniques, such as linear equalization and decision feedback equalization, which aim to reduce the effects of ISI in the received signal. Other methods include adaptive modulation and coding, which adjusts the modulation and coding scheme based on the channel conditions.

4. How does channel bandwidth affect ISI?

The bandwidth of the channel can significantly affect the severity of ISI. A wider bandwidth allows for more symbols to be transmitted simultaneously, reducing the likelihood of overlap and ISI. On the other hand, a narrow bandwidth can increase the likelihood of ISI and require more advanced equalization techniques to mitigate it.

5. How can ISI be measured in a communication system?

ISI can be measured using metrics such as bit error rate (BER) and eye diagrams. BER measures the number of bit errors in the received signal, while eye diagrams show the signal's quality and ISI effects by plotting the received signal's amplitude over time. These measurements can help evaluate the performance of a communication system and identify areas for improvement.

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