Channel equalization is a useful technique which is commonly used to combat the distortive channel effects and effectively reduce ISI hence maximizes the probability of correct decision. The equalizers can be classified into different types: linear, decision feedback type and adaptive. The project is to construct a system model with mean-square error equalization and discuss the advantages and disadvantages introduced by the technique.
To better understand the equalization technique and its principle for improvement of digital communications system. Analyze the system BER performance with/without MSE Equalizer.
Requirement ( Project to do list)
1) System model using BPSK modulation, Rician fading channel, and AWGN and plot out BER graph without MMSE equalizer
2) Same system model with equalizer and plot out BER graph (this graph should have better BER performance over number 1)
3) All clear figures and matlab codes are required for project report. Project need to have about 70-90 pages. Report needs to include
- Using Matlab, Breakdown individual figure(plot) of BPSK modulation, Racian Fading model, MMSE equalizer, BPSK demodulation whichever is possible
- BER comparison graphs
- MMSE algorithms and explanations
- Advantages and disadvantages introduced by the technique (MMSE)
- Its principle for improvement of digital communications system, the suggestions and explanations on how we can improve
Project deadline is end of October
What I have done so far
Item (1). Please verify whether what I have done so far is correct and can continue for items 2, 3 and [url removed, login to view] make necessary changes of my Matlab code whenever required. I'll send the matlab code after choosing the successful bid.