Adaptive EqualizerSteps:
1. Generate AR process
2. Initialize
3. Update
4. Repeat step 3 for 500 iterations.
5. Repeat steps 1 to 4 for 100 times and compute ensemble
average of
AR(1) ProcessAutoregressive process of order 1 is defined as:
where,'a' is the parameter of AR(1) process'v(n)' is WGN with
variance
Step1: Initialization of Variables
Step2: Generation of Transmitted bernoulli data sequence
Step3: Channel Simulation
Step4: Adaptive LMS Equalizer
Step5: Plotting Results
Simulation Results
A. For Channel 1 - 1. Channel Input Sequence
2 Channel Output
3 Equalizer Output (=0.001)
4 Equalizer Output (zoomed) (=0.001)
5 Ensemble Averaged Mean Square Error (=0.001)
6 LMS Filter Weights(=0.001)
7. Equalizer Output for N=5000(=0.001)
8. Equalizer Output for N=5000 (zoomed) (=0.001)
9. Ensemble Averaged Mean Square Error (N=5000) (=0.001)
10. LMS Filter Weights N=5000,=0.001
11. Equalizer Output for N=5000 (zoomed) (=0.05)
12. Ensemble Averaged Mean Square Error (N=5000) (=0.001)
13. LMS Filter Weights N=5000,=0.05
