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