Generate a 1000-Length Binary Random Sequence and Analyze Line Coding Schemes

This task requires completion of the following operations: A. Generate a 1000-length binary random sequence where bit '0' has probability 0.8 and bit '1' has probability 0.2. Implementation can use MATLAB's rand() function with threshold comparison: sequence = rand(1,1000) > 0.8; B. Apply Return-to-Zero AMI (Alternate Mark Inversion) encoding to the generated data. The pulse width should be 50% of symbol width with sampling rate 8 times the symbol rate. Plot waveforms for the first 20 symbols along with displaying the corresponding source sequence. The AMI algorithm alternates polarity for '1's while '0's remain zero, with return-to-zero pulse shaping. C. Replace AMI with HDB3 (High-Density Bipolar 3) coding and plot waveforms for the first 20 symbols. HDB3 encoding replaces sequences of four zeros with special bipolar violations to maintain DC balance. D. Implement Miller coding instead of AMI and visualize the first 20 symbols' waveforms. Miller code features transitions at bit boundaries and mid-bit transitions for '1's. E. Perform power spectrum estimation for all 1000 symbols using Welch's method or periodogram approach, then plot the power spectral density graphs for comparative analysis. F. Modify the probability of source bit '0' and observe corresponding changes in AMI code's power spectrum characteristics to analyze probability-dependent spectral properties. These operations will help deepen understanding of different line coding methodologies and their performance characteristics under various conditions, with practical implementation insights for digital communications systems.