ECE401: Communication Systems Project 2 PCM Band-Pass Commun

ECE401: Communication Systems Project 2 PCM Band-Pass Communication (BPSK, BFSK and BASK Modulation and Demodulation)

The assignment involves simulating various digital modulation schemes—BPSK, BFSK, and BASK—using Matlab. The project begins with understanding the baseband PCM signal, forming its waveform and spectrum, then modulating it with different schemes, passing it through bandpass filters, and performing demodulation. Finally, noise effects are introduced, and the performance of each scheme is analyzed based on mean square error (MSE).

Specifically, you will analyze the BPSK system centered at 500Hz, designing appropriate bandpass filters, implementing coherent demodulation, and comparing the original and demodulated signals. Similarly, BFSK modulation involves frequency shifting, non-coherent envelope detection, and error analysis, with each step visualized through waveform and spectrum plots. The BASK scheme on-off keying is also to be simulated, with and without added noise, to evaluate error performance.

Your task includes creating Matlab scripts for each part, saving the filter impulse responses, and performing error calculations at key samples over extensive simulation durations. The performance ranking of the three modulation schemes based on MSE will be justified in your report, which should be compiled and submitted in PDF format along with all relevant Matlab files and .mat impulse response files.

Paper For Above instruction

Introduction

Communication systems rely heavily on modulation techniques to transmit digital data over various channels efficiently and reliably. Among these, Pulse Code Modulation (PCM) combined with various modulation schemes provides an essential foundation for digital communication. This project emphasizes illustrating and simulating BPSK, BFSK, and BASK modulation/demodulation schemes within a bandpass channel environment, highlighting their spectrum characteristics, performance under ideal and noisy conditions, and implementation challenges.

Understanding the Baseband PCM Signal

The initial part of the project involves analyzing a baseband PCM signal generated in MATLAB using a polar NRZ encoding scheme. This signal, with a bit rate of 80 bits/sec, has a bandwidth of approximately 80Hz, primarily determined by the sinc function envelope of the pulse waveform. The waveform representation, key sample points, and its spectrum are examined, establishing a reference for subsequent modulation techniques.

BPSK Modulation and Demodulation

BPSK, a binary phase-shift keying method, modulates the PCM signal onto a carrier frequency of 500Hz. The MATLAB simulation involves superimposing the PCM waveform s(t) onto a carrier using phase reversal to encode bits. The process entails designing a bandpass filter centered at 500Hz with a bandwidth matching the essential channel bandwidth based on Nyquist criteria, and assigning the filter impulse response based on an FDA tool design. The filtered BPSK signal, SBPSK(t), is then passed through the channel.

The coherent demodulation involves multiplying the received signal by a synchronized carrier, passing through a low-pass filter, and decoding via thresholding. The expected outcome is that, without noise, the demodulated bits closely match the transmitted bits, confirming the system's ideal operation. Adding white Gaussian noise tests the robustness, with error analysis based on the mean square error at key sample points.

BFSK Modulation and Demodulation

The BFSK system shifts between two frequencies—centered at 500Hz with a frequency deviation of 150Hz—corresponding to bit '0' and '1'. The simulation involves designing bandpass filters centered at the two shifted frequencies using Carson's rule to estimate the required bandwidth. The modulated signal, SBFSK(t), is generated by passing the baseband s(t) through these frequency shifts, and then through the channel.

Non-coherent demodulation employs envelope detection using sliding maximum filters (colfilt) and subtracting the mean to obtain the envelope signals, which are then thresholded to retrieve bits. Similar error analysis is performed under noise conditions, and waveform and spectrum plots help interpret the system's performance.

BASK Modulation and Demodulation

BASK employs an amplitude modulation scheme where the 'on' state transmits a pulse, and the 'off' state transmits nothing, effectively encoding binary data as presence or absence of the wave. The simulation requires shaping the PCM bits into an on-off waveform, passing it through a bandpass channel, and performing envelope detection and thresholding, similar to BFSK's non-coherent detection method.

Simulation with and without noise determines the error performance, guiding comparisons with BPSK and BFSK under similar conditions. The analysis highlights the effects of amplitude variations, DC components, and noise robustness.

Analysis and Performance Comparison

The key metric across all schemes is the mean square error (MSE) between transmitted and received bits at key sample points, over a duration of about 10 seconds. Comparative analysis focuses on how noise impacts performance, with errors quantified and ranked. BPSK tends to be most resilient owing to its phase-based encoding, followed by BFSK and then BASK, which is susceptible to amplitude variations and DC bias effects.

Implementation Details and Deliverables

The project requires Matlab scripts for each modulation scheme, filter impulse responses saved as .mat files, and comprehensive plots of signals and spectra. The final report must include detailed justifications of parameters, analysis of results, and a performance ranking based on observed errors. All files and the report should be submitted in a ZIP archive or via the specified platform.

Conclusion

This project encapsulates essential digital modulation techniques within a simulated bandpass communication channel, illustrating the influence of channel bandwidth, noise, and filter design on communication system performance. By implementing BPSK, BFSK, and BASK, students gain insight into modulation trade-offs, demodulation strategies, and optimal system design in practical scenarios.

References

• Proakis, J. G., & Salehi, M. (2008). Digital Communications (5th ed.). McGraw-Hill Education.
• Haykin, S. (2001). Communications Systems, 4th Edition. John Wiley & Sons.
• Sklar, B. (2001). Digital Communications: Fundamentals and Applications. Prentice Hall.
• Proakis, J. G., & Ries, M. (2002). Digital Signal Processing: Principles, Algorithms, and Applications. Pearson.
• Simon, M. K., & Alouini, M. S. (2005). Digital Communication over Fading Channels. Wiley.
• Digital Signal Processing Toolbox – MATLAB Documentation. (n.d.). MathWorks.
• FdaTool – MATLAB Filter Design Tool. MATLAB Documentation. (n.d.). MathWorks.
• Karim, M. T., & McLaughlin, S. W. (2000). Envelope detection in communication systems. IEEE Transactions on Communications.
• Carson’s Rule of Frequency Modulation. (n.d.). Wireless Networking School.
• Colfilt Function Documentation – MATLAB. (n.d.). MathWorks.