EGB 242 : Individual Assignment Brisbane Premiere

Introduction

Congratulations on securing a summer internship at BASA, Brisbane’s premiere (and only) space agency. While this is a great achievement, the launch date of the MARS-242 mission is approaching quickly.

This mission will:

• Deliver astronauts into orbit around Mars in preparation for permanent residence.

• Land a rover onto the Martian surface to capture photographs of the proposed settlement location.

To ensure communication between astronauts, their scientific instruments, and mission control, a communication system must be designed.

Your first placement involves finalising several components of this communication system and presenting the design process in a detailed report to your supervisor, the Head of Communications Engineering.

The Communication System Overview

Figure 1: The Communication System

• Input: Audio through a microphone at mission control.

• Transmission: Audio sent via a radio transmitter to the spacecraft.

• Reception: Radio receiver on the orbiter recovers the signal.

• Processing: Signal prepared for digitisation using an analog-to-digital converter.

Academic Integrity

BASA insists on strict adherence to academic integrity to ensure:

• Competence and confidence in its engineers’ knowledge.

• Safety of the astronauts.

Section 1: Removing Periodic Noise

After testing the microphone audio at mission control, periodic interference from nearby equipment was observed. This interference can be modelled as an additive noise process.

Your Task: Model the noise using a complex Fourier series and use this approximation to de-noise the signal.

Tasks

1. Record Test Audio

   • Use MATLAB: record242(sid) (sid = student number).

   • Record the provided test message.

   • Save noise function n(t) and file DataA1.mat.

2. Initial Audio Observation

   • Load audio with load DataA1.

   • Play with sound(audio, fs).

   • Comment on audio quality and interference.

3. Plot Audio Signal

   • Create time vector t.

   • Plot audio vs. time and comment.

4. Fourier Series Analysis

   • By hand, evaluate complex Fourier series coefficients.

   • Document n(t) and series expressions (c0, cn).

   • Include hand-work in appendix.

5. MATLAB Coefficients

   • Use −5 ≤ n ≤ 5 harmonics.

   • Generate vector cn in MATLAB.

   • List coefficient values.

6. Noise Approximation

   • Use cn to generate nApprox.

   • Plot noisy audio and approximation.

7. De-Noising Audio

   • Reverse noise process to obtain.

   • Listen and plot results.

   • Compare with corrupted audio.

8. Evaluate Harmonics

   • Is 5 harmonics sufficient?

   • Experiment with different values.

   • Provide qualitative and quantitative justification.

Section 2: Transmitting and Receiving Signals

With clean audio ready, it must be modulated for transmission via the radio transmitter. Modulation shifts the signal to a carrier frequency suitable for radio communication.

Tasks

1. Magnitude Spectrum

   • Plot magnitude spectrum of clean audio.

2. Channel Observation

   • Use MATLAB:

     channelQuiet = channel(sid, zeros(size(t)));

   • Inspect channel before transmission.

3. Carrier Frequency Selection

   • Identify empty frequency band from channelQuiet.

   • State chosen frequency range and centre frequency.

   • Justify selection.

4. Modulation

   • Modulate audio with selected carrier.

5. Simulated Transmission

   • Transmit using:

     output = channel(sid, input);

   • Plot frequency domain of input vs. output.

6. Demodulation

   • Demodulate received signal.

   • Filter with MATLAB’s lowpass function.

   • Store result as audioReceived.

   • Discuss real filter considerations.

7. Other Signals

   • Demodulate and filter other visible signals in channel spectrum.

   • Identify them.

   • Note: revert changes before continuing.

Section 3: Analog-to-Digital Conversion

Astronauts require digital audio signals for distribution onboard. The signal must undergo sampling and quantisation.

Tasks

1. Sampling Rate Selection

   • Choose lowest valid rate from Table 1.

   • Justify selection.

   • Use MATLAB’s resample to create audioResampled.

   Valid Rates: 5512, 8000, 11025, 22050, 44100, 48000, 96000, 192000 Hz

2. Resampled Audio

   • Listen and comment.

3. Quantisation (16 Levels)

   • Quantise with mid-tread or mid-riser.

   • Store as audioQuantised.

   • Plot and comment.

4. Experiment with Levels

   • Use 2, 4, 8, 32 levels.

   • Compare and select suitable value.

5. Bitrate Constraint

   • System must not exceed 90 kbits/s.

   • Discuss design impact and propose alternatives.

Report Guidelines

• Length: 3–5 pages per question (clear and concise).

• Figures/Code: Must be described in text and captioned.

• Integration: Code and plots integrated into main body, not in appendix.

Report Structure

• Title Page (Name, Student ID, Unit Name, Unit Code)

• Introduction

• Solution (Sections 1–3)

• Conclusion

• Reflection

• References (if needed)

• Appendices (hand-work, raw MATLAB code, etc.)

Submission Requirements

Submit the following to Canvas:

1. Report (PDF format)

2. MATLAB file (missionA1.m)

3. Recorded audio (DataA1.mat)

Do not zip files.

After submission:

• Re-download each file.

• Ensure correct and complete version.

Interview (Authenticity Check)

Some students will be randomly selected for an interview:

• Purpose: verify understanding of report and MATLAB code.

• Attendance: compulsory.

• Outcome: grades may be withheld until interview completion.

Example Questions

• Explain purpose of each section of your MATLAB code.

• Describe challenges and solutions during the assignment.

• How would you adapt your solution for new constraints?

Summary of Assessment Requirements

The assessment requires students to design and document a communication system for the MARS-242 mission under the guidance of their academic mentor. The work is divided into three major sections:

1. Noise Removal from Microphone Audio – Identify and remove periodic interference affecting the recorded message by applying Fourier series analysis.

2. Transmission and Reception of Signals – Modulate the cleaned audio onto a carrier frequency, transmit it through a simulated channel, then demodulate and filter it to recover the original message.

3. Analog-to-Digital Conversion – Convert the recovered audio into digital form by choosing an appropriate sampling rate and applying quantisation within bandwidth and bitrate constraints.

Students must present their work in a professional engineering report, integrating explanations, figures, and justifications throughout, along with a short reflection on their learning process.

Step-by-Step Guidance from the Academic Mentor

Step 1: Recording and Noise Removal

The mentor guided the student to begin by recording a short test message and observing the interference from nearby equipment. The waveform was plotted against time to visualise the distortion. Using Fourier series theory, the noise was expressed mathematically, and coefficients were derived to approximate it. The student then subtracted the noise approximation from the original signal to produce a cleaner version. The mentor emphasised checking whether five harmonics were sufficient or if more were needed, teaching the importance of balancing complexity and accuracy.

Step 2: Preparing the Signal for Transmission

Once a clear signal was achieved, the mentor explained how real communication systems require modulation to shift signals into suitable frequency bands. The student inspected the available channel to identify an unused frequency band, then modulated the cleaned signal onto a carrier. After transmitting through the simulated channel, the received waveform was examined in the frequency domain. Demodulation and low-pass filtering were used to isolate the original audio, while the student also explored how to detect and separate other signals present in the channel.

Step 3: Converting to Digital Form

The mentor next introduced the concept of digitisation. The student evaluated valid sampling rates and chose the lowest rate capable of preserving signal quality. The audio was resampled, then quantised using 16 levels, with plots and listening tests performed to note quality changes. The student experimented with different numbers of quantisation levels to find the best trade-off between fidelity and efficiency. Finally, the bitrate restriction of 90 kbps was addressed, with discussion on how sampling rate and quantisation directly influence system design.

Final Outcome and Learning Objectives

By following the mentor’s step-by-step guidance, the student successfully:

• Identified, modelled, and removed periodic noise from an audio signal.

• Understood modulation, transmission, and demodulation in a radio communication system.

• Applied digital conversion techniques including resampling, quantisation, and bitrate analysis.

• Developed skills in visualising, justifying, and documenting engineering processes in a structured report.

The overall outcome was a comprehensive understanding of communication system design, combining theory with practical application. The learning objectives of signal processing, frequency analysis, transmission concepts, and digital conversion were fully achieved, preparing the student for future technical challenges in engineering communication systems.

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