Development and implementation of signal processing

Assignment Detail:- ME606 Digital Signal Processing - Melbourne Institute of Technology Assignment: Understanding the role of digital signal processing in state-of-the-art communications technologies and utilizing MATLAB or Python to simulate LTI systems for frequency/time domain analysis Learning Outcome 1: Development and implementation of signal processing algorithms in Matlab or Python Learning Outcome 2: In-depth design of digital filters Learning Outcome 3: Understand the design of multirate signal processing and their applications Learning Outcome 4: Implementation and applications of DFT/FFT Assignment Description This assignment focuses on the application of digital signal processing -DSP- tools and methods in solving practical problems in modern wireless communications- OFDM -orthogonal frequency division multiplexing- is one of the most important transmission methods in modern wireless communications- So, students are expected to possess an expertise in it- Programming in languages such as MATLAB and Python is another must have of communications engineers- The ability to understand and apply algorithms to the design and analysis of communications systems is another desirable skill, and so is R&D- The assignment motivates students to acquire these four skills in an integrated manner- This unit and its constituents build upon the knowledge acquired in ME502- This assignment is a foundation to Assignment 2, so a proper understanding of it is essential- This assignment requires students to review the literature on channel estimation and equalisation of wireless channels using OFDM transmission- Channel estimation and equalisation is jointly one of the most important applications of digital signal processing -DSP- algorithms and tools in wireless communications- These are needed for the estimation and decoding of transmitted data at the receiver- While completing this task, you will demonstrate the application of DSP tools studied in this unit, such as convolution, DFT, time shifting -delay or advance-, scaling, averaging and scaling- Wireless channels are liable to multipath signal propagation which induce frequency-selective fading into the transmitted signal- Such channels may also experience time-selective fading if the Doppler spread/shift is high- Channels for high-speed trains, drones, high data rate applications -as in e-g- LTE- Advanced and 5G-, underwater acoustic applications, and aeronautical communications are liable to high Doppler spreads owing to the high relative movements between the transmitting and the receiving antennas or the clutter around them- Channels liable to both frequency selectivity and time selectivity are referred to as doubly-selective channels- OFDM transmission has been adopted to counter frequency selectivity in wireless channels- However, OFDM is useful only if the orthogonality between its subcarriers is maintained- Wireless technologies using OFDM transmissions -e-g- LTE and 5G- presume that the wireless channel's variations within an OFDM symbol duration is negligible- However, this is not the case on doubly-selective channels due to the high Doppler spread, resulting in intercarrier interference -ICI- within an OFDM symbol- Algorithms estimating and equalising doubly- selective channels are much more involved than those for singly-selective channels- Your main task is to study and simulate using MATLAB or Python an article on an algorithm to estimate doubly-selective channels for the purpose of equalisation to reduce bit error rate- 1- Download from the Moodle site for this assignment the article named "Article_for_assignment_01" 2- Study and critique the paper 3- Using either MATLAB or Python, simulate the algorithm proposed in the article to verify the results in the article- Your study and report should include the following:a- An algorithm for estimating the length Lc of the channel's impulse response- You will need to search on Google scholar and/or library for useful material- Clearly indicate the value of Lc used in your simulation-b- Select one basis expansion model -BEM- and clearly justify your choice- The common BEM include complex exponential BEM -CE-BEM-, generalised CE-BEM -GCE-BEM-, polynomial BEM -P-BEM- and discrete prolate spheroidal sequences BEM -DPSS-BEM--c- Your estimated carrier frequency offset -CFO- and OFDM symbol timing offset -STO--d- Assume maximum relative velocity between the transmitting and receiving antennas of 350 km/h and estimate the maximum Doppler spread needed to estimate the number, Q, of BEM basis functions- 4- Your submission should be a single pdf document and should include your MATLAB or Python script as the appendix- In your simulation assume the following parameters:1- N=601 -maximum number of subcarriers in each OFDM symbol-- This is equivalent to a system using 10 MHz with 15-kHz subcarrier spacing-2- 15-kHz subcarrier spacing3- Fs=30-72 MHz sampling frequency4- QPSK, 16-QAM or 64-QAM baseband modulation -those you studied in ME502- Your submission should follow a structure like the article being simulated- Specifically, it should be structured into the sections:a- Titleb- Abstractc- Introductiond- Analysise- Simulation results and discussionsf- References Article - Joint Maximum Likelihood Timing, Frequency Offset, and Doubly Selective Channel Estimation for OFDM Systems by Hamed Abdzadeh-Ziabari, Wei-Ping Zhu and M-N-S-Swamy Attachment:- Digital Signal Processing-rar

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