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Objectives
This course aims to equip students with a solid foundation in wireless communication systems, from fundamental principles to advanced techniques in system simulation, performance analysis, and optimization. Starting with an introduction to wireless system classification, the course covers channel models, including path loss, shadowing, and multipath effects, as well as key concepts like coherence bandwidth and time in both SISO and MIMO channels. In MATLAB-based lab sessions, students will apply theoretical concepts to explore channel capacity, error probabilities, and diversity techniques for mitigating fading effects. Additionally, they will gain hands-on experience with multi-carrier systems, such as OFDM. The course also covers multi-antenna systems (i.e., MIMO) with a focus on multiplexing and diversity gains. Optimization techniques are introduced, including precoding and decoding strategies to maximize system performance. The course concludes with an overview of emerging topics such as AI-enabled 6G, semantic communications, and massive MIMO, giving students a view of future directions in wireless communication.
Prerequisite: Basic knowledge of calculus, linear algebra, probability, digital communications, information theory. Undergraduate level programming skills (e.g., Matlab, or Python, or C, etc.).
Final Exam: Oral discussion on a computer project carried out over one of the topics of the course.
Classroom code (2024-2025): hkzunzh
Lessons: Friday 14.00-19.00. Room 22, S. Pietro in Vincoli. Bring your laptop with Matlab installed on it!
Contents
Introduction and classification of wireless systems.
Wireless Channel models: Path loss models and Shadowing. Statistical multipath channel models. Coherence bandwidth and coherence time, SISO and MIMO channels. Matlab laboratory.
Capacity of Wireless Channels: Capacity in AWGN, Capacity of Flat-Fading Channels, Capacity of Frequency-Selective Channels. Matlab laboratory.
Performance of Wireless Communications: AWGN Channels, Error Probability for linear digital modulations. The effect of Fading. Outage Probability. Average Probability of Error. Diversity: Receiver and Transmitter diversity. Matlab laboratory.
Multi-carrier systems: Orthogonal frequency division multiplexing (OFDM): Modulation and demodulation, ciclic prefix, digital implementation using Discrete Fourier Transform. Synchronization issues. Channel Estimation. Matlab laboratory.
Multi-antenna Wireless Communications: MISO, SIMO e MIMO architectures, Multiplexing and Diversity Gain, Space-time coding, Matlab laboratory.
Optimization of Wireless Communication: Joint Optimization of Precoding and Decoding; Optimization strategies: Min MSE, Max Rate, Min BER; Beamforming. Matlab laboratory.
Emerging Topics: AI-native 6G communications, goal-oriented and semantic communications, Massive MIMO, Federated edge learning and inference.
Textbooks and resources:
[2] Goldsmith, A. (2005). Wireless communications. Cambridge university press.
[3] Tse, D., & Viswanath, P. (2005). Fundamentals of wireless communication. Cambridge university press.
[4] Barbarossa, S. (2005). Multiantenna wireless communications systems. Artech House Publishers.
Last update: 03/11/2024
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