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[[File:IIP_par_reduction.png|600px|thumb|Peak-to-average power reduction (PAR). Left: signal without PAR; right with PAR]]
 
==Short Description==
 
==Short Description==
  
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===Status: Available ===
 
===Status: Available ===
 
: Looking for 1-2 Semester/Master students
 
: Looking for 1-2 Semester/Master students
: Contact: [[:User:studer | Christoph Studer]]
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: Contact: [https://ee.ethz.ch/the-department/faculty/professors/person-detail.OTY5ODg=.TGlzdC80MTEsMTA1ODA0MjU5.html Christoph Studer]
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===Prerequisites===
 
===Prerequisites===
: VLSI I
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: For students interested in the theory: Communication Systems (''recommended'')
: VLSI II (''recommended'')
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: For students interested in the implementation: VLSI I, VLSI II (''recommended'')
: Communication Systems (''recommended'')
 
 
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===Status: Completed ===
 
===Status: Completed ===
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: Supervision: [[:User:Mluisier | Mathieu Luisier]]
 
: Supervision: [[:User:Mluisier | Mathieu Luisier]]
 
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===Character===
 
===Character===
 
: 50% Theory
 
: 50% Theory
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==Results==  
 
==Results==  
  
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==Links==
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[[Category:Available]]
 
[[Category:IIP]]
 
[[Category:IIP]]
 
[[Category:IIP_5G]]
 
[[Category:IIP_5G]]
 
==Links==
 
 
  
 
[[#top|↑ top]]
 
[[#top|↑ top]]

Latest revision as of 13:16, 24 November 2021

Peak-to-average power reduction (PAR). Left: signal without PAR; right with PAR

Short Description

Data transmission over frequency-selective channels using orthogonal frequency-division multiplexing (OFDM) suffers from high peak-to-average power ratio (PAR). The high dynamic range of OFDM signals is further aggravated in multi-antenna or massive MIMO systems where hundreds of parallel OFDM stream must be transmitted wirelessly. This project aims at investigating new methods that reduce the PAR in massive MIMO-OFDM systems. The project can be either fully theoretical, half theory and half implementation, or purely VLSI implementation based. The tools to be learned in this project are numerical (convex) optimization and deep unfolding, a recent paradigm to tune algorithm parameters using deep learning frameworks.

Status: Available

Looking for 1-2 Semester/Master students
Contact: Christoph Studer

Prerequisites

For students interested in the theory: Communication Systems (recommended)
For students interested in the implementation: VLSI I, VLSI II (recommended)

Character

50% Theory
50% VLSI Design

Professor

Christoph Studer

↑ top

Detailed Task Description

Goals

Practical Details

Results

Links

↑ top