Difference between revisions of "Forward error-correction ASIC using GRAND"
From iis-projects
| Line 1: | Line 1: | ||
| − | [[File:Grand. | + | [[File:Grand.png|380px|thumb|A MIMO basestation mitigates an ongoing jamming attack while continuing to serve the legitimate user equipments. The signal processing for this takes place in a custom ASIC.]] |
==Short Description== | ==Short Description== | ||
Revision as of 18:12, 27 May 2022
Contents
Short Description
Guessing random additive noise decoding (GRAND) is an emerging maximum likelihood (ML) decoding technique. The idea of GRAND is to efficiently guess the noise that corrupted a transmitted codeword. The goal of this project is to develop a more effective GRAND algorithm that improves the guessing accuracy, implement an architecture, and test it on an FPGA.
Status: Available
- Looking for 1-2 Semester/Master students
- Contact: Darja Nonaca
Prerequisites
- Matlab or Python
- VLSI I-II
- Familiarity with the basics of digital communication is recommended but not strictly required
Character
- 50% MATLAB simulation
- 50% VLSI Implementation and Verification
