MSc Thesis Opportunity: Physics Inspired Wireless Algorithms
Master thesis scope
MIMO detection is the problem of recovering user’s transmitted symbols from received signals at antennas. The detection can be tackled by linear estimators (e.g. LMMSE) which involve matrix inversion, or tackled by more computationally-involved near-optimal algorithms. Recent advances in physics give arise to ideas of how to revised those algorithms. These include new physics-inspired algorithms for classical computers [1,2] and algorithms for new computing hardware (e.g. quantum computing). Part of these algorithms have been experimentally verified for some scenarios in the recent literature [2,3,4,5]. This master thesis project targets the following:
- A unified review of the methods
- More comprehensive experimental study on when the physics-inspired algorithms outperforms the classical baseline in the scope of MIMO detection
- Propose new heuristics that could further speed up the algorithms
[1] Nadiia Chepurko, Kenneth Clarkson, Lior Horesh, Honghao Lin, David Woodruff, “Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra”, Proceedings of the 39th International Conference on Machine Learning, 2022
[2] Minsung Kim, Salvatore Mandrà, Davide Venturelli, Kyle Jamieson, “Physics-Inspired Heuristics for Soft MIMO Detection in 5G New Radio and Beyond”, Proceedings of the 27th Annual International Conference on Mobile Computing and Networking, 2021
[3] Abhishek Kumar Singh, Davide Venturelli, Kyle Jamieson, “A Finite-Range Search Formulation of Maximum Likelihood MIMO Detection for Coherent Ising Machines”, arXiv:2205.05020, under review for IEEE Globecom 2022
[4] Abhishek Kumar Singh, Kyle Jamieson, Davide Venturelli, Peter McMahon, “Ising Machines’ Dynamics and Regularization for Near-Optimal MIMO Detection”, IEEE Transactions on Wireless Communications, 2022
[5] Masaya Norimoto, Ryuhei Mori, Naoki Ishikawa, “Quantum Speedup for Higher-Order Unconstrained Binary Optimization and MIMO Maximum Likelihood Detection”, arXiv:2205.15478, 2022
Qualifications
- Master student in Wireless Communications, Electrical Engineering or equivalent.
- A solid theoretical background in areas such as signal processing or linear algebra.
- Experience in modeling and simulation.
Send your questions to: Gunnar Peters
gunnar.peters@huawei.com
- Department
- Wireless Algorithms
- Locations
- Stockholm
- Remote status
- Hybrid Remote
Stockholm
About Huawei Sweden R&D
Founded in 1987, Huawei Technologies is one of the fastest growing telecommunications and network solutions providers in the world.
In 2000, Huawei established the first overseas R&D office in Sweden. Huawei Technology Sweden is continuously growing and with 300+ R&D engineers located in Stockholm, Gothenburg and Lund we are trailblazing the path to future 5G and beyond with focus on standardization, research and pre-development.
MSc Thesis Opportunity: Physics Inspired Wireless Algorithms
Loading application form
Already working at Huawei Sweden R&D?
Let’s recruit together and find your next colleague.