Master thesis – Neutral Network Compression Technique for Wireless Communications
Location: Kista, Stockholm
Preferred starting date: Jan. 2025
Extent: 1-2 student, 30hp.
About the company
Founded in 1988, Huawei Technologies is one of the fastest growing telecommunications and network solutions providers in the world. At Huawei Technologies, we look for people who share our vision: to enrich life with communication. We are a leading supplier of next generation telecom networks and currently serve 37 of the world’s top 50 operators. Our people are committed to providing innovative products, services and solutions and understand it as their mission to create long-term value and growth potential for our clients.
The Huawei office in Sweden is the leading overseas R&D office in Huawei, and the Wireless Algorithm group at Huawei Sweden drives innovation for the Huawei Wireless RAN product. We work on both advanced receivers and on Radio Resource Management algorithms, for both LTE and 5G.
Thesis description
In modern wireless communication systems, efficient channel estimation plays a crucial role in ensuring high-quality communication links. However, as networks evolve towards massive MIMO systems and higher frequency bands such as mmWave and THz, the volume of channel state information (CSI) increases significantly, leading to a surge in computation and storage demands.
Deep neural networks (DNNs) have shown exceptional promise in enhancing channel estimation for modern wireless communication systems. These networks can model complex non-linearities in wireless channels and enhance channel estimation compared to traditional algorithms. However, the deployment of DNNs in real-time communication systems is challenged by their large size and high computational demands.
Compression of deep channel measurement model refers to reducing the size of the neural networks by eliminating redundancy in the network’s architecture and parameters, while maintaining or minimally affecting performance. This research aims to explore and develop novel compression techniques for DNNs specifically designed for channel estimation, such as pruning and quantization, to make them more efficient for real-time deployment without sacrificing accuracy.
Qualifications
- Master student in Electrical Engineering, computer science or equivalent.
- A solid theoretical background in areas such as information theory and signal processing.
- Experience in machine learning and AI.
- Good knowledge in simulators.
Contact person
Li Wang
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.
Master thesis – Neutral Network Compression Technique for Wireless Communications
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