Weixiao Meng
Papers
1
Total Citations
27
H-Index
1
About
Weixiao Meng is a leading researcher in wireless communications, with a primary focus on advanced signal processing for massive MIMO systems and next-generation networks. His most-cited work, "Convolutional-Neural-Network-Based Detection Algorithm for Uplink Multiuser Massive MIMO Systems" (2020, 27 citations), addresses a critical challenge for 6G and beyond: managing interference from the explosion of ultrascale intelligent devices like mobile robots and smart cars. By integrating deep learning with traditional detection methods, Meng pioneered a convolutional neural network approach that significantly improves uplink multiuser detection accuracy and efficiency. This contribution is vital for enabling reliable communication in dense, interference-heavy environments. His research bridges the gap between theoretical information theory and practical AI-driven solutions, positioning him at the forefront of 6G development. Meng’s work is particularly notable for its direct applicability to emerging technologies such as autonomous vehicles and the Internet of Things, where robust connectivity is paramount. With his innovative fusion of machine learning and wireless systems, Meng continues to shape the future of ultra-reliable, low-latency communications.
Research Focus
Key Achievements
Top Papers
- 1