LwAMP-Net Lightweight Network-Based AMP Detector is a M.Tech project topic for Electronics & Communication Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
LwAMP-Net Lightweight Network-Based AMP Detector Project Details
| Abstract |
This research project explores the development and evaluation of LwAMP-Net, a lightweight, model-driven deep learning detector optimized for hardware implementation on Field Programmable Gate Arrays (FPGAs) in massive Multiple-Input Multiple-Output (MIMO) systems. Traditional linear detectors suffer from performance degradation in complex channel environments, while optimal maximum likelihood detection is computationally prohibitive. To address these limitations, a modular and multi-mode hardware architecture is analyzed, featuring an outer-product-based dataflow designed to eliminate pipeline stalls and enhance computational parallelism. The architecture incorporates multi-mode processing elements capable of adapting to diverse computation patterns, thereby optimizing resource utilization. The project provides research direction and implementation support for modeling, simulating, and evaluating this lightweight Approximate Message
Passing (AMP) network. Performance evaluation focuses on key metrics such as throughput per Look-Up Table (LUT) slice, resource overhead, and detection accuracy under 128 × 8 MIMO configurations with 16QAM modulation. Through structured guidance, this work assists researchers in analyzing the trade-offs between hardware complexity and signal detection performance in next-generation wireless receivers.
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| Reference Paper |
LwAMP-Net: A Lightweight Network-Based AMP Detector on FPGA for Massive MIMO |
| Domain |
Electronics & Communication Engineering |
| Sub-Domain |
Communication Systems / Wireless Communications / Massive MIMO |
| PDF Download |
Download / View PDF |
| Get Help |
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