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Analog RF Computing: A New Paradigm for Energy-Efficient Edge AI Over MU-MIMO Systems
Modern edge devices increasingly rely on neural networks for intelligent applications. However, conventional digital computing-based edge inference requires substantial memory and energy consumption. In analog radio frequency (RF) computing, a base station (BS) encodes the weights of the neural netw
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