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Conferences > OFC > 2023 > M1F > M1F.3

Implementation of a Robust and Power-Efficient Nonlinear 64-QAM Demapper using In-Memory Computing

Amro Eldebiky, Georg Böcherer, Maximilian Schädler, Stefano Calabrò, Bing Li, and Ulf Schlichtmann

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Abstract

Analog in-memory computing reduces power consumption sacrificing computational accuracy. We implement multiplication-accumulation in resistive RAM accounting for non-idealities (variations, quantization, ADC noise). The floating-point performance is recovered while minimizing power consumption in offline 64-QAM experiments.

© 2023 The Author(s)

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More Like This
Power-Efficient and Robust Nonlinear Demapper for 64QAM using In-Memory Computing

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