Massive MIMO As Extreme Learning Machine
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This work shows that massive multiple-input multiple-output (MIMO) with low-resolution analog-to-digital converters (ADCs) forms a natural extreme learning machine (ELM), where the massive number of receive antennas act as hidden nodes of the ELM, and the low-resolution ADCs serve as the activation function of the ELM. It is demonstrated that by adding biases to received signals and optimizing the ELM output weights, the system can effectively tackle hardware impairments, e.g., the power amplifier nonlinearity at transmitter side. It is interesting that the low-resolution ADCs can bring benefit to the receiver in handling nonlinear impairments, and the most computation-intensive part of the ELM is naturally accomplished by signal transmission and reception.
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