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Spectral vs Energy Efficiency in 6G: Impact of the Receiver Front-End

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arxiv 2310.02622 v3 pith:3HICWQUM submitted 2023-10-04 cs.IT eess.SPmath.IT

classification cs.ITeess.SPmath.IT
keywords powerefficiencyenergyinformationtheoryarticledevicefront-end
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This article puts the spotlight on the receiver front-end (RFE), an integral part of any wireless device that information theory typically idealizes into a mere addition of noise. While this idealization was sound in the past, as operating frequencies, bandwidths, and antenna counts rise, a soaring amount of power is required for the RFE to behave accordingly. Containing this surge in power expenditure exposes a harsher behavior on the part of the RFE (more noise, nonlinearities, and coarse quantization), setting up a tradeoff between the spectral efficiency under such nonidealities and the efficiency in the use of energy by the RFE. With the urge for radically better power consumptions and energy efficiencies in 6G, this emerges as an issue on which information theory can cast light at a fundamental level. More broadly, this article advocates the interest of having information theory embrace the device power consumption in its analyses. In turn, this calls for new models and abstractions such as the ones herein put together for the RFE, and for a more holistic perspective.

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  1. Turbo-ICL: In-Context Learning-Based Turbo Equalization

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    A prompt-conditioned neural equalizer that exchanges soft information with an LDPC decoder over turbo iterations improves post-decoding BER in heavily quantized MIMO simulations.

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