NL-COMM: Demonstrating Gains of Non-Linear Processing in Open-RAN Ecosystem
Chathura Jayawardena, Marcin Filo, George N. Katsaros, Konstantinos, Nikitopoulos

TL;DR
This paper demonstrates a real-time, software-based non-linear processing framework for MU-MIMO in Open-RAN, achieving higher throughput and connectivity with fewer antennas, and integrating rate adaptation for practical deployment.
Contribution
It introduces NL-COMM, a novel non-linear processing framework that operates in real-time within a standard-compliant Open-RAN ecosystem, including the first practical rate adaptation for NL processing.
Findings
Supports four MIMO streams with a single antenna
Halves the number of antennas needed without performance loss
Meets 5G-NR real-time latency requirements
Abstract
Multi-user multiple-input, multiple-output (MU-MIMO) designs can substantially increase wireless systems' achievable throughput and connectivity capabilities. However, existing MU-MIMO deployments typically utilize linear processing techniques that, despite their practical benefits, such as low computational complexity and easy integrability, can leave much of the available throughput and connectivity gains unexploited. They typically require many power-intensive antennas and RF chains to support a smaller number of MIMO streams, even when the transmitted information streams are of low rate. Alternatively, non-linear (NL) processing methods can maximize the capabilities of the MIMO channel. Despite their potential, traditional NL methods are challenged by high computational complexity and processing latency, making them impractical for real-time applications, especially in…
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Taxonomy
TopicsNeural Networks and Applications · Neural dynamics and brain function · Photoreceptor and optogenetics research
