1. [Publications](/publications)
2. SALAD: Self-Adaptive Link Adaptation
 
 # SALAD: Self-Adaptive Link Adaptation

  ![](/sites/default/files/styles/wide/public/publications/salad_diagram.png?itok=knHwRGq_)

 Adapting the modulation and coding scheme (MCS) to the wireless link quality is critical for maximizing spectral efficiency while ensuring reliability.

We propose SALAD (self-adaptive link adaptation), an algorithm that exclusively leverages ACK/NACK feedback to reliably track the evolution of the signal-to-interference-plus-noise ratio (SINR), achieving high spectral efficiency while keeping the long-term block error rate (BLER) near a desired target.

SALAD infers the SINR by minimizing the cross-entropy loss between received ACK/NACKs and predicted BLER values, with a learning rate that self-adapts online through knowledge distillation. Based on this inference, SALAD selects the MCS via hypothesis testing: if the SINR is likely underestimated, a higher MCS is selected to accelerate link adaptation under improving channel conditions. To prevent BLER drift from its long-term target, SALAD incorporates a feedback control loop that adjusts the instantaneous BLER target.

Over-the-air experiments on a 5G testbed demonstrate that SALAD consistently outperforms the industry-standard outer-loop link adaptation (OLLA). With a single set of parameters, SALAD achieves up to 15% higher throughput and spectral efficiency than multiple OLLA variants across different traffic regimes, while meeting the BLER target.



 ## Authors



Reinhard Wiesmayr (ETH Zürich)

[Lorenzo Maggi](/person/lorenzo-maggi)

[Sebastian Cammerer](/person/sebastian-cammerer)

[Jakob Hoydis](/person/jakob-hoydis)

[Fayçal Aït Aoudia ](/person/faycal-ait-aoudia)

[Alex Keller](/person/alex-keller)

 

 

 ## Publication Date



Tuesday, October 7, 2025

 

 ## Published in



[arXiv](https://arxiv.org/pdf/2510.05784)

 

 ## Research Area



[Telecommunications](/research-area/telecommunications)