Researchers have introduced a new algorithm called Joint-Thompson Sampling (Joint-TS) for link adaptation in communication systems. This algorithm models the problem as a multi-armed bandit, where each modulation and coding scheme (MCS) is an arm. Unlike traditional Thompson Sampling, Joint-TS uses a multivariate ordered Beta distribution to account for the inherent ordering of MCS success probabilities, leading to more robust and consistent performance across various scenarios. AI
IMPACT This research could lead to more efficient and reliable communication systems by improving link adaptation strategies.
RANK_REASON The cluster describes a new algorithm proposed in a research paper submitted to arXiv. [lever_c_demoted from research: ic=2 ai=0.4]
- arXiv
- beta distribution
- Joint-Thompson Sampling
- multi-armed bandit
- multivariate ordered Beta distribution
- Thompson sampling
- Upper Confidence Bound
- Hugging Face
- Modulation and Coding (MCS)
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