In this work, we tackle the problem of bandwidth estimation (BWE) for real-time communication systems through expert personalization. While expert heuristic-based methods have been widely adopted, tailoring these methods for each and every end user environment is cumbersome due to the level of domain expertise and manual effort required to adjust the carefully tuned heuristic parameters. Thus. we propose Merlin, a data-driven solution to BWE that harnesses expert demonstrations from prior heuristic-based methods to extract an expert BWE policy. The extracted policy can then be finetuned to end user network conditions to improve user quality of experience (QoE). In real-world videoconferencing calls, Merlin matches our expert's policy with no statistically significant movements in terms of objective QoE metrics. Additionally, we show that personalizing Merlin's control policy is possible through a small number of online data-driven parameter updates.

翻译：本研究通过专家个性化方法解决实时通信系统中的带宽估计问题。尽管基于专家启发式的方法已被广泛采用，但由于调整精心调优的启发式参数需要领域专业知识和大量人工投入，为每个终端用户环境定制这些方法十分繁琐。为此，我们提出Merlin——一种数据驱动的带宽估计解决方案，该方法利用基于启发式方法的专家示范数据来提取专家带宽估计策略。提取的策略可针对终端用户网络条件进行微调，从而提升用户体验质量。在实际视频会议通话中，Merlin在客观体验质量指标上与专家策略无统计学显著差异。此外，我们证明通过少量在线数据驱动的参数更新，即可实现Merlin控制策略的个性化适配。