Go to DBLP homepageA Deep Dive into Congestion Control and Buffer Management for Fluctuation-Prone 5G-A/6G Links
Abstract: The introduction of the next generations’ mobile communications, 5 G -Advance and $\mathbf{6 G}$ (5G-A/6G), promises boosting data throughput to new dimensions, achieving submillisecond latency, and providing wider coverage. Based on this promise, a great number of previously infeasible high-throughput, real-time, and IoT-based applications, such as high-resolution face recognition and extended reality, are being developed for deployment over 5G-A/6G networks. Such demanding applications assume that ample bandwidth will be available through the utilization of a high-frequency spectrum. However, at high frequencies, radio channels are susceptible to sudden changes in the surrounding conditions, generating highly fluctuating scenarios that directly impact the performance of upperlayer protocols and services. For applications that operate under end-to-end congestion control algorithm (CCA) (e.g., TCP- and QUIC-based applications), extreme fluctuations may generate unwanted behaviors that hurt the throughput and possibly favor non-CCA traffic with unfair results in bandwidth distribution. This paper thoroughly investigates the impact of fluctuating radio access channels on $5 \mathrm{G}-\mathrm{A} / \mathbf{6 G}$ networks. We analyze the performance of various congestion control algorithms, including CUBIC, High-Speed, and BBR, as well as non-CCA traffic, under such conditions. Our evaluation, conducted through realistic simulations, examines the network’s ability to maintain desired service levels amidst fluctuations. Furthermore, we explore the potential of state-of-the-art active queue management and buffer management policies at the gNB to mitigate the negative effects of these fluctuations and enhance overall network performance.
External IDs:dblp:conf/ciot/SandovalCGTB24
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