With 5G’s support for diverse radio bands and different deployment modes, e.g., standalone (SA) vs. non-standalone (NSA), mobility management - especially the handover process - becomes far more complex. Measurement studies have shown that frequent handovers cause wild fluctuations in 5G throughput, and worst, service outages. Through a cross-country (6,200 km+) driving trip, we conduct in-depth measurements to study the current 5G mobility management practices adopted by three major U.S. carriers. Using this rich dataset, we carry out a systematic analysis to uncover the handover mechanisms employed by 5G carriers, and compare them along several dimensions such as (4G vs. 5G) radio technologies, radio (low-, mid- & high-)bands, and deployment (SA vs. NSA) modes. We further quantify the impact of mobility on application performance, power consumption, and signaling overheads. We identify key challenges facing today’s NSA 5G deployments which result in unnecessary handovers and reduced coverage. Finally, we design a holistic handover prediction system Prognos and demonstrate its ability to improve QoE for two 5G applications 16K panoramic VoD and realtime volumetric video streaming. We have released the artifacts of our study at https://github.com/SIGCOMM22-5GMobility/artifact.
@inproceedings{hassan2022vivisecting,author={Hassan, Ahmad and Narayanan, Arvind and Zhang, Anlan and Ye, Wei and Zhu, Ruiyang and Jin, Shuowei and Carpenter, Jason and Mao, Z. Morley and Qian, Feng and Zhang, Zhi-Li},title={Vivisecting Mobility Management in 5G Cellular Networks},year={2022},isbn={9781450394208},publisher={Association for Computing Machinery},address={New York, NY, USA},url={https://doi.org/10.1145/3544216.3544217},doi={10.1145/3544216.3544217},booktitle={Proceedings of the ACM SIGCOMM 2022 Conference},pages={86--100},numpages={15},keywords={coverage, 5G, dataset, energy, handover, mobility, handover prediction, mobility management, network measurement, application performance},location={Amsterdam, Netherlands},series={SIGCOMM '22},abbr={SIGCOMM},selected={true},bibtex_show={true},website={https://github.com/SIGCOMM22-5GMobility/artifact},pdf={vivisectingmobility_sigcomm22.pdf},talk={https://dl.acm.org/doi/10.1145/3544216.3544217},slides={slides-sig22-mobility-public.pptx}}
INFOCOM
A Comparative Measurement Study of Commercial 5G mmWave Deployments
5G-NR is beginning to be widely deployed in the mmWave frequencies in urban areas in the US and around the world. Due to the directional nature of mmWave signal propagation, improving performance of such deployments heavily relies on beam management and deployment configurations. We perform detailed measurements of mmWave 5G deployments by two major commercial 5G operators in the US in two diverse environments: an open field with a baseball park and a downtown urban canyon region, using smartphone-based tools that collect detailed measurements across several layers (PHY, MAC and up) such as beam-specific metrics like signal strength, beam switch times, and throughput per beam. Our measurement analysis shows that the parameters of the two deployments differ in a number of aspects: number of beams used, number of channels aggregated, and density of deployments, which reflect on the throughput performance. Our measurement-driven propagation analysis demonstrates that narrower beams experience a lower path-loss exponent than wider beams, which combined with up to eight frequency channels aggregated on up to eight beams can deliver a peak throughput of 1.2 Gbps at distances greater than 100m.
@inproceedings{narayanan2022mmwave,author={*Narayanan, Arvind and *Rochman, Muhammad Iqbal and Hassan, Ahmad and Firmansyah, Bariq S. and Sathya, Vanlin and Ghosh, Monisha and Qian, Feng and Zhang, Zhi-Li},booktitle={IEEE INFOCOM 2022 - IEEE Conference on Computer Communications},title={A Comparative Measurement Study of Commercial 5G mmWave Deployments},year={2022},pages={800-809},doi={10.1109/INFOCOM48880.2022.9796693},selected={true},bibtex_show={true},abbr={INFOCOM},website={https://5gbeams.umn.edu/},pdf={5Gmmwavebeamanalysis_infocom22.pdf},slides={slides-infocom22-mmwave-public.pptx}}
2021
SIGCOMM
A Variegated Look at 5G in the Wild: Performance, Power, and QoE Implications
Motivated by the rapid deployment of 5G, we carry out an in-depth measurement study of the performance, power consumption, and application quality-of-experience (QoE) of commercial 5G networks in the wild. We examine different 5G carriers, deployment schemes (Non-Standalone, NSA vs. Standalone, SA), radio bands (mmWave and sub 6-GHz), protocol configurations (_e.g._ Radio Resource Control state transitions), mobility patterns (stationary, walking, driving), client devices (_i.e._ User Equipment), and upper-layer applications (file download, video streaming, and web browsing). Our findings reveal key characteristics of commercial 5G in terms of throughput, latency, handover behaviors, radio state transitions, and radio power consumption under the above diverse scenarios, with detailed comparisons to 4G/LTE networks. Furthermore, our study provides key insights into how upper-layer applications should best utilize 5G by balancing the critical tradeoff between performance and energy consumption, as well as by taking into account the availability of both network and computation resources. We have released the datasets and tools of our study at https://github.com/SIGCOMM21-5G/artifact.
@inproceedings{narayanan2021variegated,author={*Narayanan, Arvind and *Zhang, Xumiao and Zhu, Ruiyang and Hassan, Ahmad and Jin, Shuowei and Zhu, Xiao and Zhang, Xiaoxuan and Rybkin, Denis and Yang, Zhengxuan and Mao, Zhuoqing Morley and Qian, Feng and Zhang, Zhi-Li},title={A Variegated Look at 5G in the Wild: Performance, Power, and QoE Implications},year={2021},isbn={9781450383837},publisher={Association for Computing Machinery},address={New York, NY, USA},url={https://doi.org/10.1145/3452296.3472923},doi={10.1145/3452296.3472923},booktitle={Proceedings of the 2021 ACM SIGCOMM 2021 Conference},pages={610--625},numpages={16},keywords={video streaming, mmWave, power characteristics, network measurement, power model, dataset, energy efficiency, latency, 5G},location={Virtual Event, USA},series={SIGCOMM '21},selected={true},bibtex_show={true},abbr={SIGCOMM},code={https://github.com/SIGCOMM21-5G/artifact.git},pdf={avariegatedlookat5g_sigcomm21.pdf},talk={https://dl.acm.org/doi/10.1145/3452296.3472923}}