Understanding Operational 5G: A First Measurement Study on Its Coverage, Performance and Energy Consumption

By Dongzhu Xu, Anfu Zhou, Xinyu Zhang, Guixian Wang, Xi Liu, Congkai An, Yiming Shi, Liang Liu, Huadong Ma. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2020

317 citations recorded by the source corpus.

5G, as a monumental shift in cellular communication technology, holds tremendous potential for spurring innovations across many vertical industries, with its promised multi-Gbps speed, sub-10 ms low latency, and massive connectivity. On the other hand, as 5G has been deployed for only a few months, it is unclear how well and whether 5G can eventually meet its prospects. In this paper, we demystify operational 5G networks through a first-of-its-kind cross-layer measurement study. Our measurement focuses on four major perspectives: (i) Physical layer signal quality, coverage and hand-off performance; (ii) End-to-end throughput and latency; (iii) Quality of experience of 5G's niche applications (e.g., 4K/5.7K panoramic video telephony); (iv) Energy consumption on smartphones. The results reveal that the 5G link itself can approach Gbps throughput, but legacy TCP leads to surprisingly low capacity utilization (< 32%), latency remains too high to support tactile applications and power consumption escalates to 2 - 3x over 4G. Our analysis suggests that the wireline paths, upper-layer protocols, computing and radio hardware architecture need to co-evolve with 5G to form an ecosystem, in order to fully unleash its potential.

Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ac91a3df43413be2c59fb48a67c12e6183a33aa2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

  1. Carlos Bermejo
  2. Tristan Braud
  3. Abhishek Kumar
  4. Zijun Lin
  5. Lin Wang
  6. Dianlei Xu
  7. Lik-Hang Lee
  8. Pan Hui

In Electrical and Electronic Engineering

  1. Pan Hui

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