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Role of Sensing and Computer Vision in 6G Wireless Communications

Seungnyun Kim, Jihoon Moon, Jinhong Kim, Yongjun Ahn, Donghoon Kim, Sunwoo Kim, Kyuhong Shim, Byonghyo Shim

TL;DR

To demonstrate the efficacy of SVWC, the whole process of SVWC including the sensing dataset collection, DL model training, and execution of realistic wireless tasks are designed including the sensing dataset collection, DL model training, and execution of realistic wireless tasks.

Abstract

Recently, we are witnessing the remarkable progress and widespread adoption of sensing technologies in autonomous driving, robotics, and metaverse. Considering the rapid advancement of computer vision (CV) technology to analyze the sensing information, we anticipate a proliferation of wireless applications exploiting the sensing and CV technologies in 6G. In this article, we provide a holistic overview of the sensing and CV-aided wireless communications (SVWC) framework for 6G. By analyzing the high-resolution sensing information through the powerful CV techniques, SVWC can quickly and accurately understand the wireless environments and then perform the wireless tasks. To demonstrate the efficacy of SVWC, we design the whole process of SVWC including the sensing dataset collection, DL model training, and execution of realistic wireless tasks. From the numerical evaluations on 6G communication scenarios, we show that SVWC achieves considerable performance gains over the conventional 5G systems in terms of positioning accuracy, data rate, and access latency.

Role of Sensing and Computer Vision in 6G Wireless Communications

TL;DR

To demonstrate the efficacy of SVWC, the whole process of SVWC including the sensing dataset collection, DL model training, and execution of realistic wireless tasks are designed including the sensing dataset collection, DL model training, and execution of realistic wireless tasks.

Abstract

Recently, we are witnessing the remarkable progress and widespread adoption of sensing technologies in autonomous driving, robotics, and metaverse. Considering the rapid advancement of computer vision (CV) technology to analyze the sensing information, we anticipate a proliferation of wireless applications exploiting the sensing and CV technologies in 6G. In this article, we provide a holistic overview of the sensing and CV-aided wireless communications (SVWC) framework for 6G. By analyzing the high-resolution sensing information through the powerful CV techniques, SVWC can quickly and accurately understand the wireless environments and then perform the wireless tasks. To demonstrate the efficacy of SVWC, we design the whole process of SVWC including the sensing dataset collection, DL model training, and execution of realistic wireless tasks. From the numerical evaluations on 6G communication scenarios, we show that SVWC achieves considerable performance gains over the conventional 5G systems in terms of positioning accuracy, data rate, and access latency.
Paper Structure (12 sections, 4 figures, 1 table)

This paper contains 12 sections, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Basics of Sensing and Computer Vision
  3. Sensing and Computer Vision-aided Wireless Communications
  4. Sensing and CV-aided Beam Management
  5. Sensing and CV-aided Proactive Cell Association
  6. Sensing and CV-aided Environment-aware Channel Estimation
  7. Sensing and CV-aided Semantic Signal Compression
  8. Sensing and CV-aided Random Access
  9. Simulation Results
  10. Sensing Dataset and Simulation Setup
  11. Simulation Results
  12. Future Works and Conclusion

Figures (4)

  • Figure 1: Comparison of conventional RF transmission-based communication system and SVWC.
  • Figure 3: Illustrations of sensing and CV-aided beam management, cell association, channel estimation, semantic signal compression, and random access.
  • Figure 4: Example of sensing dataset tailored for wireless communications. Two cameras are used to obtain the images of a scene from different viewpoints.
  • Figure 5: (a) Access latency and (b) data rate performance of SVWC.