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LIU_3D_On_and_Off-Grid_Dynamic_Channel_Tracking_for_Multiple_UAVs_and_Satellite_Communications.pdf (2.09 MB)

3D on and off-grid dynamic channel tracking for multiple UAVs and satellite communications

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journal contribution
posted on 2022-06-10, 15:22 authored by Jiadong Yu, Xiaolan LiuXiaolan Liu, Yue Gao, Xuemin Shen

The space-air-ground integrated network (SAGIN) has drawn increasing attention for its benefits, such as wide coverage, high throughput for 5G and 6G communications. As one of the links, space-air communications between multiple unmanned aerial vehicles (UAVs) and Ka-band orbiting low earth orbit (LEO) satellites face a crucial challenge in tracking the 3D dynamic channel information. This paper exploits a statistical dynamic channel model called the multi-dimensional Markov model (MD-MM), which investigates the more realistic spatial and temporal correlation in the sparse UAVs-satellite channel. Specifically, the spatial and temporal probabilistic relationships of multi-user (MU) hidden support vector, single-user (SU) joint hidden support vector, and SU hidden value vector are investigated. The specific transition probabilities that connect the SU and MU hidden support vector for both azimuth and elevation directions are defined. Moreover, based on the proposed MD-MM, we derive a novel multi-dimensional dynamic turbo approximate message passing (MD-DTAMP) algorithm for tracking the 3D dynamic channel in multiple UAVs systems. Furthermore, we also develop a gradient update scheme to recursively find the azimuth and elevation offset for 3D off-grid estimation. Numerical results verify that the proposed algorithm shows superior 3D channel tracking performance with smaller pilot overhead and comparable complexity.

Funding

GBSense: GHz Bandwidth Sensing from Smart Antennas to Sub-Nyquist Signal Processing

Engineering and Physical Sciences Research Council

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History

School

  • Loughborough University London

Published in

IEEE Transactions on Wireless Communications

Volume

21

Issue

6

Pages

3587 - 3604

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

2021-10-09

Publication date

2021-10-26

Copyright date

2021

ISSN

1536-1276

eISSN

1558-2248

Language

  • en

Depositor

Dr Xiaolan Liu. Deposit date: 9 June 2022

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