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Quasi-Synchronous Random Access for Massive MIMO-Based LEO Satellite Constellations

Keke Ying, Zhen Gao, Sheng Chen, Mingyu Zhou, Dezhi Zheng, Symeon Chatzinotas, Björn Ottersten, H. Vincent Poor

TL;DR

Simulation results verify the effectiveness of the proposed schemes in terms of channel estimation, activity detection, and data detection for quasi-synchronous random access in satellite systems.

Abstract

Low earth orbit (LEO) satellite constellation-enabled communication networks are expected to be an important part of many Internet of Things (IoT) deployments due to their unique advantage of providing seamless global coverage. In this paper, we investigate the random access problem in massive multiple-input multiple-output-based LEO satellite systems, where the multi-satellite cooperative processing mechanism is considered. Specifically, at edge satellite nodes, we conceive a training sequence padded multi-carrier system to overcome the issue of imperfect synchronization, where the training sequence is utilized to detect the devices' activity and estimate their channels. Considering the inherent sparsity of terrestrial-satellite links and the sporadic traffic feature of IoT terminals, we utilize the orthogonal approximate message passing-multiple measurement vector algorithm to estimate the delay coefficients and user terminal activity. To further utilize the structure of the receive array, a two-dimensional estimation of signal parameters via rotational invariance technique is performed for enhancing channel estimation. Finally, at the central server node, we propose a majority voting scheme to enhance activity detection by aggregating backhaul information from multiple satellites. Moreover, multi-satellite cooperative linear data detection and multi-satellite cooperative Bayesian dequantization data detection are proposed to cope with perfect and quantized backhaul, respectively. Simulation results verify the effectiveness of our proposed schemes in terms of channel estimation, activity detection, and data detection for quasi-synchronous random access in satellite systems.

Quasi-Synchronous Random Access for Massive MIMO-Based LEO Satellite Constellations

TL;DR

Simulation results verify the effectiveness of the proposed schemes in terms of channel estimation, activity detection, and data detection for quasi-synchronous random access in satellite systems.

Abstract

Low earth orbit (LEO) satellite constellation-enabled communication networks are expected to be an important part of many Internet of Things (IoT) deployments due to their unique advantage of providing seamless global coverage. In this paper, we investigate the random access problem in massive multiple-input multiple-output-based LEO satellite systems, where the multi-satellite cooperative processing mechanism is considered. Specifically, at edge satellite nodes, we conceive a training sequence padded multi-carrier system to overcome the issue of imperfect synchronization, where the training sequence is utilized to detect the devices' activity and estimate their channels. Considering the inherent sparsity of terrestrial-satellite links and the sporadic traffic feature of IoT terminals, we utilize the orthogonal approximate message passing-multiple measurement vector algorithm to estimate the delay coefficients and user terminal activity. To further utilize the structure of the receive array, a two-dimensional estimation of signal parameters via rotational invariance technique is performed for enhancing channel estimation. Finally, at the central server node, we propose a majority voting scheme to enhance activity detection by aggregating backhaul information from multiple satellites. Moreover, multi-satellite cooperative linear data detection and multi-satellite cooperative Bayesian dequantization data detection are proposed to cope with perfect and quantized backhaul, respectively. Simulation results verify the effectiveness of our proposed schemes in terms of channel estimation, activity detection, and data detection for quasi-synchronous random access in satellite systems.
Paper Structure (30 sections, 58 equations, 16 figures, 3 tables, 4 algorithms)

This paper contains 30 sections, 58 equations, 16 figures, 3 tables, 4 algorithms.

Table of Contents

  1. Introduction
  2. Related Works
  3. Our Contributions
  4. Preliminaries
  5. Processing Framework
  6. System Model
  7. Transmission Procedure
  8. Massive Access Processing at Single Satellite
  9. Signal Formulation of JADCE
  10. OAMP-Based JADCE at Edge Satellite Node
  11. Enhanced AoA Estimation for Channel Reconstruction
  12. 2D-ESPRIT for AoA Estimation
  13. Channel Gain Estimation and Channel Reconstruction
  14. Single Satellite DD Algorithm
  15. Massive Access Processing Based on Multi-Satellite Cooperation
  16. ...and 15 more sections

Figures (16)

  • Figure 1: Schematic diagram of random access in mMIMO-based LEO constellation for MTC.
  • Figure 2: Block diagram of the proposed diversity transmission and receiving scheme.
  • Figure 3: Illustration of the proposed TSP frame structure for LEO satellite-based random access.
  • Figure 4: Example of geographic distribution of UTs and satellites. Three satellites nodes serve as BSs to provide the access service for terrestrial UTs.
  • Figure 5: CDF curve of correlation coefficient $c_{0}$.
  • ...and 11 more figures