Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Exploiting On-Orbit Characteristics for Joint Parameter and Channel Tracking in LEO Satellite Communications

Chenlan Lin, Xiaoming Chen, Zhaoyang Zhang

TL;DR

Simulation results show that compared to the rough estimation methods, the proposed joint parameter and channel tracking (JPCT) algorithm performs much better in the estimation of state-dependent parameters.

Abstract

In high-dynamic low earth orbit (LEO) satellite communication (SATCOM) systems, frequent channel state information (CSI) acquisition consumes a large number of pilots, which is intolerable in resource-limited SATCOM systems. To tackle this problem, we propose to track the state-dependent parameters including Doppler shift and channel angles, by exploiting the physical and approximate on-orbit mobility characteristics for LEO satellite and ground users (GUs), respectively. As a prerequisite for tracking, we formulate the state evolution models for kinematic (state) parameters of both satellite and GUs, along with the measurement models that describe the relationship between the state-dependent parameters and states. Then the rough estimation of state-dependent parameters is initially conducted, which is used as the measurement results in the subsequent state tracking. Concurrently, the measurement error covariance is predicted based on the formulated Cram$\acute{\text{e}}$r-Rao lower bound (CRLB). Finally, with the extended Kalman filter (EKF)-based state tracking as the bridge, the Doppler shift and channel angles can be further updated and the CSI can also be acquired. Simulation results show that compared to the rough estimation methods, the proposed joint parameter and channel tracking (JPCT) algorithm performs much better in the estimation of state-dependent parameters. Moreover, as to the CSI acquisition, the proposed algorithm can utilize a shorter pilot sequence than benchmark methods under a given estimation accuracy.

Exploiting On-Orbit Characteristics for Joint Parameter and Channel Tracking in LEO Satellite Communications

TL;DR

Simulation results show that compared to the rough estimation methods, the proposed joint parameter and channel tracking (JPCT) algorithm performs much better in the estimation of state-dependent parameters.

Abstract

In high-dynamic low earth orbit (LEO) satellite communication (SATCOM) systems, frequent channel state information (CSI) acquisition consumes a large number of pilots, which is intolerable in resource-limited SATCOM systems. To tackle this problem, we propose to track the state-dependent parameters including Doppler shift and channel angles, by exploiting the physical and approximate on-orbit mobility characteristics for LEO satellite and ground users (GUs), respectively. As a prerequisite for tracking, we formulate the state evolution models for kinematic (state) parameters of both satellite and GUs, along with the measurement models that describe the relationship between the state-dependent parameters and states. Then the rough estimation of state-dependent parameters is initially conducted, which is used as the measurement results in the subsequent state tracking. Concurrently, the measurement error covariance is predicted based on the formulated Cramr-Rao lower bound (CRLB). Finally, with the extended Kalman filter (EKF)-based state tracking as the bridge, the Doppler shift and channel angles can be further updated and the CSI can also be acquired. Simulation results show that compared to the rough estimation methods, the proposed joint parameter and channel tracking (JPCT) algorithm performs much better in the estimation of state-dependent parameters. Moreover, as to the CSI acquisition, the proposed algorithm can utilize a shorter pilot sequence than benchmark methods under a given estimation accuracy.

Paper Structure

This paper contains 21 sections, 58 equations, 7 figures, 2 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Frame Structure
  4. Channel Model
  5. Signal Model
  6. Formulation of Tracking Models
  7. Coordinate System and Assumptions
  8. State Evolution Model
  9. Measurement Model
  10. Design of Joint Parameter and Channel Tracking Algorithm
  11. Rough Doppler Estimation
  12. Rough Angle Estimation
  13. Measurement Error Prediction Based on CRLB
  14. CRLB for Rough Doppler Estimation
  15. CRLB for Rough Angle Estimation
  16. ...and 6 more sections

Figures (7)

  • Figure 1: Illustration and transceiver architecture of a multi-user LEO SATCOM system.
  • Figure 2: Frame structure of the proposed joint parameter and channel tracking algorithm.
  • Figure 3: Geometric relationship diagram for LEO satellite communication based on the ECF coordinate system: (a) coordinate system rotation; (b) rotation on the satellite orbit plane; and (c) presentation for measurement model formulation.
  • Figure 4: RMSE performance against SNRs for: (a) Doppler shift; (b) elevation angle; and (c) azimuth angle.
  • Figure 5: Analysis on effects of state evolution noise with $\text{SNR} = -10$ dB: (a) RMSE performance against $\sigma_v$ with $\sigma_\text{U}\in\{5,20\}$ for Doppler shift; RMSE performance against $\sigma_\text{U}$ with $\sigma_v \in \{1, 4\}$ for: (b) elevation angle; and (c) azimuth angle.
  • ...and 2 more figures

Theorems & Definitions (1)

  • Remark 1