Multiple Satellites Collaboration for Joint Code-aided CFOs and CPOs Estimation

TL;DR

This paper proposes an iterative code-aided algorithm for joint CFO and CPO estimation in multi-satellite LEO communication systems, significantly improving signal coherence and communication reliability under low SNR conditions.

Contribution

It introduces a novel iterative estimation method for CFO and CPO that approaches theoretical performance bounds in satellite collaboration scenarios.

Findings

Algorithm approaches CRLB within 0.4 dB

Enhanced SNR through satellite cooperation

Improved BER performance in low SNR conditions

Abstract

Low Earth Orbit (LEO) satellites are being extensively researched in the development of secure Internet of Remote Things (IoRT). In scenarios with miniaturized terminals, the limited transmission power and long transmission distance often lead to low Signal-to-Noise Ratio (SNR) at the satellite receiver, which degrades communication performance. A solution to address this issue is the utilization of cooperative satellites, which can combine signals received from multiple satellites, thereby significantly improve SNR. However, in order to maximize the combination gain, the signal coherent combining is necessary, which requires the carrier frequency and phase of each receiving signal to be aligned. Under low SNR circumstances, carrier parameter estimation can be a significant challenge, especially for short burst transmission with no training sequence. In order to tackle it, we propose an iterative code-aided estimation algorithm for joint Carrier Frequency Offset (CFO) and Carrier Phase Offset (CPO). The Cram\'er-Rao Lower Bound (CRLB) is suggested as the limit on the parameter estimation performance. Simulation results demonstrate that the proposed algorithm can approach Bit Error Rate (BER) performance bound within 0.4 dB with regards to four-satellite collaboration.