Search arXiv⌕ Search

arXiv · 2610.35649

RLNC vs Reed-Solomon in Satellite Channels: Crossover Analysis and the Bridging Property

Abstract

Satellite communication systems are increasingly relied upon for connectivity in remote areas and are expected to play a pivotal role in 6G networks, operating under high round-trip times and packet loss where forward error correction is essential. This work evaluates Reed-Solomon (RS) coding, Random Linear Network Coding (RLNC), and a combined RS+RLNC hybrid over a three-hop satellite channel whose loss statistics are derived from orbital geometry and link-budget calculations rather than assumed, comparing RS and RLNC at matched code rates of 0.800. The central finding is the \emph{bridging property} of RLNC: every RS code rate collapses above a crossover threshold $p^*$, while RLNC operates continuously through all failure regions with overhead growing as $1/(1-p)$. At rate~0.800, $p^* \approx 0.21$. Under the derived satcom channel with mean burst duration 166~minutes, RS$(255,204)$ is impractical despite an average loss rate of 1%, while RLNC requires 15.5~Mbit to recover all 1000 packets. An RS+RLNC hybrid reduces overhead by 19% relative to pure RLNC at BER$=10^{-3}$. To the authors' knowledge, this is the first analytical derivation of the rate-normalised crossover $p^*$ between RS and RLNC and the first experimental confirmation of the bridging property under a physically derived satellite channel model.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Angeline Szczepanski, Vipindev Adat Vasudevan. 2026-10-26. RLNC vs Reed-Solomon in Satellite Channels: Crossover Analysis and the Bridging Property. https://arxiv.org/abs/2610.35649

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Can We Trust AI in 6G? Verifiable and Auditable AI-Driven Trustworthy Wireless Networks

Mobile network operators are increasingly exploring the use of artificial intelligence (AI) to automate network tasks such as cell selection and mobility management. Current assurance methods for these AI functions are forms of output testing. They check what a function decides, but they cannot show why it decided that way, and two functions can pass the same tests for different reasons. In this paper, we propose mechanistic auditing, which inspects the internal features of an AI function and checks them against machine-verifiable 3GPP specifications. We set out a three-step auditing principle that locates protocol-relevant features, verifies whether decisions depend on them, and audits each decision against them. We then present an audit-native network architecture. In this architecture, a dedicated verification agent certifies each AI function before deployment and audits its decisions during operation. In a case study on a language model for LTE signalling, we find internal features that carry the 3GPP handover concepts. Removing them lowers the model's accuracy on handover tasks from 96% to 0%, while removing the same number of random features changes its accuracy by less than two points. An audit of a handover decision can therefore check whether these features are active when the model makes that decision. We also discuss the open challenges that remain before mechanistic auditing can enter telecommunications practice and standardisation.

cs.NI↗

Efficient Co-simulator Integration with Application to Smart Grids

The evolution of the electric power grid towards a ``smart grid'' is an example of an emerging large-scale cyber-physical system. To study the potential of cyberattacks or other sources of extreme events, high-fidelity co-simulation is one of the few realistic strategies. In this work, we demonstrate a practical and high-performance co-simulation strategy for smart grids, which provides lessons about co-simulation integration that can be carried over to other cyber-physical systems. Specifically, we present a co-simulation platform based on the Mosaik framework that integrates several federates including OpenDSS for power flow, a refined NS-3 for communication networks, and custom Python-based simulators for on-load tap changer control, distributed state estimation, and data collection. We compare synchronization strategies -- exhaustive lock-step time advancement versus an optimized event-driven approach that exploits lower-bound time stamps (LBTS) and next-event prediction -- and introduce targeted refinements to NS-3 event handling and relevance filtering of internal events. Performance is evaluated on two standard IEEE benchmark systems: the 13-node test feeder with tap-changer voltage regulation and a large-scale 33-bus system augmented with 32 European low-voltage feeders (1,793 nodes total) performing distributed state estimation with thousands of phasors and smart meters. Experimental results demonstrate that the refined event-based synchronization that uses LBTS-based NS-3 event filtering reduces execution time by up to 50\% over non-filtered LBTS, and more than 4$\times$ in the tap control scenario compared to naïve lock-step methods, while strictly preserving temporal correctness and simulation accuracy.

cs.NI↗

Movable Antennas Enabled Wireless Powered Networks: Principles and Technologies

As an emerging framework, movable antenna (MA)-enabled wireless powered networks (WPNs) have attracted growing attention. WPNs integrate wireless communication and energy transfer. MA can dynamically adjust the position of antenna units by introducing additional spatial degrees of freedom, so as to make full use of channel gain, optimize the effect of energy beamforming, and further improve the performance of WPNs. In this article, we first classify the implementations of MA by driving architectures, and review the fundamental principles of WPNs. We then highlight the key advantages of MA-enabled WPNs in enhancing wireless power transfer efficiency, realizing flexible and adaptive beamforming, and improving system robustness and interference resilience. Furthermore, four representative application scenarios and three key enabling technologies are discussed. A case study is also presented to show the reduction in transmit power brought by MA for WPNs. Finally, we discuss the challenges and future directions of MA-enabled WPNs, aiming to provide reference for future research and practice.

cs.NI↗