On Dual Connectivity in 6G Leo Constellations

Dual connectivity (DC) has garnered significant attention in 5G evolution, allowing for enhancing throughput and reliability by leveraging the channel conditions of two paths. However, when the paths exhibit different delays, such as in terrestrial and non-terrestrial integrated networks with multi-orbit topologies or in networks characterized by frequent topology changes, like Low Earth Orbit (LEO) satellite constellations with different elevation angles, traffic delivery may experience packet reordering or triggering congestion control mechanisms. Additionally, real-time traffic may experience packet drops if their arrival exceeds a play-out threshold. Different techniques have been proposed to address these issues, such as packet duplication, packet switching, and network coding for traffic scheduling in DC. However, if not accurately designed, these techniques can lead to resource waste, encoding/decoding delays, and computational overhead, undermining DC’s intended benefits. This paper provides a mathematical framework for calculating the average end-to-end packet loss in case of a loss process modeled with a Discrete Markov Chain - typical of a wireless channel - when combining packet duplication and packet switching or when network coding is employed in DC. Such metrics help derive optimal policies with full knowledge of the underlying loss process to be compared to empirical models learned through Machine Learning algorithms.

💡 Research Summary

The paper investigates the challenges of Dual Connectivity (DC) in the emerging 6G landscape, focusing on Low‑Earth‑Orbit (LEO) satellite constellations that introduce heterogeneous propagation delays and frequent topology changes. Such delay asymmetry leads to packet reordering, increased retransmission timeouts, and, for real‑time services, packet drops when jitter exceeds playback thresholds. The authors first review 3GPP‑defined NTN (Non‑Terrestrial Network) architectures, distinguishing between transparent payload satellites (simple RF relays) and regenerative payloads that host gNB‑DU functions. They discuss how Master‑Node (MN) and Slave‑Node (SN) configurations, Xn/F1 interfaces, and mixed GEO‑LEO links create variable round‑trip times (RTTs) and consequently out‑of‑sequence (OoS) flows.

To mitigate these issues, three techniques are examined: Packet Duplication (PD), Packet Splitting (PS), and Random Linear Network Coding (RLNC). PD sends identical copies of each packet over both paths; the overall loss probability is simply the product of the independent loss probabilities of the two links. While PD guarantees high reliability, it doubles the required radio resources. PS divides the traffic stream into two sub‑flows according to a split ratio (w₁, w₂). The loss probability is derived by convolving the loss distributions of each sub‑flow, which can be tuned to balance load and latency but still suffers from reordering when the delay gap is large. RLNC encodes K source packets into N coded packets; the destination can recover the original data as soon as any K coded packets arrive, regardless of which path they traveled. The authors provide closed‑form expressions for the decoding probability based on the finite field size q and the loss statistics of each link.

A key contribution is the unified analytical framework that models each wireless link as a two‑state discrete‑time Markov chain (DTMC) with transition matrix T =