Reducing Handover Latency in Mobile Satellite Networks

Core Concepts

Proposing a novel handover scheme to reduce latency in mobile satellite networks by avoiding communication with the core network.

Abstract

The construction of Low Earth Orbit (LEO) satellite constellations has attracted significant attention from academia and industry. Ground terminals face high-latency handovers due to fast-traveling satellites, impacting latency-sensitive applications. A novel handover flowchart is proposed to reduce latency by leveraging predictable satellite trajectories and spatial distribution. The synchronized algorithm addresses synchronization challenges between access and core networks without control signaling interaction. Extensive experiments show a 10x reduction in handover latency compared to existing schemes.

Stats

The proposed handover scheme achieved a 10x reduction in latency compared to existing schemes.
The average handover latency based on the proposed scheme was 20.87 ms, significantly shorter than other schemes.
The proposed fast access satellite prediction algorithm reduced computing time with increasing numbers of users.

Quotes

"Our proposed handover scheme shows superior performance over existing schemes in terms of reducing handover latency."
"The synchronized algorithm successfully addressed synchronization challenges between RAN and core network without control signaling interaction."
"The fast access satellite prediction algorithm significantly reduced computing time with increasing numbers of users."

Key Insights Distilled From

Accelerating Handover in Mobile Satellite Network

by Jiasheng Wu,... at arxiv.org 03-19-2024

https://arxiv.org/pdf/2403.11502.pdf

Deeper Inquiries

How can the proposed handover scheme be adapted for different types of satellite constellations?

The proposed handover scheme can be adapted for different types of satellite constellations by considering the specific characteristics and configurations of each constellation. For example, in constellations with varying altitudes or inter-satellite link arrangements, adjustments may need to be made in the prediction algorithms to account for these differences. Additionally, the access satellite selection strategies may need to be optimized based on factors like coverage area and user mobility patterns unique to each constellation. By tailoring the handover scheme parameters to suit the specific requirements of different satellite constellations, it can effectively reduce handover latency across a variety of network setups.

What are the potential drawbacks or limitations of avoiding communication with the core network during handovers?

While avoiding communication with the core network during handovers can significantly reduce latency and streamline the process, there are potential drawbacks and limitations to consider:

Limited Control: By bypassing interactions with the core network, there may be limited control over certain aspects of handovers such as resource allocation or quality-of-service management.

Dependency on Predictions: The accuracy and reliability of predictions become crucial when eliminating direct communication with the core network. Inaccurate predictions could lead to disruptions in service continuity.

Scalability Challenges: As networks scale up in terms of users and satellites, managing synchronization solely at RAN without involving core networks could pose scalability challenges.

Security Concerns: Direct communication between RAN and core networks often includes security measures that ensure data integrity and confidentiality. Avoiding this interaction might raise security concerns if not adequately addressed through alternative means.

Complexity in Handling Exceptions: Handling exceptional cases such as abnormal user behavior or deviations from predicted trajectories becomes more challenging without real-time coordination between RAN and core networks.

How might advancements in satellite technology impact the effectiveness of the proposed handover optimization?

Advancements in satellite technology have a significant impact on how effective the proposed handover optimization can be:

Improved Ephemeris Data: More accurate ephemeris data provided by advanced tracking systems would enhance prediction accuracy for user access satellites, reducing errors due to trajectory deviations.

Enhanced Inter-Satellite Communication: Advancements enabling faster inter-satellite links would minimize delays associated with transmitting signaling information between satellites during a handover.

Increased Satellite Density: Higher-density constellations allow for more frequent access opportunities which could improve overall system performance by providing better connectivity options during a handover event.

4Dynamic Resource Allocation: Advanced technologies facilitating dynamic resource allocation among satellites based on traffic load or user demand could optimize routing decisions during a handover process leading to improved efficiency.
5Autonomous Decision-Making: With advancements like AI-based decision-making capabilities onboard satellites, autonomous adaptation strategies could further optimize seamless transitions during a mobile satellite network's operation.
These advancements collectively contribute towards enhancing operational efficiency while leveraging predictive algorithms within mobile satellite networks'handoff procedures..