Latency-aware End-to-end Multi-path Data Transmission for URLLC Services Liu Cao Abbas Kiani Amanda Xiang Kaippallimalil John Tony Saboorian

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Latency-aware End-to-end Multi-path Data

Transmission for URLLC Services

Liu Cao∗, Abbas Kiani†, Amanda Xiang†, Kaippallimalil John†, Tony Saboorian†

∗Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA

†Wireless Research and Standards, Futurewei Technologies Inc., Addison, TX, USA

Emails: liucao@uw.edu, {abbas.kiani, amanda.xiang, john.kaippallimalil, tony.saboorian}@futurewei.com

Abstract—5th Generation Mobile Communication Technology

(5G) utilizes the Access Trafﬁc Steering, Switching, and Splitting

(ATSSS) rule to enable multi-path data transmission, which is cur-

rently being standardized. Recently, the 3rd Generation Partnership

Project (3GPP) SA1 and SA2 have been working on the multi-

path solution for possible improvement from different perspectives.

However, the existing 3GPP multi-path solution has some limitations

on ultra-reliable low-latency communication (URLLC) trafﬁc in

terms of reliability and latency requirements. In order to capture the

potential gains of multi-path architecture in the context of URLLC

services, this paper proposes a novel trafﬁc splitting technique that

can more efﬁciently enjoy the beneﬁt of multi-path architecture in

reducing user equipment (UE) uplink (UL) end-to-end (E2E) latency.

In particular, we formulate an optimization framework that mini-

mizes user’s UL E2E latency via the joint optimization on the ratio

of trafﬁc assigned to each path and their corresponding transmit

power. The performance of the proposed scheme is evaluated via

well-designed simulations.

Index Terms—ATSSS, E2E, Multi-path, URLLC, Latency.

I. INTRODUCTION

NOWADAYS a mobile device may establish multiple data

paths simultaneously with the same application using dif-

ferent access technologies (e.g., 5G, 4G, WiFi, Satellite, etc.).

Even connecting through different networks (e.g., private network,

public network) to improve user quality of service (QoS) is

becoming one of the feasible and desirable deployment options

in beyond 5G (B5G). 3rd Generation Partnership Project (3GPP)

SA1 and SA2 have been working on end-to-end (E2E) multi-path

solution since Release 16 [1] and the work will be continued on

Release 18 and 19. Speciﬁcally, redundant transmission for high-

reliability communication was ﬁrst introduced [2]. The Phase 3 of

further enhancing Access Trafﬁc Steering, Switching and Splitting

(ATSSS) has started in Release 18 [3]. More recently, Release 19

studied the upper layer ATSSS over dual 3GPP access [4].

Although 3GPP has paid particular attention to the E2E multi-

path solution for data transmission, it still has some limitations

in the following aspects: 1) The current solution only takes

into consideration between 3GPP access and non-3GPP access.

However, Release 19 has planned to consider the ATSSS between

two 3GPP access; 2) It does not satisfy the latency and the

reliability requirement of URLLC trafﬁc because all trafﬁc is

splitted and steered based on a static policy; 3) It lacks holistic

and intelligent view on E2E QoS assurance, e.g., UE and network

function (NF) make individual decisions based on simple inputs

and relative static policy.

The recent research literature has focused on the multi-path

work to fulﬁll the latency and reliability requirements of data

transmission [5]–[11]. In particular, the authors in [8] investigated

an optimization problem for trafﬁc scheduling in NR and WLAN

aggregation (NWA) which is mainly focused on enhanced mobile

broadband (eMBB) services and does not take into consideration

of speciﬁc requirements of URLLC services. The literature [9]

studied a multi-path transmission control protocol (MPTCP)

scheduler, providing a good user experience for latency-sensitive

applications when interface quality is asymmetric. However, this

work considers the multi-path only from the transport layer

perspective. In addition, machine learning (ML) based algorithms

have been applied in the multi-path architecture. A joint power

control and channel allocation scheme was developed in [12] to

reduce interference adaptively based on combining a reinforce-

ment learning (RL) algorithm from the radio link side rather than

the E2E side.

Motivated by the aforementioned issues, this paper proposes a

novel E2E multi-path solution for URLLC data transmission. The

major contributions of this paper are summarized as follows.

•We propose an optimization framework that minimizes the

latency of user equipment (UE) uplink (UL) URLLC trafﬁcs

by jointly optimizing the trafﬁc ratio of each path and

associated transmit power.

•The proposed optimization framework is a dynamic policy

because the decision in each time interval is determined

by the combination of particular network conditions, trafﬁc

characteristics, and latency requirements.

•We compare the proposed multi-path solution with potential

baselines under different scenarios, showing the advantages

of the proposed multi-path solution.

The rest of this paper is organized as follows: Sec II intro-

duces the system architecture. The system model is illustrated

in Sec III. In Sec IV, we compare the multi-path solution with

proposed baseline solutions in terms of the instant latency and

the average latency via the simulation. Finally, section V draws

the conclusions for this paper.

II. SYSTEM ARCHITECTURE

As Fig. 1 shows, we consider an E2E system architecture where

a single UE that has multiple trafﬁc types for UL transmission

connects to an application server (AS) via radio access network

(RAN) and core network (CN) [13]. UE connects to each base

arXiv:2210.13740v2 [cs.NI] 21 Oct 2023

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Latency-awareEnd-to-endMulti-pathDataTransmissionforURLLCServicesLiuCao∗,AbbasKiani†,AmandaXiang†,KaippallimalilJohn†,TonySaboorian†∗DepartmentofElectricalandComputerEngineering,UniversityofWashington,Seattle,WA,USA†WirelessResearchandStandards,FutureweiTechnologiesInc.,Addison,TX,USAEmails:liucao@u...

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Latency-aware End-to-end Multi-path Data Transmission for URLLC Services Liu Cao Abbas Kiani Amanda Xiang Kaippallimalil John Tony Saboorian

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