open access publication

Article, 2024

Network Slicing for eMBB, URLLC, and mMTC: An Uplink Rate-Splitting Multiple Access Approach

IEEE Transactions on Wireless Communications, ISSN 1536-1276, Volume 23, 3, Pages 2140-2152, 10.1109/TWC.2023.3295804

Contributors

Liu Y. 0000-0002-3947-0427 (Corresponding author) [1] Clerckx B. 0000-0001-5949-6459 [1] Popovski P. 0000-0001-6195-4797 [2]

Affiliations

  1. [1] Imperial College London
  2. [NORA names: United Kingdom; Europe, Non-EU; OECD];
  3. [2] Aalborg University
  4. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

There are three generic services in 5G: enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). To guarantee the performance of heterogeneous services, network slicing is proposed to allocate resources to different services. Network slicing is typically done in an orthogonal multiple access (OMA) fashion, which means different services are allocated non-interfering resources. However, as the number of users grows, OMA-based slicing is not always optimal, and a non-orthogonal scheme may achieve better performance. This work aims to analyse the performances of different slicing schemes in uplink, and a promising scheme based on rate-splitting multiple access (RSMA) is studied. RSMA can provide a more flexible decoding order and theoretically has the largest achievable rate region than OMA and non-orthogonal multiple access (NOMA) without time-sharing. Hence, RSMA has the potential to increase the rate of users requiring different services. In addition, it is not necessary to decode the two split streams of one user successively, so RSMA lets suitable users split messages and designs an appropriate decoding order depending on the service requirements. This work shows that for network slicing RSMA can outperform NOMA counterpart, and obtain significant gains over OMA in some regions.

Keywords

URLLC, eMBB, mMTC, network slicing, rate-splitting multiple access

Data Provider: Elsevier