Efficient Integration of Distributed Learning Services in Next-Generation Wireless Networks

International Conference on Communications, pp. 4577–4582

Abstract

Distributed learning (DL) is considered a cornerstone of intelligence enabler, since it allows for collaborative training without the necessity for local clients to share raw data with other parties, thereby preserving privacy and security. Integrating DL into the 6G networks requires coexistence design with existing services such as high-bandwidth (HB) traffic like eMBB. Current designs in the literature mainly focus on communication round (CR)-wise designs that assume a fixed resource allocation during each CR. However, fixed resource allocation within a CR is a highly inefficient and inaccurate representation of the system's realistic behavior. This is due to the heterogeneous nature of the system, where clients inherently need to access the network at different times. This work zooms into one arbitrary communication round and demonstrates the importance of considering a time-dependent resource-sharing design with HB traffic. We propose a time-dependent optimization problem for minimizing the consumed time and energy by DL within the CR. Due to its intractability, a session-based optimization problem has been proposed assuming a large-scale coherence time. An iterative algorithm has been designed to solve such problems and simulation results confirm the importance of such efficient and accurate integration design.

Authors 7

1. Paul Zheng Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Information Theory and Data Analytics,Germany

2. Navid Keshtiarast Aachen Mobile Communications and Computing Group

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Mobile Communications and Computing Group,Germany

3. Pradyumna Kumar Bishoyi Aachen Mobile Communications and Computing Group

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Mobile Communications and Computing Group,Germany

4. Yao Lin Zhu Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Information Theory and Data Analytics,Germany

5. Yulin Hu

   Wuhan University

   Affiliation as printed

   School of Electronic Information, Wuhan University,China

6. Marina Petrova Aachen Mobile Communications and Computing Group

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Mobile Communications and Computing Group,Germany

7. Anke Schmeink Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Information Theory and Data Analytics,Germany