University of Oulu

Y. Liu, Q. Hu, Y. Cai and M. Juntti, "Latency Minimization in Intelligent Reflecting Surface Assisted D2D Offloading Systems," in IEEE Communications Letters, doi: 10.1109/LCOMM.2021.3093165

Latency minimization in intelligent reflecting surface assisted D2D offloading systems

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Author: Liu, Yanzhen1; Hu, Qiyu1; Cai, Yunlong1;
Organizations: 1College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
2Centre for Wireless Communications, University of Oulu, Oulu 90014, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021080642187
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-08-06
Description:

Abstract

In this letter, we investigate an intelligent reflecting surface (IRS) aided device-to-device (D2D) offloading system, where an IRS is employed to assist in computation offloading from a group of users with intensive tasks to another group of idle users. To minimize the system latency while cutting down the heavy overhead in exchange of channel state information (CSI), we study the joint design of beamforming and resource allocation on mixed timescales. Specifically, the high-dimensional passive beamforming vector at the IRS is updated in a frame-based manner based on the channel statistics, where each frame consists of a number of time slots, while the offloading ratio and user matching strategy are optimized relied on the low-dimensional real-time effective channel coefficients in each time slot. A novel mixed-integer stochastic successive convex approximation (MISSCA) algorithm is proposed to tackle the challenging problem. The convergence property and the computational complexity of the proposed algorithm are then examined. Simulation results show that our proposed algorithm significantly outperforms the conventional benchmarks.

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Series: IEEE communications letters
ISSN: 1089-7798
ISSN-E: 2373-7891
ISSN-L: 1089-7798
Volume: Early Access
Issue: Early Access
Pages: 1 - 5
DOI: 10.1109/LCOMM.2021.3093165
OADOI: https://oadoi.org/10.1109/LCOMM.2021.3093165
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
D2D
Funding: This work was supported in part by the National Natural Science Foundation of China under Grants 61971376 and 61831004, and in part by the Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars under Grant LR19F010002. (Corresponding author: Yunlong Cai.)
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