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Joint task allocation and hybrid beamforming for mmWave D2D MEC systems

Joint task allocation and hybrid beamforming for mmWave D2D MEC systems
Joint task allocation and hybrid beamforming for mmWave D2D MEC systems

Mobile edge computing (MEC) and millimeter wave (mmWave) communications are capable of significantly reducing the network's delay and/or enhancing its capacity. Hence we investigate a mmWave device-to-device (D2D) MEC system, in which user A carries out some computational tasks and shares the results with user B with the aid of a base station (BS). In order to minimize the system's delay, the task can be partitioned into two portions: the first part is computed locally at user A, while the second part is transmitted to the BS and computed by the MEC server. The computational results are then sent to user B through a D2D link and via the link from the BS to user B, over orthogonal time slots. To support computation offloading, both the users and the BS are equipped with multiple antennas and employ A/D hybrid beamforming for their transmission. We develop a novel algorithm for jointly optimizing the offloading ratio and the hybrid beamformers. The simulation results show that the proposed algorithm significantly reduces the system's delay compared to the existing algorithms.

D2D, Delay minimization, MmWave, Mobile edge computing
IEEE
Liu, Yanzhen
56fd81a3-15a3-4e11-a928-6e61f59f0311
Cai, Yunlong
44a85b9f-185b-4078-aecd-02df90f5eab6
Liu, An
74769859-8fe6-4f56-b2c9-c0f23b7b7e24
Zhao, Minjian
d552c3c1-57fd-4643-b914-4572ef291edf
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Liu, Yanzhen
56fd81a3-15a3-4e11-a928-6e61f59f0311
Cai, Yunlong
44a85b9f-185b-4078-aecd-02df90f5eab6
Liu, An
74769859-8fe6-4f56-b2c9-c0f23b7b7e24
Zhao, Minjian
d552c3c1-57fd-4643-b914-4572ef291edf
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Liu, Yanzhen, Cai, Yunlong, Liu, An, Zhao, Minjian and Hanzo, Lajos (2020) Joint task allocation and hybrid beamforming for mmWave D2D MEC systems. In 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2020. vol. 2020-August, IEEE.. (doi:10.1109/PIMRC48278.2020.9217285).

Record type: Conference or Workshop Item (Paper)

Abstract

Mobile edge computing (MEC) and millimeter wave (mmWave) communications are capable of significantly reducing the network's delay and/or enhancing its capacity. Hence we investigate a mmWave device-to-device (D2D) MEC system, in which user A carries out some computational tasks and shares the results with user B with the aid of a base station (BS). In order to minimize the system's delay, the task can be partitioned into two portions: the first part is computed locally at user A, while the second part is transmitted to the BS and computed by the MEC server. The computational results are then sent to user B through a D2D link and via the link from the BS to user B, over orthogonal time slots. To support computation offloading, both the users and the BS are equipped with multiple antennas and employ A/D hybrid beamforming for their transmission. We develop a novel algorithm for jointly optimizing the offloading ratio and the hybrid beamformers. The simulation results show that the proposed algorithm significantly reduces the system's delay compared to the existing algorithms.

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More information

e-pub ahead of print date: 8 October 2020
Additional Information: Publisher Copyright: © 2020 IEEE.
Venue - Dates: 31st IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2020, , Virtual, London, United Kingdom, 2020-08-31 - 2020-09-03
Keywords: D2D, Delay minimization, MmWave, Mobile edge computing

Identifiers

Local EPrints ID: 467440
URI: http://eprints.soton.ac.uk/id/eprint/467440
PURE UUID: 38f14647-9d54-4e9d-a7f4-cfc0e3ebba3e
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 08 Jul 2022 16:39
Last modified: 18 Mar 2024 02:36

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Contributors

Author: Yanzhen Liu
Author: Yunlong Cai
Author: An Liu
Author: Minjian Zhao
Author: Lajos Hanzo ORCID iD

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