eprintid: 10205325 rev_number: 8 eprint_status: archive userid: 699 dir: disk0/10/20/53/25 datestamp: 2025-02-27 09:12:26 lastmod: 2025-02-27 09:16:01 status_changed: 2025-02-27 09:12:26 type: article metadata_visibility: show sword_depositor: 699 creators_name: Huang, Siyue creators_name: Wang, Lifeng creators_name: Wang, Xin creators_name: Tan, Bo creators_name: Ni, Wei creators_name: Wong, Kai-Kit title: Edge Intelligence in Satellite-Terrestrial Networks with Hybrid Quantum Computing ispublished: inpress divisions: UCL divisions: B04 divisions: F46 keywords: Satellite-terrestrial networks, edge intelligence, hybrid quantum computing note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: This paper exploits the potential of edge intelligence empowered satellite-terrestrial networks, where users’ computation tasks are offloaded to the satellites or terrestrial base stations. The computation task offloading in such networks involves the edge cloud selection and bandwidth allocations for the access and backhaul links, which aims to minimize the energy consumption under the delay and satellites’ energy constraints. To address it, an alternating direction method of multipliers (ADMM)-inspired algorithm is proposed to decompose the joint optimization problem into small-scale subproblems. Moreover, we develop a hybrid quantum double deep Q-learning (DDQN) approach to optimize the edge cloud selection. This novel deep reinforcement learning architecture enables that classical and quantum neural networks process information in parallel. Simulation results confirm the efficiency of the proposed algorithm, and indicate that duality gap is tiny and a larger reward can be generated from a few data points compared to the classical DDQN. date: 2025-02-14 date_type: published publisher: Institute of Electrical and Electronics Engineers (IEEE) official_url: https://doi.org/10.1109/lwc.2025.3542085 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 2364413 doi: 10.1109/LWC.2025.3542085 lyricists_name: Wong, Kai-Kit lyricists_name: Tan, Bo lyricists_id: KWONG98 lyricists_id: BTANX50 actors_name: Wong, Kai-Kit actors_id: KWONG98 actors_role: owner full_text_status: public publication: IEEE Wireless Communications Letters issn: 2162-2337 citation: Huang, Siyue; Wang, Lifeng; Wang, Xin; Tan, Bo; Ni, Wei; Wong, Kai-Kit; (2025) Edge Intelligence in Satellite-Terrestrial Networks with Hybrid Quantum Computing. IEEE Wireless Communications Letters 10.1109/LWC.2025.3542085 <https://doi.org/10.1109/LWC.2025.3542085>. (In press). Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10205325/1/manuscript_LEO.pdf