Cooperative Secure Communication in UAV Assisted Networks with Dynamic Role Switching
Authors: Wang, Q., Gao, A., Hu, Y. and Zhang, J.
Journal: 2023 IEEE Globecom Workshops, GC Wkshps 2023
Pages: 2152-2157
DOI: 10.1109/GCWkshps58843.2023.10464417
Abstract:This paper proposes a novel role switching scheme (RSS) to optimize the secure communication by the cooperation of multiple unmanned aerial vehicles (UAVs). Each UAV is enabled to switch its role during the flight, i.e., could be an aerial relay to serve ground users (GUs) or a friendly jammer to generate artificial noise (AN) to deteriorate the wiretapping of potential eavesdropper users (EUs). It's worthy to be noticed that the joint optimization for UAVs' trajectory and legitimate GUs' transmission power control with RSS is a non-convex mixed integer fractional programming problem. A multi-agent deep reinforcement learning (MADRL) combined successive convex approximate (SCA) algorithm is further designed to maximize the achievable secrecy energy efficiency (ASEE). Numerical results illustrate that compared with the role fixed scheme (RFS) and relaxation based SCA approaches, the proposed DRL-SCA algorithm endows UAVs the capacity to fly close enough to target users (both GUs and EUs) which brings a better achievable secrecy rate (ASR), less energy consumption and higher ASEE.
https://eprints.bournemouth.ac.uk/39500/
Source: Scopus
Cooperative Secure Communication in UAV Assisted Networks with Dynamic Role Switching
Authors: Zhang, J., Wang, Q., Gao, A. and Hu, Y.
Conference: 2023 IEEE Global Communications Conference
Dates: 4-8 December 2023
https://eprints.bournemouth.ac.uk/39500/
Source: Manual
Cooperative Secure Communication in UAV Assisted Networks with Dynamic Role Switching
Authors: Zhang, J., Wang, Q., Gao, A. and Hu, Y.
Conference: 2023 IEEE Global Communications Conference
Pages: 2152-2157
Publisher: IEEE
Abstract:This paper proposes a novel role switching scheme (RSS) to optimize the secure communication by the cooperation of multiple unmanned aerial vehicles (UAVs). Each UAV is enabled to switch its role during the flight, i.e., could be an aerial relay to serve ground users (GUs) or a friendly jammer to generate artificial noise (AN) to deteriorate the wiretapping of potential eavesdropper users (EUs). It’s worthy to be noticed that the joint optimization for UAVs’ trajectory and legitimate GUs’ transmission power control with RSS is a non-convex mixed integer fractional programming problem. A multi-agent deep reinforcement learning (MADRL) combined successive convex approximate (SCA) algorithm is further designed to maximize the achievable secrecy energy efficiency (ASEE). Numerical results illustrate that compared with the role fixed scheme (RFS) and relaxation based SCA approaches, the proposed DRL-SCA algorithm endows UAVs the capacity to fly close enough to target users (both GUs and EUs) which brings a better achievable secrecy rate (ASR), less energy consumption and higher ASEE. Index Terms—Secure Communication, Dynamic Role Switching, DRL, SCA, UAV Assisted Networks
https://eprints.bournemouth.ac.uk/39500/
Source: BURO EPrints