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