Abstract

This paper investigates the problem of maximizing the secrecy energy efficiency (SEE) for unmanned aerial vehicle- (UAV-) to-ground wireless communication system, in which a fixed-wing UAV tries to transmit covert information to a terrestrial legitimate destination receiver with multiple terrestrial eavesdroppers. In particular, we intend to maximize the worst-case SEE of UAV by jointly optimizing UAV’s flight trajectory and transmit power over a finite flight period. However, the formulated problem is challenging to solve because of its large-scale nonconvexity. For efficiently solving this problem, we first decouple the above optimization problem into two subproblems and then propose an alternating iterative algorithm by adopting block coordinate descent method and Dinkelbach’s algorithm as well as successive convex approximation technique to seek a suboptimal solution. For the sake of performance comparison, two benchmark schemes, the secrecy rate maximization (SRM) scheme and constrained energy minimization (CEM) scheme are considered to obtain more useful insights. Finally, simulation results are executed to verify that our proposed SEE maximization (SEEM) algorithm is superior to two benchmark schemes for the UAV-ground communication system.

Highlights

  • According to Global Information, Inc. (GII) [1], by 2027, the UAV market will reach $21.8 billion and 13.2 million vehicles in terms of volume

  • Over the past few years, there are plenty of Physical layer security (PLS) schemes proposed to enable secure terrestrial wireless communication. They can be classified in two main categories: first, schemes based on introducing multiple-level cooperative relay [9] or multiple-input multiple-output (MIMO) [10] to improve the legitimate channel capacity and second, noise forward- [11] or cooperative jammingbased [12, 13] schemes to significantly reduce the eavesdropping channel capacity

  • (ii) The formulated secrecy energy efficiency (SEE) maximization problem is challenging to solve because of its large-scale nonconvexity. To handle this intractable issue, we present an iterative algorithm to find the high-quality local optimum via employing the block coordinate descent (BCD) method and Dinkelbach’s algorithm as well as successive convex approximation (SCA) technique (iii) To obtain more performance insights, the SEE for the secrecy rate maximization (SRM) scheme and constrained energy minimization (CEM) scheme are considered for comparison

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Summary

Introduction

According to Global Information, Inc. (GII) [1], by 2027, the UAV market will reach $21.8 billion and 13.2 million vehicles in terms of volume. Over the past few years, there are plenty of PLS schemes proposed to enable secure terrestrial wireless communication. They can be classified in two main categories: first, schemes based on introducing multiple-level cooperative relay [9] or multiple-input multiple-output (MIMO) [10] to improve the legitimate channel capacity and second, noise forward- [11] or cooperative jammingbased [12, 13] schemes to significantly reduce the eavesdropping channel capacity. PLS schemes based on transmit power control, beamforming, and/or cooperative jamming usually require precisely known channel state information (CSI) of Wireless Communications and Mobile Computing eavesdropper. The terrestrial wireless channel is rather random, especially for the case in the presence of the passive eavesdroppers, which makes CSI estimation very difficult

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