Robust Trajectory and Transmit Power Optimization for Secure UAV-Enabled Cognitive Radio Networks

Abstract

Cognitive radio is a promising technology to improve spectral efficiency. However, the secure performance of a secondary network achieved by using physical layer security techniques is limited by its transmit power and channel fading. In order to tackle this issue, a cognitive unmanned aerial vehicle (UAV) communication network is studied by exploiting the high flexibility of a UAV and the possibility of establishing line-ofsight links. The average secrecy rate of the secondary network is maximized by robustly optimizing the UAV's trajectory and transmit power. Our problem formulation takes into account two practical inaccurate location estimation cases, namely, the worst case and the outage-constrained case. In order to solve those challenging non-convex problems, an iterative algorithm based on S-Procedure is proposed for the worst case while an iterative algorithm based on Bernstein-type inequalities is proposed for the outage-constrained case. The proposed algorithms can obtain effective suboptimal solutions of the corresponding problems. Our simulation results demonstrate that the algorithm under the outage-constrained case can achieve a higher average secrecy rate with a low computational complexity compared to that of the algorithm under the worst case. Moreover, the proposed schemes can improve the secure communication performance significantly compared to other benchmark schemes.

Cognitive NOMA for UAV-Enabled Secure Communications: Joint 3D Trajectory Design and Power Allocation

“…The work in [29] deploys UAV as a mobile relay to assist communication from a secondary transmitter (ST) to a secondary receiver (SR) in the presence of an Eve, while the work in [30] employs UAV as a friendly jammer to interfere with the Eve. Moreover, the security of cognitive UAV communication networks is studied in [31], [32], where a cognitive/secondary UAV acts as a transceiver to communicate with an SR. With imperfect information regarding the locations of PRs and Eves, a joint robust two-dimensional (2D) trajectory and transmit power design is investigated in [32] to maximize the average secrecy rate by taking into account two practical inaccurate location estimations, i.e., the worst case and the outage-constrained case. However, the above works in [29]- [32] only consider one SR, which extremely simplifies the practical consideration.…”

“…In such a spectrum sharing scenario, PRs suffer severe air-to-ground interference from the secondary UAV. In order to protect primal communications, the interference temperature (IT) technique is adopted as in [29]- [32] such that the interference power at i-th PR within time slot n is constrained below the tolerable threshold Γ, i.e.,…”

Joint Trajectory Optimization and Spectrum Access for Cognitive UAV Networks

“…is Gaussian noise with variance σ 2 P , x m is the mth PT signal with power p m , and h FP m (n) is the air-to-ground channel gain between FUAV m and the mth PT. The channel from the UAV-based CR to the ground PU can be seen as line-of-sight (LoS) since the decrease of sensing performance caused by the severe ground fading can be ignored in the air UAV spectrum sensing [11], [21], i.e., h FPm (n) = α 0 / q Fm (n) − q Pm 2 , where q Pm represents the locations of the mth PT and q Fm (n) denotes the three dimensional allocations of FUAVm at time slot t n .…”

“…By observing (21), because Q[x] is a monotonically decreasing function, P f (n) is an increasing function with respect to P d0 . Based on this observation, R 1 +R 2 is a decreasing function with respect to P d0 since C 1 > C 2 .…”

Spectrum-Sharing UAV-Assisted Mission-Critical Communication: Learning-Aided Real-Time Optimisation

“…In [8], the authors utilised UAVs as a solution to enhance the average secrecy rate in the cognitive communication networks, by optimising UAVs' robust trajectory and transmit power allocation. In [9], considering the downlink transmission of UAV-enabled networks in coexistence with D2D communication, the authors proposed a joint design of D2D assignment and resource allocation for maximising ground terminals throughput.…”