Abstract:
The Non-Terrestrial Network (NTN) is a promising technology to achieve the ubiquitous, low latency, and high data rate next-generation communication system, however, sinc...Show MoreMetadata
Abstract:
The Non-Terrestrial Network (NTN) is a promising technology to achieve the ubiquitous, low latency, and high data rate next-generation communication system, however, since the broad application of the NTN, the security problem in the NTN is of paramount importance. In this regard, this paper investigates a novel secure communication strategy within the NTN, where a legitimate user of the LEO satellite-integrated unmanned aerial vehicles network (ISUAVN) is equipped with a high-gain antenna and attempts to cross-layer eavesdrop on the GEO satellite network.In the considered NTN system, the cell-free massive multi-input multi-output (CFmMIMO) network is utilized at the ISUAVN to enhance the spectral efficiency of the terrestrial users. Furthermore, the ISUAVN shares the millimeter wave spectrum with the GEO satellite multicast downlink communication link. We first formulated a multi-objective optimization (MOO) based joint beamforming design problem for the secure communication of the considered CFmMIMO NTN system to achieve a Pareto optimal trade-off between two conflicting and essential objectives: minimizing total transmitted power and maximizing the secret data rate of the satellite network. Thereafter, to address this mathematically complicated optimization problem, we utilized successive convex approximation methods to transform this intractable problem into an equivalent convex optimization problem. Then, the commercial optimization package is employed to achieve the optimal solution of the MOO problem, commencing from a feasible point that is identified by a semi-definite programming initialization algorithm. Ultimately, the numerical simulation results demonstrated that the Pareto optimal trade-offs for the formulated MOO problem were achieved using the proposed algorithm, and the effectiveness of our proposed algorithm was shown through comparisons with existing related methods.
Published in: IEEE Internet of Things Journal ( Early Access )