Robust Chance-Constrained Secure Transmission for Cognitive Satellite-Terrestrial Networks

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Abstract

Cognitive satellite-terrestrial networks (CSTNs) have been recognized as a promising network architecture for addressing spectrum scarcity problem in next-generation communication networks. In this paper, we investigate the secure transmission for CSTNs where the terrestrial base station serving as a green interference resource is introduced to enhance the security of the satellite link. Adopting a stochastic model for the channel state information uncertainty, we propose a secure and robust beamforming framework to minimize the transmit power, while satisfying a range of outage (probabilistic) constraints concerning the signal-to-interference-plus-noise ratio (SINR) recorded at the satellite user and the terrestrial user, the leakage-SINR recorded at the eavesdropper, as well as the interference power recorded at the satellite user. The resulting robust optimization problem is highly intractable and the key observation is that the highly intractable probability constraints can be equivalently reformulated as the deterministic versions with Gaussian statistics. In this regard, we develop two robust reformulation methods, namely S-procedure and Bernstein-type inequality restriction techniques, to obtain a safe approximate solution. In the meantime, the computational complexities of the proposed schemes are analyzed. Finally, the effectiveness of the proposed schemes are demonstrated by numerical results with different system parameters.

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Li, B., Fei, Z., Chu, Z., Zhou, F., Wong, K. K., & Xiao, P. (2018). Robust Chance-Constrained Secure Transmission for Cognitive Satellite-Terrestrial Networks. IEEE Transactions on Vehicular Technology, 67(5), 4208–4219. https://doi.org/10.1109/TVT.2018.2791859

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