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2019-01-21
Wang, J., Lin, S., Liu, C., Wang, J., Zhu, B., Jiang, Y..  2018.  Secrecy Capacity of Indoor Visible Light Communication Channels. 2018 IEEE International Conference on Communications Workshops (ICC Workshops). :1–6.
In the indoor scenario, visible light communications (VLC) is regarded as one of the most promising candidates for future wireless communications. Recently, the physical layer security for indoor VLC has drawn considerable attention. In this paper, the secrecy capacity of indoor VLC is analyzed. Initially, an VLC system with a transmitter, a legitimate receiver, and an eavesdropper is established. In the system, the nonnegativity, the peak optical intensity constraint and the dimmable average optical intensity constraint are considered. Based on the principle of information theory, the closed-form expressions of the upper and the lower bounds on the secrecy capacity are derived, respectively. Numerical results show that the upper and the lower bounds on secrecy capacity are very tight, which verify the accuracy of the derived closed-form expressions.
2018-08-23
Lagunas, E., Rugini, L..  2017.  Performance of compressive sensing based energy detection. 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). :1–5.

This paper investigates closed-form expressions to evaluate the performance of the Compressive Sensing (CS) based Energy Detector (ED). The conventional way to approximate the probability density function of the ED test statistic invokes the central limit theorem and considers the decision variable as Gaussian. This approach, however, provides good approximation only if the number of samples is large enough. This is not usually the case in CS framework, where the goal is to keep the sample size low. Moreover, working with a reduced number of measurements is of practical interest for general spectrum sensing in cognitive radio applications, where the sensing time should be sufficiently short since any time spent for sensing cannot be used for data transmission on the detected idle channels. In this paper, we make use of low-complexity approximations based on algebraic transformations of the one-dimensional Gaussian Q-function. More precisely, this paper provides new closed-form expressions for accurate evaluation of the CS-based ED performance as a function of the compressive ratio and the Signal-to-Noise Ratio (SNR). Simulation results demonstrate the increased accuracy of the proposed equations compared to existing works.