Biblio

In this paper, we present a chaos-based information rotated polar coding scheme for enhancing the reliability and security of visible light communication (VLC) systems. In our scheme, we rotate the original information, wherein the rotation principle is determined by two chaotic sequences. Then the rotated information is encoded by secure polar coding scheme. After the channel polarization achieved by the polar coding, we could identify the bit-channels providing good transmission conditions for legitimate users and the bit-channels with bad conditions for eavesdroppers. Simulations are performed over the visible light wiretap channel. The results demonstrate that compared with existing schemes, the proposed scheme can achieve better reliability and security even when the eavesdroppers have better channel conditions.

This paper investigates the problem of user pairing in multi-carrier non-orthogonal multiple access (MC-NOMA) systems. Firstly, the hard channel capacity and soft channel capacity are presented. The former depicts the transmission capability of the system that depends on the channel conditions, and the latter refers to the effective throughput of the system that is determined by the actual user demands. Then, two optimization problems to maximize the hard and soft channel capacities are established, respectively. Inspired by the multiagent deep reinforcement learning (MADRL) and convolutional neural network, the user paring network (UP-Net), based on the cooperative game and deep deterministic policy gradient, is designed for solving the optimization problems. Simulation results demonstrate that the performance of the designed UP-Net is comparable to that obtained from the exhaustive search method via the end-to-end low complexity method, which is superior to the common method, and corroborate that the UP-Net focuses more on the actual user demands to improve the soft channel capacity. Additionally and more importantly, the paper makes a useful exploration on the use of MADRL to solve the resource allocation problems in communication systems. Meanwhile, the design method has strong universality and can be easily extended to other issues.

High-accuracy localization is a prerequisite for many wireless applications. To obtain accurate location information, it is often required to share users' positional knowledge and this brings the risk of leaking location information to adversaries during the localization process. This paper develops a theory and algorithms for protecting location secrecy. In particular, we first introduce a location secrecy metric (LSM) for a general measurement model of an eavesdropper. Compared to previous work, the measurement model accounts for parameters such as channel conditions and time offsets in addition to the positions of users. We determine the expression of the LSM for typical scenarios and show how the LSM depends on the capability of an eavesdropper and the quality of the eavesdropper's measurement. Based on the insights gained from the analysis, we consider a case study in wireless localization network and develop an algorithm that diminish the eavesdropper's capabilities by exploiting the reciprocity of channels. Numerical results show that the proposed algorithm can effectively increase the LSM and protect location secrecy.