In this paper, the closed-form expressions of signal-to-interference-plus-noise ratio (SINR) and the outage probability are derived for a maximal ratio combining (MRC) two-dimensional (2-D)-RAKE receiver with imperfect power control in a frequency-selective Nakagami fading channel. The impact of power control error (PCE) on the performance of the receiver is analyzed for all kinds of fading environments. The results of numerical derivation and simulation indicate that the performance of 2-D-RAKE receivers degrades due to imperfect power control. But when PCE is not serious, increasing the number of antennae and temporal diversity order can compensate for the performance loss. The exact performance improvement due to space-time processing varies with the PCE and the fading environment.

In order to satisfy the very high traffic demand in crowded hotspot areas and realize adequate security in future fifth-generation networks, this paper studies physical-layer security in the downlink of a two-tier ultra dense heterogeneous network, where a ubiquitous array formed by ultra dense deployed small-cells surrounds a macrocell base station. In this paper, the locations of legitimate users and eavesdroppers are drawn from Poisson point processes. Then, the cumulative distribution functions of the receive signal-to-interference-plus-noise ratio for legitimate users and eavesdroppers are derived. Further, the average secrecy rate and secrecy coverage probability for each tier as well as for the whole network are investigated. Finally, we analyze the influences on secrecy performance caused by eavesdropper density, transmit power allocation ratio, antenna number allocation ratio, and association area radius.

The final exponentiation affects the efficiency of pairing computations especially on pairing-friendly curves with high embedding degree. We propose an efficient method for computing the hard part of the final exponentiation on the KSS18 curve at the 192-bit security level. Implementations indicate that the computation of the final exponentiation is 8.74% faster than the previously fastest result.

This letter proposes a novel approach for mel-cepstral analysis based on the psychoacoustic model of MPEG. A perceptual weighting function is developed by applying cubic spline interpolation on the signal-to-mask ratios (SMRs) which are obtained from the psychoacoustic model. Experiments on speaker identification and speech re-synthesis showed that the proposed method not only improved the speaker recognition performance, but also improved the speech quality of the re-synthesized speech.

In this paper, a deep learning-based secret key generation scheme is proposed for FDD multiple-input and multiple-output (MIMO) systems. We built an encoder-decoder based convolutional neural network to characterize the wireless environment to learn the mapping relationship between the uplink and downlink channel. The designed neural network can accurately predict the downlink channel state information based on the estimated uplink channel state information without any information feedback. Random secret keys can be generated from downlink channel responses predicted by the neural network. Simulation results show that deep learning based SKG scheme can achieve significant performance improvement in terms of the key agreement ratio and achievable secret key rate.

Dynamic linear feedback shift registers (DLFSRs) are a scheme to transfer from one LFSR to another. In cryptography each LFSR included in a DLFSR should generate maximal-length sequences, and the number of switches transferring LFSRs should be small for efficient performance. This corresponding addresses on searching such conditioned DLFSRs. An efficient probabilistic algorithm is given to find such DLFSRs with two or four switches, and it is proved to succeed with nonnegligible probability.

In this paper, the bit error rate (BER) and the outage probability are presented for a maximal ratio combining (MRC) two-dimensional (2D)-RAKE receiver operating in a correlated frequency-selective Nakagami-m fading environment with multiple access interference. A simple approximated probability distribution function of the signal-to-interference-plus-noise ratio (SINR) is derived for the receiver with multiple correlated antennas and RAKE branches in arbitrary fading environments. The combined effects of spatial and temporal diversity order, average received signal-to-noise ratio, the number of multiple access interference, angular spread, antennae spacing and multi-path Nakagami-m fading environment on the system performance are illustrated. Numerical results indicate that the performance of the 2D-RAKE receiver depends highly on the operating environment and antenna array configuration. The performance can be improved by increasing the spatio-temporal diversity gains and antenna spacing.

The image-to-image translation aims to learn a mapping between the source and target domains. For improving visual quality, the majority of previous works adopt multi-stage techniques to refine coarse results in a progressive manner. In this work, we present a novel approach for generating plausible details by only introducing a group of intermediate supervisions without cascading multiple stages. Specifically, we propose a Laplacian Pyramid Transformation Generative Adversarial Network (LapTransGAN) to simultaneously transform components in different frequencies from the source domain to the target domain within only one stage. Hierarchical perceptual and gradient penalization are utilized for learning consistent semantic structures and details at each pyramid level. The proposed model is evaluated based on various metrics, including the similarity in feature maps, reconstruction quality, segmentation accuracy, similarity in details, and qualitative appearances. Our experiments show that LapTransGAN can achieve a much better quantitative performance than both the supervised pix2pix model and the unsupervised CycleGAN model. Comprehensive ablation experiments are conducted to study the contribution of each component.