Vehicular Channel Characterization in Urban Environment at 30 GHz considering Overtaking and Traffic Flow

To realize reliable and stable millimeter-wave (mmWave) vehicular wireless communication, the research of vehicular channel characteristics in the dense urban environment is becoming increasingly important. A comprehensive research on the channel characteristics for 30 GHz vehicular communication in the Beijing Central Business District (CBD) scenario is conducted in this paper. The self-developed high-performance ray-tracing (RT) simulator is employed to support intensive simulations. Based on simulation results, the effects of multiantenna and beam switching on the key channel parameters are analyzed, as well as the impact of different traffic flows. The results can provide theoretical and data support for the evaluation of vehicular channel characteristics and will help for the design of the vehicular communication system enabling future intelligent transportation.

PARAFAC-Based Multiuser Channel Parameter Estimation for MmWave Massive MIMO Systems over Frequency Selective Fading Channels

Channel estimation is crucial in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, especially with a few training sequences. To solve the problem of uplink channel estimation in mmWave massive MIMO systems, a PARAFAC-based algorithm is proposed for joint estimation of multiuser channels. The orthogonal frequency divisional multiplexing (OFDM) technique is exploited to combat the frequency selective fading channels. In this paper, the received signal at the base station (BS) is formulated as a third-order parallel factor (PARAFAC) tensor, and then a low-complexity algorithm is designed for fast estimation of the factor matrices related to channel parameters, thus leading to joint estimation of multiuser channel parameters via one-dimensional search. Moreover, the Cramér–Rao Bound (CRB) results for multiuser channel parameters are derived for evaluation. Theorical analysis and numerical results reveal that the algorithm performs well with a few training sequences. Compared with existing algorithms, the proposed algorithm has clear advantages both in estimation accuracy and computational complexity.

Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings

Symmetry-based channel digital twin is a great technology which can reproduce the communication channel of real scenes for performance evaluation of the wireless sensor network (WSN) inside tower buildings, based on the ray tracing (RT) method and machine learning (ML) theories, a cluster-based channel model is proposed in this paper. Meanwhile, an improved k-means method, which considers the weight of different dimensions in the multipath component distance (MCD) is presented for clustering, which has better clustering performance over the sparsity-based algorithm and traditional k-means algorithm. Moreover, the channel parameters such as cluster delay and cluster power are also investigated. On this basis, the communication performance of WSN, i.e., bit error rate (BER) and channel capacity are derived and analyzed. The simulation and analysis results show that the cluster model based on the RT method can get approximately equivalent channel impulse response (CIR), and the BER of proposed model is consistent with the simulated one. These results can provide reference for the node layout and optimization of WSN inside tower buildings.

Dependence of the Piezoelectric Micropump Operating Mode on Its Geometry

A mathematical and computer axisymmetric models in which periodic oscillations of ring piezoelectric actuators placed on an elastic tube of circular cross-section leads to radial deformations of the tube is constructed. The result of these displacements is a local compression of the microchannel, which leads to changes in its volume and the corresponding pushing of the fluid. If a non-symmetrical oscillation scheme is used, the average fluid flow over the period will be non-zero and the device can be used as a micropump. The aim of the work is a computer study of the geometric features of an axisymmetric piezoelectric micropump, taking into account the processes of heat transfer by a fluid in the channel. The dependence of the average fluid flow rate on the channel parameters and the frequency of oscillations of the piezoelectric actuators is determined by the method of factorial experiment. The parameters preventing heat backflow have been determinate, which makes it possible to use a device for supplying coolant to a microgripper cooling system.

Quadrature method for broadband measurement of microwave path parameters

A mathematical model has been developed for the procedure for broadband automatic measurement of the complex reflection coefficient and power level in the microwave path based on the quadrature measurement method. Analytical expressions are obtained for the quadrature components at the outputs of a quadrature demodulator connected with a switch to two non-directional measuring probes for the case of an unmatched microwave path. A modified system of nonlinear equations with respect to measured values was formed and solved, which allows setting zero assumptions. A block diagram of a broadband device for built-in automatic control of microwave channel parameters has been developed, which implements the developed measurement procedure and the solution of a system of measurement equations to determine the current values of the power level factor, as well as the modulus and argument of the complex reflection coefficient.

Impact of receiver imbalances on the security of continuous variables quantum key distribution

Continuous-variable quantum key distribution (CV-QKD) provides a theoretical unconditionally secure solution to distribute symmetric keys among users in a communication network. However, the practical devices used to implement these systems are intrinsically imperfect, and, as a result, open the door to eavesdropper attacks. In this work, we show the impact of receiver device imperfections on the estimated channel parameters, performance and security of a CV-QKD system. The presented results show that, due to the erroneously estimated channel parameters, non-monitored imbalances can pose a security risk or even reduce the system’s performance. Our results show the importance of monitoring these imbalances and hint at the possibility of compensating for some receiver imbalances by tuning other components.

Variational Sparse Bayesian Learning for Estimation of Gaussian Mixture Distributed Wireless Channels

In this paper, variational sparse Bayesian learning is utilized to estimate the multipath parameters for wireless channels. Due to its flexibility to fit any probability density function (PDF), the Gaussian mixture model (GMM) is introduced to represent the complicated fading phenomena in various communication scenarios. First, the expectation-maximization (EM) algorithm is applied to the parameter initialization. Then, the variational update scheme is proposed and implemented for the channel parameters’ posterior PDF approximation. Finally, in order to prevent the derived channel model from overfitting, an effective pruning criterion is designed to eliminate the virtual multipath components. The numerical results show that the proposed method outperforms the variational Bayesian scheme with Gaussian prior in terms of root mean squared error (RMSE) and selection accuracy of model order.