Reliable and Energy-Efficient LEO Satellite Communication with IR-HARQ via Power Allocation.

This paper examines reliable and energy-efficient transmission in low earth orbit (LEO) satellite communication systems. In particular, we analyze the link transmission characteristics of the LEO satellite to the ground user and model the channel as a combination of large-scale fading and small-scale fading. Based on this, we consider an incremental redundancy hybrid automatic repeat request (IR-HARQ) technique with a variable-power allocation method, and we call it the IR-HARQ-VPA scheme. In this method, the outage probability after each IR-HARQ round can be obtained through numerical integration based on the fast Fourier transform (NI-FFT). This method is suitable for any number of HARQ transmission rounds and can improve the accuracy compared with previous approximation methods. In addition, variable-power allocation based on the genetic algorithm (VPA-GA) is introduced to reduce the energy consumption. The simulation results show that the proposed IR-HARQ-VPA scheme cannot only meet the requirements of transmission reliability but also achieves higher energy efficiency than IR-HARQ with equal power (IR-HARQ-EP) transmission and a previously proposed variable-power allocation method. Moreover, the simulation results in a LEO satellite communication window also confirm the effectiveness of the proposed IR-HARQ-VPA scheme.

Keypoint-Based Disentangled Pose Network for Category-Level 6-D Object Pose Tracking.

Category-level 6-D object pose tracking is very challenging in the field of 3-D computer vision. Keypoint-based object pose estimation has demonstrated its effectiveness in dealing with it. However, current approaches first estimate the keypoints through a neural network and further compute the interframe pose change via least-squares optimization. They estimate rotation and translation in the same way, ignoring the differences between them. In this work, we propose a keypoint-based disentangled pose network, which disentangles the 6-D object pose change to 3-D rotation and 3-D translation. Specifically, the translation is directly estimated by the network and the rotation is indirectly calculated by singular value decomposition according to the keypoints. Extensive experiments on the NOCS-REAL275 dataset demonstrate the superiority of our method.

Design of mmWave Directional Antenna for Enhanced 5G Broadcasting Coverage.

5G mmWave broadcasting is considered to be the main method of future broadcasting. However, the mmWave transmission has a large space loss, especially in tunnels. In order to compensate for the attenuation of the broadcast signal, a directional horn antenna is designed in this paper. Substrate integrated waveguide (SIW) technology, dual-element arrays and extension structures are used to improve the antenna structure and achieve good directional characteristics. The multi-objective genetic algorithm (MOGA) is used to optimize the antenna parameters and improve optimization efficiency. Ultimately, the whole antenna was 28.2 mm in length and 28.6 mm in width, and the FR4 material, with a relative permittivity of 4.4, was used as a dielectric plate. The maximum gain of the antenna is 8.06 dB, and the bandwidth with gain greater than 6.5 dB is nearly 2 GHz. Antenna performance simulation and test results show that the extended semicircular structure is beneficial in enhancing the directional radiation of the antenna. This provides a reference method for directional antennas applied to 5G millimeter wave bands to increase gain and narrow beams.

A Dynamic Access Probability Adjustment Strategy for Coded Random Access Schemes.

In this paper, a dynamic access probability adjustment strategy for coded random access schemes based on successive interference cancellation (SIC) is proposed. The developed protocol consists of judiciously tuning the access probability, therefore controlling the number of transmitting users, in order to resolve medium access control (MAC) layer congestion states in high load conditions. The protocol is comprised of two steps: Estimation of the number of transmitting users during the current MAC frame and adjustment of the access probability to the subsequent MAC frame, based on the performed estimation. The estimation algorithm exploits a posteriori information, i.e., available information at the end of the SIC process, in particular it relies on both the frame configuration (residual number of collision slots) and the recovered users configuration (vector of recovered users) to effectively reduce mean-square error (MSE). During the access probability adjustment phase, a target load threshold is employed, tailored to the packet loss rate in the finite frame length case. Simulation results revealed that the developed estimator was able to achieve remarkable performance owing to the information gathered from the SIC procedure. It also illustrated how the proposed dynamic access probability strategy can resolve congestion states efficiently.

[Special decorrelation technique used for DWT-based hyperspectral image compression].

Hyperspectral images are massive data consisting of hundreds of spectral bands and have been used in a large number of applications. With growth of spectral resolution and spatial resolution of hyperspectral data, data size increases rapidly. How to effectively compress hyperspectral image becomes a key problem that affects the development and popularization of hyperspectral image. Recently, DWT-based methods have been proved promising for hyperspectral image. But their performances are restricted because it is difficult for them to efficiently take advantage of the various properties of hyperspectral image. For the traditional wavelet transform, the specific properties of hyperspectral images are basically utilized by corresponding to characteristics of wavelet coefficients. So the present paper proposes a new DWT-based method using decorrelation technique according to the spectral characters of hyperspectral image. Block predictive coding is designed to remove the spectral correlation as well as spatial correlation simultaneously and is applied into the DWT-based method. Firstly, hyperspectral image is divided into several image blocks. The bands in a single block possess high spectral correlation. Afterwards, it is deduced that bands of a single block tend to be proportional in altitudes. Bands prediction, which is done in the range of each block respectively, is designed according to this and others characteristics of hyperspectral images. Finally, reference bands of block prediction and the deviation data obtained after block prediction are compressed by 2D-DWT algorithm and 3D-DWT algorithm respectively. Experiment results indicate that compared with the well known techniques the proposed method can significantly improve SNR and PSNR performance, even to 4.2 dB (compared with AT-3DSPIHT algorithm). And the code efficiency at low bit rates is also competitive.