Effective Capacity of URLLC over Parallel Fading Channels with Imperfect Channel State Information

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.

Multi-User Semantic Fusion for Semantic Communications over Degraded Broadcast Channels

Degraded broadcast channels(DBC) are a typical multiuser communication scenario, Semantic communications over DBC still lack in-depth research. In this paper, we design a semantic communications approach based on multi-user semantic fusion for wireless image transmission over DBC. The transmitter extracts semantic features for two users separately and then effectively fuses them for broadcasting by leveraging semantic similarity. Unlike traditional allocation of time, power, or bandwidth, the semantic fusion scheme can dynamically control the weight of the semantic features of the two users to balance their performance. Considering the different channel state information(CSI) of both users over DBC,a DBC-Aware method is developed that embeds the CSI of both users into the joint source-channel coding encoder and fusion module to adapt to the channel.Experimental results show that the proposed system outperforms the traditional broadcasting schemes.

Intelligent Network Selection for Data Offloading in 5G Multi-Radio Heterogeneous Networks

In next generation networks, multiradio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi(IFW) small cells have been introduced by 3GPP to offload data from cellular networks recently. These IFW cells are multi-mode capable(i.e., both licensed bands via cellular interface and unlicensed bands via WiFi interface). Therefore how to offload data effectively has become one of the most significant discussions in 5G Multi-Radio Heterogeneous Network. So far, most researches mainly focus on the generality of UEs, few attention has been paid to UEs' individual requirements. Considering UE's preference vary from individual to individual, in this paper, we present an UE preference-aware network selection scheme for mobile data offloading. It intelligently supports the distribution of heterogeneous classes of services, considers different types of UEs and delay-tolerant flows, and handles the mobility of UEs. The simulation results show the superiority of the proposed algorithm in user fairness, enhanced capacity and energy saving maximization.

Introduction to Point Cloud Compression

Characterized by geometry and photometry attributes, point cloud has been widely applied in the immersive services of various 3Dobjects and scenes. The development of even more precise capture devices and the increasing requirements for vivid rendering in-evitably induce huge point capacity, thus making the point cloud compression a demanding issue. In this paper, we introduce sev-eral well-known compression algorithms in the research area as well as the boosting industry standardization works. Specifically,based on various applications of this 3D data, we summarize the static and dynamic point cloud compression, both including irreg-ular geometry and photometry information that represent the spatial structure information and corresponding attributes, respective-ly. In the end, we conclude the point cloud compression as a promising topic and discuss trends for future works.

Introduction to AVS2 Scene Video Coding Techniques

The second generation Audio Video Coding Standard (AVS2) is the most recent video coding standard. By introducing several new coding techniques, AVS2 can provide more efficient compression for scene videos such as surveillance videos, conference videos, etc. Due to the limited scenes, scene videos have great redundancy especially in background region. The new scene video coding techniques applied in AVS2 mainly focus on reducing redundancy in order to achieve higher compression. This paper introduces several important AVS2 scene video coding techniques. Experimental results show that with scene video coding tools, AVS2 can save nearly 40%BD?rate (Bj?ntegaard?Delta bit?rate) on scene videos.

Edge Intelligence for 6G Networks

With the rapid development of smart terminals and infrastructures,as well as diversified applications(e.g.,autonomous driving,virtual and augmented reality,space-air-ground integrated networks)with colorful demands,current networks(e.g.,4G and 5G networks)may not be well suited to the requirements of novel applications and services.Recently,efforts from both the industry and academia have been made on the research into 6G networks,artificial intelligence(AI)will play a pivotal role in the design and optimization of 6G networks.

A Novel Energy Efficient MAC Protocol for Wireless Body Area Network

Wireless Body Area Network(WBAN) is the most promising technology in e-health applications.Energy efficiency stands out as the paramount issue for WBAN.In this paper,an energy efficient MAC protocol named Quasi-Sleep-Preempt-Supported(QSPS) is proposed.The protocol is mainly TDMA-based:nodes transmit packets in the allocated slots,while entering the Q-Sleep mode in other slots.Moreover,for a node with emergency packet,it can broadcast a special designed Awakening Message to wake up the whole network and preempts the right to use the current slot to transmit that emergency packet,thus decreasing delay.Compared with relevant protocols,QS-PS can achieve high energy efficiency and decrease the delay of both normal packets and emergency packets.

Psycho-visual modulation based information display:introduction and survey

Industry and academia have been making great efforts in improving refresh rates and resolutions of display devices to meet the ever increasing needs of consumers for better visual quality.As a result,many modem displays have spatial and temporal resolutions far beyond the discern capability of human visual systems.Thus,leading to the possibility of using those display-eye redundancies for innovative usages.Tempo-ral/spatial psycho-visual modulation(TPVM/SPVM)was proposed to exploit those redundancies to generate multiple visual percepts for different viewers or to transmit non-visual data to computing devices without affecting normal viewing.This paper reviews the STPVM technology from both conceptual and algorithmic perspectives,with exemplary applications in multiview display,display with visible light communication,etc.Some possible future research directions are also identified.

IMAGE QUALITY ASSESSMENT BASED ON CONTOUR AND REGION

Image Quality Assessment （IQA） is a fundamental problem in image processing. It is a common principle that human vision is hierarchical： we first perceive global structural information such as contours then focus on local regional details if necessary. Following this principle, we propose a novel framework for IQA by quantifying the degenerations of structural information and region content separately, and mapping both to obtain the objective score. The structural information can be obtained as contours by contour detec- tion techniques. Experiments are conducted to demonstrate its performance in comparison with multiple state-of-the-art methods on two large scale datasets.