6G New Multiple Access Technology

As a basic technology at physical layer of mobile communications,non-orthogonal multiple access has been attracting wide attention across the academia and the industry.During the standardization of the fifth-generation(5G)of mobile communications,3GPP conducted preliminary study on non-orthogonal multiple access without reaching the consensus to standardize the technology.

Toward Wisdom-Evolutionary and Primitive-Concise 6G:A New Paradigm of Semantic Communication Networks

The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G networks.Such hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks,calling for revolutionary theories and technological innovations.To this end,we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network(WePCN)vision for the Ubiquitous-X 6G network.In particular,we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework,namely semantic base,and then establishing an intelligent and efficient semantic communication(IE-SC)network architecture.In the IE-SC architecture,a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer,network protocol layer,and application-intent layer via semantic information flows.The proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in 6G.It features a lower bandwidth requirement,less redundancy,and more accurate intent identification.We also present a brief review of recent advances in semantic communications and highlight potential use cases,complemented by a range of open challenges for 6G.

Energy Theft Detection in Smart Grids:Taxonomy,Comparative Analysis,Challenges,and Future Research Directions

Electricity theft is one of the major issues in developing countries which is affecting their economy badly.Especially with the introduction of emerging technologies,this issue became more complicated.Though many new energy theft detection(ETD)techniques have been proposed by utilising different data mining(DM)techniques,state&network(S&N)based techniques,and game theory(GT)techniques.Here,a detailed survey is presented where many state-of-the-art ETD techniques are studied and analysed for their strengths and limitations.Three levels of taxonomy are presented to classify state-of-the-art ETD techniques.Different types and ways of energy theft and their consequences are studied and summarised and different parameters to benchmark the performance of proposed techniques are extracted from literature.The challenges of different ETD techniques and their mitigation are suggested for future work.It is observed that the literature on ETD lacks knowledge management techniques that can be more effective,not only for ETD but also for theft tracking.This can help in the prevention of energy theft,in the future,as well as for ETD.

Breast Cancer Detection Using an Ultrashort-Pulse Radar System in Synthetic Breast Phantom Model

Using ultrashort-pulse radar with compact vivaldi antennas, the simulation experiment of breast cancer detection has been performed in a synthetic breast phantom. Two metallic balls with 9 mm and 6 mm in diameter are used as tumors in our experiment. The image reconstructions of the breast models with tumors using reflection data have been presented by a confocal microwave imaging technique. The method can be used for a pulse compression technique to reflected waves for clear image formation.

Development of Millimeter-Wave Radio-over-Fiber Technology

Millimeter-wave radio-over-fiber techno- logy demonstrates the potential for providing wireless broad-band service in the next generation wireless communication system.Optical generation of millimeter-wave signal is one of the most important technologies of millimeter-wave radio-over-fiber system.The virtues and shortcomings of some ways of optical generation of millimeter-wave signal are discussed.Then optical millimeter-wave signal transmission perfor- mance is described.Finally,an overview of the millimeter-wave radio-over-fiber system is given.It is suggested that the millimeter-wave radio-over-fiber technology should be paid more attention,especially for modulators for optical generation of millimeter-wave signal and radio-over-fiber system.

Many-Objective Optimization-Based Task Scheduling in Hybrid Cloud Environments

Due to the security and scalability features of hybrid cloud architecture,it can bettermeet the diverse requirements of users for cloud services.And a reasonable resource allocation solution is the key to adequately utilize the hybrid cloud.However,most previous studies have not comprehensively optimized the performance of hybrid cloud task scheduling,even ignoring the conflicts between its security privacy features and other requirements.Based on the above problems,a many-objective hybrid cloud task scheduling optimization model(HCTSO)is constructed combining risk rate,resource utilization,total cost,and task completion time.Meanwhile,an opposition-based learning knee point-driven many-objective evolutionary algorithm(OBL-KnEA)is proposed to improve the performance of model solving.The algorithm uses opposition-based learning to generate initial populations for faster convergence.Furthermore,a perturbation-based multipoint crossover operator and a dynamic range mutation operator are designed to extend the search range.By comparing the experiments with other excellent algorithms on HCTSO,OBL-KnEA achieves excellent results in terms of evaluation metrics,initial populations,and model optimization effects.

Towards Collaborative Robotics in Top View Surveillance:A Framework for Multiple Object Tracking by Detection Using Deep Learning

Collaborative Robotics is one of the high-interest research topics in the area of academia and industry.It has been progressively utilized in numerous applications,particularly in intelligent surveillance systems.It allows the deployment of smart cameras or optical sensors with computer vision techniques,which may serve in several object detection and tracking tasks.These tasks have been considered challenging and high-level perceptual problems,frequently dominated by relative information about the environment,where main concerns such as occlusion,illumination,background,object deformation,and object class variations are commonplace.In order to show the importance of top view surveillance,a collaborative robotics framework has been presented.It can assist in the detection and tracking of multiple objects in top view surveillance.The framework consists of a smart robotic camera embedded with the visual processing unit.The existing pre-trained deep learning models named SSD and YOLO has been adopted for object detection and localization.The detection models are further combined with different tracking algorithms,including GOTURN,MEDIANFLOW,TLD,KCF,MIL,and BOOSTING.These algorithms,along with detection models,help to track and predict the trajectories of detected objects.The pre-trained models are employed;therefore,the generalization performance is also investigated through testing the models on various sequences of top view data set.The detection models achieved maximum True Detection Rate 93%to 90%with a maximum 0.6%False Detection Rate.The tracking results of different algorithms are nearly identical,with tracking accuracy ranging from 90%to 94%.Furthermore,a discussion has been carried out on output results along with future guidelines.

DOA and Power Estimation Using Genetic Algorithm and Fuzzy Discrete Particle Swarm Optimization

Aiming to reduce the computational costs and converge to global optimum, a novel method is proposed to solve the optimization of a cost function in the estimation of direction of arrival （DOA）. In this method, a genetic algorithm （GA） and fuzzy discrete particle swarm optimization （FDPSO） are applied to optimize the direction of arrival and power parameters of the mode simultaneously. Firstly, the GA algorithm is applied to make the solution fall into the global searching. Secondly, the FDPSO method is utilized to narrow down the search field. In FDPSO, a chaotic factor and a crossover method are added to speed up the convergence. This approach has been demonstrated through some computational simulations. It is shown that the proposed algorithm can estimate both the DOA and the powers accurately. It is more efficient than some present methods, such as the Newton-like algorithm, Akaike information critical （AIC）, particle swarm optimization （PSO）, and genetic algorithm with particle swarm optimization （GA-PSO）.

A Fast-Speed Pulse Detector Based on N-Type Si-Schottky Diode via Tuning Circuit

A fast-speed pulse detector based on n-type Si-Sehottky diode mounted in the waveguide is investigated. The relation of the fast-speed pulse detector between response time and 3 dB bandwidth is analyzed. By adopting the tunable circuit, the matched bandwidth is achieved as wide as possible. Experi- mental results show that the pulse response time of the detector is less than 150 ps within random carrier signal 500 MHz bandwidth range between 35 GHz to 39 GHz via tuning circuit. The detector is very easy to operate because it does not need bias current or synch-pulse source.

A 10-MHz SOI-Based Face Shear Square Micromechanical Resonator

A 10-MHz face shear （FS） square micro- mechanical resonator based on silicon-on-insulator （SO1） technology is presented in this paper. In order to examine the improvement of quality factor as well as motional resistance Rx in this structure, the center-stem anchor is employed in this study. The benefit of anchoring the square in the center, which is the nodal point, is that the energy losses through the anchor can be minimized. Hence, a quality factor value of 2.0 million and the motional resistance of 8.2 k~ can be obtained with an FS mode resonator via finite element （FE） simulation. The results show the significance of the FS mode in this design, not only in its structure but also in its square-extensional mode and Lame-mode. Additionally, an SOI-based fabrication process is proposed to support the design.

Influence of surface roughness on surface plasmon resonance phenomenon of gold film

We experimentally investigate the effects of the surface roughness of gold thin films on the properties of surface plasmon resonance. By annealing at different temperatures, film samples with different surface morphologies are obtained. Specifically, due to the diffusion of the gold atoms towards the films＇ surface, the surface root- mean-square roughness decreases with the increasing annealing temperature. Then, we measure the surface plasmon resonance of the samples. The results show that the resonance angle of the surface plasmon resonance is sensitive to the root-mean-square roughness, and it gradually decreases by reducing the surface root-mean-square roughness.