Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands

Background Robot grasping encompasses a wide range of research areas;however, most studies have been focused on the grasping of only stationary objects in a scene;only a few studies on how to grasp objects from a user's hand have been conducted. In this paper, a robot grasping algorithm based on deep reinforcement learning (RGRL) is proposed. Methods The RGRL takes the relative positions of the robot and the object in a user's hand as input and outputs the best action of the robot in the current state. Thus, the proposed algorithm realizes the functions of autonomous path planning and grasping objects safely from the hands of users. A new method for improving the safety of human-robot cooperation is explored. To solve the problems of a low utilization rate and slow convergence of reinforcement learning algorithms, the RGRL is first trained in a simulation scene, and then, the model para-meters are applied to a real scene. To reduce the difference between the simulated and real scenes, domain randomization is applied to randomly change the positions and angles of objects in the simulated scenes at regular intervals, thereby improving the diversity of the training samples and robustness of the algorithm. Results The RGRL's effectiveness and accuracy are verified by evaluating it on both simulated and real scenes, and the results show that the RGRL can achieve an accuracy of more than 80% in both cases. Conclusions RGRL is a robot grasping algorithm that employs domain randomization and deep reinforcement learning for effective grasping in simulated and real scenes. However, it lacks flexibility in adapting to different grasping poses, prompting future research in achieving safe grasping for diverse user postures.

OTFS-Based Efficient Handover Authentication Scheme with Privacy-Preserving for High Mobility Scenarios

Handover authentication in high mobility scenarios is characterized by frequent and shortterm parallel execution.Moreover,the penetration loss and Doppler frequency shift caused by high speed also lead to the deterioration of network link quality.Therefore,high mobility scenarios require handover schemes with less handover overhead.However,some existing schemes that meet this requirement cannot provide strong security guarantees,while some schemes that can provide strong security guarantees have large handover overheads.To solve this dilemma,we propose a privacy-preserving handover authentication scheme that can provide strong security guarantees with less computational cost.Based on Orthogonal Time Frequency Space(OTFS)link and Key Encapsulation Mechanism(KEM),we establish the shared key between protocol entities in the initial authentication phase,thereby reducing the overhead in the handover phase.Our proposed scheme can achieve mutual authentication and key agreement among the user equipment,relay node,and authentication server.We demonstrate that our proposed scheme can achieve user anonymity,unlinkability,perfect forward secrecy,and resistance to various attacks through security analysis including the Tamarin.The performance evaluation results show that our scheme has a small computational cost compared with other schemes and can also provide a strong guarantee of security properties.

Reinforcement Learning-Based Handover Scheme with Neighbor Beacon Frame Transmission

Mobility support to change the connection from one access point(AP)to the next(i.e.,handover)becomes one of the important issues in IEEE 802.11 wireless local area networks(WLANs).During handover,the channel scanning procedure,which aims to collect neighbor AP(NAP)information on all available channels,accounts for most of the delay time.To reduce the channel scanning procedure,a neighbor beacon frame transmission scheme(N-BTS)was proposed for a seamless handover.N-BTS can provide a seamless handover by removing the channel scanning procedure.However,N-BTS always requires operating overhead even if there are few mobile stations(MSs)for the handover.Therefore,this paper proposes a reinforcement learning-based handover scheme with neighbor beacon frame transmission(MAN-BTS)to properly consider the use of N-BTS.The optimization equation is defined to maximize the expected reward tofind the optimal policy and is solved using Q-learning.Simulation results show that the proposed scheme outperforms the comparison schemes in terms of the expected reward.

Dynamic MmWave Channel Reconstruction of MIMO OTA Testing for Handover Scenarios

The evaluation of handover performance is essential for ensuring seamless user experience under innovative application scenarios in the fifth generation(5G)and beyond era,including autonomous driving,mobile augmented and virtual reality.However,due to the hardware constrains of a sectored multiprobe anechoic chamber(SMPAC),switching among multiple channel models is of low precision with a high cost in traditional over-the-air(OTA)test solutions.In this paper,we present an efficient and repeatable emulation strategy to reconstruct dynamic millimeter-wave(mm Wave)channels in laboratories for multiple-input multiple-output(MIMO)mobile devices.Firstly,we propose a novel evaluation metric,called average power angular spectrum similarity percentage(APSP),which minimizes the unexpected impact induced by the indefinite condition of adaptive antenna arrays in mm Wave terminals during handover process.Moreover,we propose a partitioned probe configuration strategy by designing a beam directivitybased switching circuit,which enables quick changes of probe configurations in SMPAC.Simulation results demonstrate the effectiveness of the proposed algorithms,thus providing a guideline for the reconstruction of the dynamic channel in different scenarios with resource limitation.

An Intelligent Admission Control Scheme for Dynamic Slice Handover Policy in 5G Network Slicing

5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and dynamic.Slicing enables service providers to develop various network slice architectures.As users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different expectations.This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks.Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies.Therefore,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover.The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being dropped.Hence,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity.Moreover,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces.The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.

Fuzzy Logic Based Handover Authentication in 5g Telecommunication Heterogeneous Networks

Under various deployment circumstances,fifth-generation(5G)telecommunications delivers improved network compound management with fast communication channels.Due to the introduction of the Internet of Things(IoT)in data management,the majority of the ultra-dense network models in 5G networks frequently have decreased spectral efficiency,weak handover management,and vulnerabilities.The majority of traditional handover authentication models are seriously threatened,making them vulnerable to a variety of security attacks.The authentication of networked devices is the most important issue.Therefore,a model that incorporates the handover mechanism and authentication model must be created.This article uses a fuzzy logic model to create a handover and key management system that focuses on cloud handover management and authentication performance.In order to decrease delays in 5G networks,the fuzzy logic is built with multiple criteria that aim to reduce the number of executed handovers and target cell selection.The simulation is run to evaluate the model’s performance in terms of latency,spatial complexity,and other metrics related to authentication attack validation.

Six Generation Load Cells Solution Based Congestion Management Control Purpose

Several assessing efforts are approved making both communication and information technologies available.In addition to being a part of universal access and service,we aim at assessing the impact of radio access technologies on universal access indicators.The proposed work demonstrates the possibility of inter-working of all existing Radio Access Technologies(RATs),in a limited area presented in the Six Generation Radio Resources Allocation(6 G-A)network.We propose a solution for the Vertical hand Over(VHO)in 6 G-A heterogeneous system,that adopts Media Independent Handover(MIH)protocol to benefit between different used technologies in a direct communication firstly and facilitate,in addition,coordination between congestion controlmechanisms with themobilitymanagement entity.The mathematical model has been developed to deal with locality coverage and broadband needs,based on a methodological approach consisting in integrating parameters linked to access index through radio technologies.This approach has been applied.In practice,it has contributed to highlighting its relative simplicity of implementation,but it is not enough for sixgeneration system radio access networks.The congestion control mechanism is integrated within the vertical handover process,this proposition is used to prevent each presented congestion state.The media independent handover IS equipment,as well as six G-A equipment which are both considered as the whole architecture key equipment,perform and guaranty this related process.Efficient communication is established besides information exchange between various technologies.Achieved evaluation results are performant and prove that proposed mechanisms are efficient.Both simulation and tests results are accomplished.

BE-RPL:Balanced-load and Energy-efficient RPL

Internet of Things(IoT)empowers imaginative applications and permits new services when mobile nodes are included.For IoT-enabled low-power and lossy networks(LLN),the Routing Protocol for Low-power and Lossy Networks(RPL)has become an established standard routing protocol.Mobility under standard RPL remains a difficult issue as it causes continuous path disturbance,energy loss,and increases the end-to-end delay in the network.In this unique circumstance,a Balanced-load and Energy-efficient RPL(BE-RPL)is proposed.It is a routing technique that is both energy-efficient and mobility-aware.It responds quicker to link breakage through received signal strength-based mobility monitoring and selecting a new preferred parent reactively.The proposed system also implements load balancing among stationary nodes for leaf node allocation.Static nodes with more leaf nodes are restricted from participating in the election for a new preferred parent.The performance of BE-RPL is assessed using the COOJA simulator.It improves the energy use,network control overhead,frame acknowledgment ratio,and packet delivery ratio of the network.

Recognizing Early Warning Signs (EWS) in Patients Is Critically Important

Introduction: Monitoring vital signs is a basic indicator of a patient’s health status and allows prompt detection of delayed recovery or adverse effects and early intervention. Patients with adverse events during hospitalization often display clinical decline for several hours before the event is observed. Non-critical care Nurses’ inconsistent recognition and response to patient deterioration lead to an increase in the length of hospital stay, unexpected admissions to the ICU, and increased morbidity and mortality. Aim: The study aimed to assess the factors that facilitate or impede the detection of early warning signs among adult patients hospitalized in tertiary care settings. Training should be provided to improve nurses’ knowledge, practice and attitude toward early warning signs of deteriorating patients leading to enhanced clinical judgment, skills and decision-making in addressing alerts. Methodology: A literature search was carried out in various databases;these were Cumulative Index to Nursing and Allied Health Literature (CINHAL), Google Scholar, PubMed, Science Direct, and Sage. The search area was narrowed from 2017 to 2022. The keywords used were “prevalence” AND “unplanned ICU admission”, “the importance of early warning signs” “outcome failure in rescue” “patient deterioration, communication” “improvement in early detection” AND “patient outcome admission” AND “early warning signs” AND “Pakistan”. After the analysis process, around 33 articles that met the inclusion criteria and were most relevant to the scope and context of the current study were considered. Conclusion: Most of the studies had reviewed literature in a qualitative retrospective observational study, content analysis, mixed method, and quasi-experimental study. The literature review identified that long hours of shift, nurse staffing levels, missed vital signs, lack of nursing training and education, and communication impact nurses’ ability to recognize and respond to early warning signs.

Handover研究综述

随着无线网络技术的快速发展,怎样使用户正在进行的网络服务在用户移动过程中不被中断,使正在进行的服务能够在基站之间平滑过渡一直受到人们的广泛关注。设计一种高效、稳定的服务切换算法成为当前服务切换领域研究的热点问题。本文详细地介绍了现有部分服务切换算法和协议,以及相应算法的优点和缺点,并对服务切换算法进行了分类。文中对服务切换领域当前研究的现状进行了说明,并在讨论中介绍了今后的研究方向。

A Minimum Cost Handover Algorithm for Mobile Satellite Networks

For mobile satellite networks, an appropriate handover scheme should be devised to shorten handover delay with optimized application of network resources. By introducing the handover cost model of service, this article proposes a rerouting triggering scheme for path optimization after handover and a new minimum cost handover algorithm for mobile satellite networks. This algorithm ensures the quality of service （QoS） parameters, such as delay, during the handover and minimizes the handover costs. Simulation indicates that this algorithm is superior to other current algorithms in guaranteeing the QoS and decreasing handover costs.

语音连续性技术SRVCC性能分析与优化

本文主要研究候选技术SRVCC在LTE(TD-LTE和LTE-FDD)与TD-SCDMA和GSM系统之间互操作时,语音业务保持连续性的技术性能及可能的优化方案。通过对SRVCC流程参考实验数据和目前3GPP标准化的SRVCC的主要问题(切换时延长、信令流程复杂等)的深入研究,初步探讨这些问题的优化思路,最后介绍了SRVCC优化技术的国际标准化进展。

一种应用于Mobile IPv6中切换算法的分析与改进

MobileIPv6为全球的移动数据通信提供了一个平台。当一个通信主机在不同的子网间移动时,希望在进行切换的时间段内仍能保持通信的连贯和通信的性能。该文介绍了一个切换算法,分析了它的不足,并提出了自己的改进算法。

A long-term-based handover decision algorithm for dense macro-femto coexistence networks

For the dense macro-femto coexistence networks scenario, a long-term-based handover（LTBH） algorithm is proposed. The handover decision algorithm is jointly determined by the angle of handover（AHO） and the time-tostay（TTS） to reduce the unnecessary handover numbers.First, the proposed AHO parameter is used to decrease the computation complexity in multiple candidate base stations（CBSs） scenario. Then, two types of TTS parameters are given for the fixed base stations and mobile base stations to make handover decisions among multiple CBSs. The simulation results show that the proposed LTBH algorithm can not only maintain the required transmission rate of users, but also effectively reduce the unnecessary numbers of handover in the dense macro-femto networks with the coexisting mobile BSs.

Dynamic channel reservation scheme based on priorities in LEO satellite systems

According to low earth orbit（LEO） satellite systems with users of different levels, a dynamic channel reservation scheme based on priorities is proposed. Dynamic calculation of the thresholds for reserved channels is the key of this strategy. In order to obtain the optimal thresholds, the traffic is predicted based on the high-speed deterministic movement property of LEO satellites firstly. Then, a channel allocation model based on Markov is established. Finally, the solution of the model is obtained based on the genetic algorithm. Without user location, this strategy effectively reduces handover failures and improves channel utilization by adjusting dynamically the thresholds according to traffic conditions. The simulation results show that the system＇s overall quality of service can be improved by this strategy.

Position-assisted fast handover schemes for LTE-advanced network under high mobility scenarios

Two position-assisted fast handover schemes, scheme A and scheme B, for LTE-A system under very high mobility scenarios, are proposed, together with their performance evaluation. Scheme A is designed to reduce handover delay by making handover preparation before handover starts. Scheme B aims at reducing unnecessary handovers and improving handover success rate, by calculating the geographically best target handover cell, which makes it easier for mobile terminals to access the target cell. A system level simulation is conducted to evaluate the performance of these two schemes. It is shown that, scheme A could reduce inter-site handover delay by about 50 ms, while scheme B could cut down nearly 50% of all handovers when time-to-trigger （TTT） is 0 ms. Besides, as TTT gets larger, Scheme B has much better success rate.

A Trajectory Prediction Based Intelligent Handover Control Method in UAV Cellular Networks

The airborne base station(ABS) can provide wireless coverage to the ground in unmanned aerial vehicle(UAV) cellular networks.When mobile users move among adjacent ABSs,the measurement information reported by a single mobile user is used to trigger the handover mechanism.This handover mechanism lacks the consideration of movement state of mobile users and the location relationship between mobile users,which may lead to handover misjudgments and even communication interrupts.In this paper,we propose an intelligent handover control method in UAV cellular networks.Firstly,we introduce a deep learning model to predict the user trajectories.This prediction model learns the movement behavior of mobile users from the measurement information and analyzes the positional relations between mobile users such as avoiding collision and accommodating fellow pedestrians.Secondly,we propose a handover decision method,which can calculate the users' corresponding receiving power based on the predicted location and the characteristic of air-to-ground channel,to make handover decisions accurately.Finally,we use realistic data sets with thousands of non-linear trajectories to verify the basic functions and performance of our proposed intelligent handover controlmethod.The simulation results show that the handover success rate of the proposed method is 8% higher than existing methods.

Packet Cache-Forward Method Based on Improved Bayesian Outlier Detection for Mobile Handover in Satellite Networks

In this paper, we propose a Packet Cache-Forward(PCF) method based on improved Bayesian outlier detection to eliminate out-of-order packets caused by transmission path drastically degradation during handover events in the moving satellite networks, for improving the performance of TCP. The proposed method uses an access node satellite to cache all received packets in a short time when handover occurs and forward them out in order. To calculate the cache time accurately, this paper establishes the Bayesian based mixture model for detecting delay outliers of the entire handover scheme. In view of the outliers' misjudgment, an updated classification threshold and the sliding window has been suggested to correct category collections and model parameters for the purpose of quickly identifying exact compensation delay in the varied network load statuses. Simulation shows that, comparing to average processing delay detection method, the average accuracy rate was scaled up by about 4.0%, and there is about 5.5% cut in error rate in the meantime. It also behaves well even though testing with big dataset. Benefiting from the advantage of the proposed scheme in terms of performance, comparing to conventional independent handover and network controlled synchronizedhandover in simulated LEO satellite networks, the proposed independent handover with PCF eliminates packet out-of-order issue to get better improvement on congestion window. Eventually the average delay decreases more than 70% and TCP performance has improved more than 300%.

Handover algorithm for multiple networks based on Bayesian decision

An improved vertical handover algorithm for multiple networks based on Bayesian decision is proposed. Firstly, the handover probability distribution is established considering multiple conditions including signal strength, bit error rate, blocking probability and user demands, and accordingly the prior handover probability is calculated. Secondly, the posterior probability based on Bayesian decision algorithm is got. Finally, the optimal access network is selected according to the decision strategy based on posterior probability. Simulation results indicate that the proposed algorithm not only effectively achieves vertical handover among WLAN, WiMAX and LTE with the least number of handovers, but also keeps high average network load, which can provide the users with good service quality.

Spot beam handover trigger and channel allocation scheme in GEO mobile satellite communication

An effective spot beam handover trigger and channel allocation scheme is proposed for GEO mobile satellite communication based on its characteristic and application. By using both signal strength and terminal location information, necessary handover is triggered promptly and accurately to reduce the negative effect of long signaling delay. Then handover decision is made with the handover queuing and channel allocation strategy. An adaptive channel resource allocation scheme is considered to optimize resource utilization with guarantee of emergency communication, which is significant for emergency rescue and disaster relief. Simulation results show that the proposed scheme prevents unnecessary handover effectively and has favorable adaptability to emergent requirement of satellite communication.