CAW-YOLO:Cross-Layer Fusion and Weighted Receptive Field-Based YOLO for Small Object Detection in Remote Sensing

In recent years,there has been extensive research on object detection methods applied to optical remote sensing images utilizing convolutional neural networks.Despite these efforts,the detection of small objects in remote sensing remains a formidable challenge.The deep network structure will bring about the loss of object features,resulting in the loss of object features and the near elimination of some subtle features associated with small objects in deep layers.Additionally,the features of small objects are susceptible to interference from background features contained within the image,leading to a decline in detection accuracy.Moreover,the sensitivity of small objects to the bounding box perturbation further increases the detection difficulty.In this paper,we introduce a novel approach,Cross-Layer Fusion and Weighted Receptive Field-based YOLO(CAW-YOLO),specifically designed for small object detection in remote sensing.To address feature loss in deep layers,we have devised a cross-layer attention fusion module.Background noise is effectively filtered through the incorporation of Bi-Level Routing Attention(BRA).To enhance the model’s capacity to perceive multi-scale objects,particularly small-scale objects,we introduce a weightedmulti-receptive field atrous spatial pyramid poolingmodule.Furthermore,wemitigate the sensitivity arising from bounding box perturbation by incorporating the joint Normalized Wasserstein Distance(NWD)and Efficient Intersection over Union(EIoU)losses.The efficacy of the proposedmodel in detecting small objects in remote sensing has been validated through experiments conducted on three publicly available datasets.The experimental results unequivocally demonstrate the model’s pronounced advantages in small object detection for remote sensing,surpassing the performance of current mainstream models.

A Cross-Layer Scheme for Handover in 802.16e Network with F-HMIPv6 Mobility

IEEE802.16e is the major global cellular wireless standard that enables low-cost mobile Internet application. However, existing handover process system still has latency affects time-sensitive applications. In this paper, the handover procedures of 802.16e and Fast Handover for Hierarchical MIPv6 (F-HMIPv6) are reconstructed to achieve a better transmission performance. The concept of cross layer design is adopted to refine the existing handover procedure specified in 802.16e MAC layer and F-HMIPv6. More specifically, layer2 and layer3 signaling messages for handover are analyzed and combined/interleaved to optimize the handover performance. Extensive simulations show that the proposed scheme in this paper is superior to the other scheme proposed by IETF.

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.

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.

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.

Novel E2E-QoE Metric for PHY Optimization:A Cross-Layered Framework

Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to terminal users and thus induce additional cost and energy waste.Therefore,it is necessary to utilize directly the quality of experience(QoE)of user as a metric of optimization,which can achieve the global optimum of QoE under cost and energy constraints.However,QoE is still a metric of application layer that cannot be easily used to design and optimize the PHY.To address this problem,we in this paper propose a novel end-to-end QoE(E2E-QoE)based optimization architecture at the user-side for the first time.Specifically,a cross-layer parameterized model is proposed to establish the relationship between PHY and E2E-QoE.Based on this,an E2E-QoE oriented PHY anomaly diagnosis method is further designed to locate the time and root cause of anomalies.Finally,we investigate to optimize the PHY algorithm directly based on the E2E-QoE.The proposed frameworks and algorithms are all validated using the data from real fifth-generation(5G)mobile system,which show that using E2E-QoE as the metric of PHY optimization is feasible and can outperform existing schemes.

Multi-Agent Deep Reinforcement Learning for Cross-Layer Scheduling in Mobile Ad-Hoc Networks

Due to the fading characteristics of wireless channels and the burstiness of data traffic,how to deal with congestion in Ad-hoc networks with effective algorithms is still open and challenging.In this paper,we focus on enabling congestion control to minimize network transmission delays through flexible power control.To effectively solve the congestion problem,we propose a distributed cross-layer scheduling algorithm,which is empowered by graph-based multi-agent deep reinforcement learning.The transmit power is adaptively adjusted in real-time by our algorithm based only on local information(i.e.,channel state information and queue length)and local communication(i.e.,information exchanged with neighbors).Moreover,the training complexity of the algorithm is low due to the regional cooperation based on the graph attention network.In the evaluation,we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states,and demonstrate the adaptability and stability in different topologies.The method is general and can be extended to various types of topologies.

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.

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.

Cross-Layer Adaptive Resource Allocation Algorithm with Diverse QoS Requirements for Single-Cell OFDMA Systems

The orthogonal frequency division multiple access( OFDMA) based communication system has been considered as the main trend of next-Generation communication system. But the existing resource allocation algorithm designed for such system is always with high complexity thus hard to be realized. To solve such problem with the constraints of spectrum efficiency and buffer state,a novel cross-layer resource allocation algorithm( RAA) is proposed in this paper. The goal of our RAA is to maximize the system throughput while satisfying several practical constraints,such as fairness among services,head of line( Ho L) delay and diverse quality of service( Qo S) requirements. Due to these constraints,finding the optimal solution becomes a NPhard problem. Therefore in this paper a novel method to solve such problem with acceptable complexity is proposed within following steps: firstly,based on the link state we formulate the ideal subchannel allocation strategy as a convex optimization problem,which can be efficiently solved by our proposed lagrange multiplier technique subchannel allocation( LMTSA) algorithm; secondly,according to the obtained channel allocation matrix,a power allocation algorithm based on the water-filling power allocation( WPA) idea is deployed to get the optimal power allocation matrix combining with adaptive modulation and coding( AMC); finally,through a greedy algorithm,the ultimate subchannel and power allocation matrix can be obtained based on iterative method. The simulation results illustrate that we can achieve the higher throughput and better Qo S performance than the widely-used maximum throughput( MT) algorithm and round robin( RR) algorithm.

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.

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.

A software-defined networking approach for handover management with real-time video in WLANs

To achieve high performance and reliability in video streaming over wireless local area networks （WLANs）, one must jointly consider both optimized association to access points （APs） and handover management based on dynamic scanning of alternate APs. In this article, we propose a new architecture within the software-defined networking （SDN） framework, which allows stations to be connected to several APs simultaneously and to switch fast between them. We evaluate our system in a real-time testbed and demonstrate that our SDN-based handover mechanism significantly reduces the number and duration of video freeze events and allows for smaller playout buffers.

SLCRM： Subjective Logic-Based Cross-Layer Reputation Mechanism for Wireless Mesh Networks

Wireless Mesh Networks （WMNs） are vulnerable to various security threats because of their special infrastructure and communication mode, wherein insider attacks are the most challenging issue. To address this problem and protect innocent users from malicious attacks, it is important to encourage cooperation and deter malicious behaviors. Reputation systems constitute a major category of techniques used for managing trust in distributed networks, and they are effective in characterizing and quantifying a node＇s behavior for WMNs. However, conventional layered reputation mechanisms ignore several key factors of reputation in other layers; therefore, they cannot provide optimal performance and accurate malicious node identification and isolation for WMNs. In this paper, we propose a novel dynamic reputation mechanism, SLCRM, which couples reputation systems with a cross-layer design and node-security-rating classification techniques to dynamically detect and restrict insider attacks. Simulation results show that in terms of network throughput, packet delivery ratio, malicious nodes＇ identification, and success rates, SI_CRM imple- ments security protection against insider attacks in a more dynamic, effective, and efficient manner than the subjective logic and uncertainty-based reputation model and the familiarity-based reputation model.

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%.

COOPERATIVE DIRECTIONAL INTER-CELL HANDOVER SCHEME IN HIGH ALTITUDE PLATFORM COMMUNICATIONS SYSTEMS

A novel Cooperative Directional inter-cell Handover Scheme(CDHS) for High Altitude Platform(HAP) communications systems is proposed,in which the handover target cell and the two cells adjacent to this handover target cell work cooperatively to exploit the traffic fluctuation to improve handover performance.Users in the overlap area of the overloaded handover target cell will be forced to handover directionally before their optimal handover boundary in order to free up resources for the handover calls which would otherwise be dropped due to the shortage of resources and queue time out.Simulation results show that the handover call dropping probability is greatly reduced(at least 60%) compared with the general queue handover scheme,with little performance reduction to the call blocking probability,and the Not in the Best Cell(NBC) average time is only increased moderately.Moreover,an optimal cell radius can be achieved for a specific platform speed by minimizing the unified system performance,which is the linear combination of the handover call dropping probability and the NBC average time.

Cross-Layer Design and Ant-Colony Optimization Based Routing Algorithm for Low Earth Orbit Satellite Networks

To improve the robustness of the Low Earth Orbit(LEO) satellites networks and realise load balancing, a Cross-layer design and Ant-colony optimization based Load-balancing routing algorithm for LEO Satellite Networks(CAL-LSN) is proposed in this paper. In CALLSN, mobile agents are used to gather routing information actively. CAL-LSN can utilise the information of the physical layer to make routing decision during the route construction phase. In order to achieve load balancing, CALLSN makes use of a multi-objective optimization model. Meanwhile, how to take the value of some key parameters is discussed while designing the algorithm so as to improve the reliability. The performance is measured by the packet delivery rate, the end-to-end delay, the link utilization and delay jitter. Simulation results show that CAL-LSN performs well in balancing traffic load and increasing the packet delivery rate. Meanwhile, the end-to-end delay and delay jitter performance can meet the requirement of video transmission.