Performance of Cross-Layer Design with Power Allocation in Space-Time Coded MIMO Systems

A cross-layer design(CLD)scheme with combination of power allocation,adaptive modulation(AM)and automatic repeat request(ARQ)is presented for space-time coded MIMO system under imperfect feedback,and the corresponding system performance is investigated in a Rayleigh fading channel.Based on imperfect feedback information,a suboptimal power allocation(PA)scheme is derived to maximize the average spectral efficiency(SE)of the system.The scheme is based on a so-called compressed SNR criterion,and has a closed-form expression for positive power allocation,thus being computationally efficient.Moreover,it can improve SE of the presented CLD.Besides,due to better approximation,it obtains the performance close to the existing optimal approach which requires numerical search.Simulation results show that the proposed CLD with PA can achieve higher SE than the conventional CLD with equal power allocation scheme,and has almost the same performance as CLD with optimal PA.However,it has lower calculation complexity.

Cross-Layer Design for EH Systems with Finite Buffer Constraints

Energy harvesting(EH)technology in wireless communication is a promising approach to extend the lifetime of future wireless networks.A cross-layer optimal adaptation policy for a point-to-point energy harvesting(EH)wireless communication system with finite buffer constraints over a Rayleigh fading channel based on a Semi-Markov Decision Process(SMDP)is investigated.Most adaptation strategies in the literature are based on channeldependent adaptation.However,besides considering the channel,the state of the energy capacitor and the data buffer are also involved when proposing a dynamic modulation policy for EH wireless networks.Unlike the channeldependent policy,which is a physical layer-based optimization,the proposed cross-layer dynamic modulation policy is a guarantee to meet the overflow requirements of the upper layer by maximizing the throughput while optimizing the transmission power and minimizing the dropping packets.Based on the states of the channel conditions,data buffer,and energy capacitor,the scheduler selects a particular action corresponding to the selected modulation constellation.Moreover,the packets are modulated into symbols according to the selected modulation type to be ready for transmission over the Rayleigh fading channel.Simulations are used to test the performance of the proposed cross-layer policy scheme,which shows that it significantly outperforms the physical layer channel-dependent policy scheme in terms of throughput only.

An Ant Colony Algorithm Based on Cross-Layer Design for Routing and Wavelength Assignment in Optical Satellite Networks

This paper introduces an ant colony routing and wavelength assignment algorithm based on cross-layer design(CL-ACRWA),which can overcome the adverse effects of Doppler wavelength shift on data transmission in optical satellite networks. Firstly, a cross-layer optimization model is built, which considers the Doppler wavelength shift, the transmission delay as well as wavelength-continuity constraint. Then an ant colony algorithm is utilized to solve the cross-layer optimization model, resulting in finding an optimal light path satisfying the above constraints for every connection request. The performance of CL-ACRWA is measured by the communication success probability, the convergence property and the transmission delay. Simulation results show that CL-ACRWA performs well in communication success probability and has good global search ability as well as fast convergence speed. Meanwhile, the transmission delay can meet the basic requirement of real-time transmission of business.

Wireless sensor networks in relic protection:deployment methodology and cross-layer design

This paper describes the deployment optimization technology and the cross-layer design of a surveil-lance WSN system applied in relic protection.Facing the typical technical challenges in the applicationcontext of relic protection,we firstly propose a deployment technology based on ant colony optimization al-gorithm(DT-ACO)to overcome the difficulties in communication connectivity and sensing coverage.Meanwhile,DT-ACO minimizes the overall cost of the system as much as possible.Secondly we proposea novel power-aware cross-layer scheme(PACS)to facilitate adjustable system lifetime and surveillanceaccuracy.The performance analysis shows that we achieve lower device cost,significant extension of thesystem lifetime and improvement on the data delivery rate compared with the traditional methods.

Novel Optimized Cross-Layer Design with Maximum Weighted Capacity Based Resource Allocation for AMC/HARQ Wireless Networks

To provide quality-of service (QoS) guarantees for heterogeneous applications, most recent wireless communications technologies and standards combine the error-correcting capability of hybrid automatic repeat request (HARQ) schemes at the data link layer (DLL) with the adaptation ability of the adaptive modulation and coding (AMC) modes at the physical layer (PHY) layer. This paper aims to investigate the aggregated system capacity as well as the breakdown of this capacity for different ACM modes in each HARQ scheme. This investigation was done by using maximum weighted capacity (MWC) resource allocation at the PHY layer in conjunction with a novel packet error rate (PER)-based scheduling at the medium access control (MAC) layer. As a result, the dominant AMC mode corresponding to channel SNR was available.

Cross-layer design of combining AMC with HARQ in cooperative relay system with perfect and imperfect CSI

A cross-layer design which combines adaptive modulation and coding (AMC) at the physical layer with a hybrid automatic repeat request (HARQ) protocol at the data link layer (LL) is presented, in cooperative relay system over Nakagami-m fading channels with perfect and imperfect channel state information (CSI). In order to maximize spectral efficiency (SE) under delay and packet error rate (PER) performance constraints, a state transition model and an optimization framework with perfect CSI are presented. Then the framework is extended to cooperative relay system with imperfect CSI. The numerical results show that the scheme can achieve maximum SE while satisfying transmitting delay requirements. Compared with the imperfect CSI, the average PER with perfect CSI is much lower and the spectral efficiency is much higher.

Optimal Rate Allocation Based on Cross-Layer Design and End-to-End Congestion Control in WCDMA Networks

In this paper, a novel idea for rate allocation combining both vertical coupling and horizontal coupling constraints is proposed, and a unified utility function to balance two paradoxical issues: efficiency and fairness, revenue and cost is elaborated in WCDMA networks. Then, the optimal rate allocation problem is formulated as a network utility maximization(NUM) model based on cross-layer design and end-to-end congestion control, aiming at exploring the impacts of wired networks and the characteristics of radio access networks(RANs) on rate allocation. Furthermore, a distributed algorithm is derived, which can effectively match load states between RANs and wired networks, followed by a detailed illustration of the practical implementations. Numerical results demonstrate a signifi cant performance improvement in the end-to-end throughput.

Cross-Layer Design Based Optimized Link State Routing Protocol for Wireless Mesh Networks

A proactive routing protocol CL-OLSR (cross-layer based optimized link state routing) by using a brand-new routing metric CLM (cross-layer metric) is proposed. CL-OLSR takes into account four link quality impact factors in route calculation through the cross-layer operation mechanism: the node available bandwidth, the node load, the link delivery rate, and the link interference, and thus the effect of route selection is optimized greatly. The simulation results show that the proposed CL-OLSR protocol can not only improve the network throughput to a large extent, but also reduce the end-to-end delay, while achieving load balance route results.

A cross-layer design approach on spectrum allocation and resource scheduling in cognitive PMP networks

We propose the spectrum allocation and resource scheduling algorithms in cognitive point to multipoint (PMP) networks with rapid changes of spectrum opportunities and present a media access control (MAC) protocol based on these algorithms. The objective of spectrum allocation is to make efficient use of the spectrum while maintaining the transceiver synchronization on frequency and time in the network. The objective of resource scheduling is to guarantee the quality of service (QoS) requirements of different kinds of connections and to minimize the total energy consumption in the network as well. By sensing only a small set of possible channels in each slot based on the state transition probability of each channel, our spectrum allocation algorithm achieves high spectrum efficiency in the network. The resource scheduling problem is divided into three sub problems and we derive optimal solutions to these problems by greedy algorithm and convex optimization. The simulation results show that our algorithm can make efficient use of the spectrum and the network resources at a cost of low computational complexity.

Dynamic routing and wavelength assignment algorithm of optical satellite networks based on cross-layer design

In order to overcome the adverse effects of Doppler wavelength shift on data transmission in the optical satellite networks,a dynamic routing and wavelength assignment algorithm based on crosslayer design( CL-DRWA) is introduced which can improve robustness of the network. Above all,a cross-layer optimization model is designed,which considers transmission delay and wavelength-continuity constraint,as well as Doppler wavelength shift. Then CL-DRWA is applied to solve this model,resulting in finding an optimal light path satisfying the above constraints for every connection request. In CL-DRWA,Bellman-Ford method is used to find an optimal route and a distributed relative capacity loss method is implemented to get an optimal wavelength assignment result on the optimal route. Moreover,compared with the dynamic routing and wavelength assignment algorithm based on minimum delay strategy( MD-DRWA),CL-DRWA can make an improvement of 5. 3% on the communication success probability. Meanwhile,CL-DRWA can meet the requirement of transmission delay for real-time services.

On Cross-Layer Design of AMC Based on Rate Compatible Punctured Turbo Codes

This paper extends the work on cross-layer design which combines adaptive modulation and coding at the physical layer and hybrid automatic repeat request protocol at the data link layer. By contrast with previous works on this topic, the present development and the performance analysis as well, is based on rate compatible punctured turbo codes. Rate compatibility provides incremental redundancy in transmission of parity bits for error correction at the data link layer. Turbo coding and iterative decoding gives lower packet error rate values in low signal-to-noise ratio regions of the adaptive modulation and coding (AMC) schemes. Thus, the applied cross-layer design results in AMC schemes can achieve better spectral efficiency than convolutional one while it retains the QoS requirements at the application layer. Numerical results in terms of spectral efficiency for both turbo and convolutional rate compatible punctured codes are presented. For a more comprehensive presentation, the performance of rate compatible LDPC is contrasted with turbo case as well as the performance complexity is discussed for each of the above codes.

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 design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks

In order to periodically reassess the status of the alternate path route(APR)set and to improve the efficiency of alternate path construction existing in most current alter-nate path routing protocols,we present a cross-layer design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks(CALRA)in this paper.In CALRA,the APR set maintained in nodes is aged and reas-sessed by the inherent mechanism of pheromone evaporation of ant-colony optimization algorithm,and load balance of network is achieved by ant-colony optimization combining with cross-layer synthetic optimization.The efficiency of APR set construction is improved by bidirectional and hop-by-hop routing update during routing discovery and routing maintenance process.Moreover,ants in CALRA deposit simulated pheromones as a function of multiple parameters corresponding to the information collected by each layer of each node visited,such as the distance from their source node,the congestion degree of the visited nodes,the current pheromones the nodes possess,the velocity of the nodes,and so on,and provide the information to the visiting nodes to update their pheromone tables by endowing the different parameters corresponding to different information and different weight values,which provides a new method to improve the congestion problem,the shortcut problem,the convergence rate and the heavy overheads commonly existed in existing ant-based routing protocols for ad-hoc networks.The performance of the algorithm is measured by the packet delivery rate,good-put ratio(routing overhead),and end-to-end delay.Simulation results show that CALRA performs well in decreasing the route overheads,balancing traffic load,as well as increasing the packet delivery rate,etc.

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.

Enhanced performance based on cross-layer design from physical to transport layers for multihop wireless networks

This paper puts forward a novel cognitive cross-layer design algorithms for multihop wireless networks optimization across physical,mediam access control (MAC),network and transport layers.As is well known,the conventional layered-protocol architecture can not provide optimal performance for wireless networks,and cross-layer design is becoming increasingly important for improving the performance of wireless networks.In this study,we formulate a specific network utility maximization (NUM) problem that we believe is appropriate for multihop wireless networks.By using the dual algorithm,the NUM problem has been optimal decomposed and solved with a novel distributed cross-layer design algorithm from physical to transport layers.Our solution enjoys the benefits of cross-layer optimization while maintaining the simplicity and modularity of the traditional layered architecture.The proposed cross-layer design can guarantee the end-to-end goals of data flows while fully utilizing network resources.Computer simulations have evaluated an enhanced performance of the proposed algorithm at both average source rate and network throughput.Meanwhile,the proposed algorithm has low implementation complexity for practical reality.

基于“Design Thinking”理念的职业院校创新创业人才培养模式

随着我国经济不断发展和社会进步,创新创业已经成为推动经济增长的关键驱动力,在2015年全国人民代表大会上,李克强总理将“大众创业、万众创新”明确列为我国经济增长的“双引擎”之一,彰显了创新创业对于推动社会发展的重要地位。为响应国家政策,各高校积极开展创新创业教育,将其纳入高等教育综合改革的重要议程,成为培养未来人才的重要途径。本文分析了“Design Thinking”理念下职业院校创新创业人才培养的必要性,围绕新时期专业院校创新创业人才培养的要求,提出了基于“Design Thinking”理念的职业院校创新创业人才培养模式的有效策略,为职业院校人才培养效率的强化提供了参考性意见。

基于Cast Designer的壳体铸件铸造工艺设计及智能优化

使用Cast Designer铸造仿真分析软件,通过可铸性评估系统DFM,完成浇冒系统的辅助设计,然后使用DOE技术和基于遗传算法GA的智能优化技术,评估不同工艺设计方案与铸造过程参数对壳体铸件质量的影响,分析在不同的冒口、冷铁和浇注温度条件下得料率和缩孔量的关系。根据对DOE模拟结果的分析,发现顶冒口和侧冒口尺寸是影响得料率和缩孔量的关键因数,再利用遗传算法GA选择最佳设计方案和参数。通过帕累托曲线得到了生产壳体铸件的最优工艺方案。

Web Layout Design of Large Cavity Structures Based on Topology Optimization

Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.