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第36届中国控制会议

作者： Luo Chengming Fan Xinnan Xin Gaifang Yang Hai Zhang Xuewu College of Internet of Things Engineering Hohai University College of Computer and Information Hohai University Jiangsu Wenguang Vehicle Accessories Company Limited School of Mechanical and Electrical Engineering Changzhou College of Information Technology School of Mechatronic Engineering Southwest Petroleum University

ISBN: (纸本)9781538629185

As a class of narrow band structures such as dock,bridge and dam,chain-type networks are applied to monitor and track underwater *** paper proposes a coverage strategy for probabilistic positioning of mobile targets,which can balance the coverage and positioning performance of underwater sensor *** on careful analysis characteristic of network architectures,multiple relay nodes integrated with non-uniform deployment are designed in the consideration of the extensibility of underwater sensor network,which consists of common sense nodes,relay nodes and a base *** probabilistic positioning model for mobile targets is devised with the support of node optimization ***,the simulation experiments have been implemented in order to evaluate the proposed algorithm performance for targets probabilistic positioning.

关键词： Underwater Sensor Network Mobile Targets Probabilistic Positioning coverage optimization

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Cognitive optimization Scheme of coverage for Femtocell using Multi-element Antenna

Cognitive Optimization Scheme of Coverage for Femtocell usin...

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IEEE 72nd Vehicular Technology Conference Fall 2010

作者： Li, Yizhe Feng, Zhiyong Zhang, Qixun Tan, Li Tian, Fang Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Wireless Technol Innovat Inst WTI Beijing 100876 Peoples R China

ISBN: (纸本)9781424435746

Recently, femtocell has been proposed as a good solution to increase the coverage area and capacity of the wireless communication system as well as meet the increasing demand for high data rate. The femtocell is low-cost, low-power and can be realized by deploying a femto-base-station connected to the core network via a wired-backhaul. Since the femtocell reuses the macrocell spectrum, co-channel interference between femtocell and macrocell should be taken into consideration first of all. The leakage of femtocell's pilot power to the outside of a residence would cause passing users' handover events and result in increasing load to the network. In this paper, firstly we put forward a simple method for the femtocell to gain recognition of the residence and network environment, and then according to the obtained knowledge the femtocell carries out self-cofiguration and self-optimization for the purpose of achieving an optimized coverage to improve the in door Quality of Service (QoS) and minimum the interference in the existing network. To implement that we bring up a low-cost multi-element antenna solution and a series of corresponding algorithms, which is mainly based on low-complexity shaped beam forming and power adjusting. The simulation results show that the approaches proposed in the paper greatly reduce the femtocell's interference to the macrocell and optimize indoor coverage at the same time. These results can provide guidelines for the deployment of femtocell.

关键词： femtocell multi-element antenna cognition of environment coverage optimization

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The tradeoff between coverage and capacity in dynamic optimization of 3G cellular networks

The tradeoff between coverage and capacity in dynamic optimi...

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58th IEEE Vehicular Technology Conference (VTC 2003)

作者： Hampel, G Clarkson, KL Hobby, JD Polakos, PA Bell Labs Lucent Technol Murray Hill NJ 07974 USA

ISBN: (纸本)0780379543

For 3G cellular networks, capacity is an important objective, along with coverage, when characterizing the performance of high-data-rate services. In live networks, the effective network capacity heavily depends on the degree that the traffic load is balanced over all cells, so changing traffic patterns demand dynamic network reconfiguration to maintain good performance. Using a four-cell sample network, and antenna tilt, cell power level and pilot fraction as adjustment variables, we study the competitive character of network coverage and capacity in such a network optimization process, and how it compares to the CDMA-intrinsic coverage-capacity tradeoff driven by interference. We find that each set of variables provides its distinct coverage-capacity tradeoff behavior with widely varying and application-dependent performance gains. The study shows that the impact of dynamic load balancing highly depends on the choice of the tuning variable as well as the particular tradeoff range of operation.

关键词： coverage optimization capacity optimization 3G cellular networks coverage-capacity tradeoff load balancing

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Parallel Particle Swarm optimization (PPSO) on the coverage Problem in Pursuit-Evasion Games

Parallel Particle Swarm Optimization (PPSO) on the Coverage ...

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High Performance Computing Symposium (HPC 2012)

作者： Jin, Shiyuan Dechev, Damian Qu, Zhihua Univ Cent Florida Dept EECS Orlando FL 32816 USA

ISBN: (纸本)9781618397881

A Parallel Particle Swarm optimization (PPSO) algorithm using MPI is implemented to solve the coverage problem of pursuit-evasion (PE) games where multiple pursuers need to cooperate to cover an agile evader's possible escape area within reasonable time. The area to be covered is complex and thus difficult to calculate analytically. With the use of PPSO, maximum coverage is achieved in less time, given the minimum number of pursuers. The computation time can be further reduced by optimizing the fitness function based on data locality. In addition, using variable length of communication data frame performs better than fixed length in reducing inter-process communication time when the number of processors increases (more than four in the test example). Simulation results show a comparison of the speedup, the computation time before and after optimizing the fitness function, and communication time between fixed and variable data frame. Pursuers' positions and orientations are also presented to show the effectiveness of the PPSO algorithm.

关键词： Parallel computing PSO coverage optimization pursuit-evasion games

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Virtual Angle Boundary-Aware Particle Swarm optimization to Maximize the coverage of Directional Sensor Networks

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SENSORS 2021年第8期21卷 2868页

作者： Cheng, Gong Wei, Huangfu Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China Univ Sci & Technol Beijing Shunde Grad Sch Foshan 528300 Peoples R China

With the transition of the mobile communication networks, the network goal of the Internet of everything further promotes the development of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs). Since the directional sensor has the performance advantage of long-term regional monitoring, how to realize coverage optimization of Directional Sensor Networks (DSNs) becomes more important. The coverage optimization of DSNs is usually solved for one of the variables such as sensor azimuth, sensing radius, and time schedule. To reduce the computational complexity, we propose an optimization coverage scheme with a boundary constraint of eliminating redundancy for DSNs. Combined with Particle Swarm optimization (PSO) algorithm, a Virtual Angle Boundary-aware Particle Swarm optimization (VAB-PSO) is designed to reduce the computational burden of optimization problems effectively. The VAB-PSO algorithm generates the boundary constraint position between the sensors according to the relationship among the angles of different sensors, thus obtaining the boundary of particle search and restricting the search space of the algorithm. Meanwhile, different particles search in complementary space to improve the overall efficiency. Experimental results show that the proposed algorithm with a boundary constraint can effectively improve the coverage and convergence speed of the algorithm.

关键词： directional sensor networks coverage optimization boundary constraints particle swarm optimization

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Intelligent Drone Positioning via BIC optimization for Maximizing LPWAN coverage and Capacity in Suburban Amazon Environments

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SENSORS 2023年第13期23卷 6231页

作者： Ferreira, Flavio Henry Cunha da Silva Neto, Miercio Cardoso de Alcantara Barros, Fabricio Jose Brito de Araujo, Jasmine Priscyla Leite Fed Univ Para UFPA Inst Technol BR-66075110 Belem Brazil

This paper aims to provide a metaheuristic approach to drone array optimization applied to coverage area maximization of wireless communication systems, with unmanned aerial vehicle (UAV) base stations, in the context of suburban, lightly to densely wooded environments present in cities of the Amazon region. For this purpose, a low-power wireless area network (LPWAN) was analyzed and applied. LPWAN are systems designed to work with low data rates but keep, or even enhance, the extensive area coverage provided by high-powered networks. The type of LPWAN chosen is LoRa, which operates at an unlicensed spectrum of 915 MHz and requires users to connect to gateways in order to relay information to a central server;in this case, each drone in the array has a LoRa module installed to serve as a non-fixated gateway. In order to classify and optimize the best positioning for the UAVs in the array, three concomitant bioinspired computing (BIC) methods were chosen: cuckoo search (CS), flower pollination algorithm (FPA), and genetic algorithm (GA). Positioning optimization results are then simulated and presented via MATLAB for a high-range IoT-LoRa network. An empirically adjusted propagation model with measurements carried out on a university campus was developed to obtain a propagation model in forested environments for LoRa spreading factors (SF) of 8, 9, 10, and 11. Finally, a comparison was drawn between drone positioning simulation results for a theoretical propagation model for UAVs and the model found by the measurements.

关键词： wireless sensor networks IoFT LoRa coverage optimization channel modeling bioinspired computing

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optimization in VHTS Satellite System Design with Irregular Beam coverage for Non-Uniform Traffic Distribution

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REMOTE SENSING 2021年第13期13卷 2642-2642页

作者： Ortiz-Gomez, Flor G. Salas-Natera, Miguel A. Martinez, Ramon Landeros-Ayala, Salvador Univ Politecn Madrid Informat Proc & Telecommun Ctr Madrid 28040 Spain Univ Nacl Autonoma Mexico Dept Telecommun Engn Mexico City 04360 DF Mexico Agencia Espacial Mexicana Mexico City 01020 DF Mexico

Very High Throughput Satellites (VHTS) have a pivotal role in complementing terrestrial networks to increase traffic demand. VHTS systems currently assume a uniform distribution of traffic in the service area, but in a real system, traffic demands are not uniform and are dynamic. A possible solution is to use flexible payloads, but the cost of the design increases considerably. On the other hand, a fixed payload that uses irregular beam coverage depending on traffic demand allows maintaining the cost of a fixed payload while minimizing the error between offered and required capacity. This paper presents a proposal for optimizing irregular beams coverage and beam pattern, minimizing the costs per Gbps in orbit, the Normalized coverage Error, and Offered Capacity Error per beam. We present the analysis and performance for the case study and compare it with a previous algorithm for a uniform coverage area.

关键词： beamwidth coverage optimization cost per Gbps in orbit irregular sized beams irregular coverage offered capacity error very high throughput satellite satellite multibeam

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A novel topology optimization of coverage-oriented strategy for wireless sensor networks

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2021年第4期17卷 p1-14页

作者： Wang, Shuxin You, Hairong Yue, Yinggao Cao, Li Wenzhou Univ Oujiang Coll Wenzhou 325035 Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang Peoples R China Hubei Univ Arts & Sci Comp Sch Xiangyang Peoples R China

Aiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of coverage-oriented strategy for wireless sensor networks based on the wolf pack algorithm is proposed. Combining the characteristics of topology structure of wireless sensor networks and the optimization idea of the wolf pack algorithm redefines the group's wandering and surprise behavior. A novel head wolf mutation strategy is proposed, which increases the neighborhood search range of the optimal solution, enhances the uniformity of wolf pack distribution and the ergodicity ability of the wolf pack search, and greatly improves the calculation speed and the accuracy of the wolf pack algorithm. With the same probability, the cluster heads are randomly selected periodically, and the overall energy consumption of wireless sensor networks is evenly distributed to the sensor node to realize the balanced distribution of the data of the member nodes in the cluster and complete the design of the topology optimization of wireless sensor networks. Through algorithm simulation and result analysis, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the wolf swarm algorithm shows its advantages in terms of the residual energy of the sensor node, the average transmission delay, the average packet delivery rate, and the coverage of the network. Among them, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the remaining energy of nodes has increased by 9.5% and 15.5% and the average coverage of the network has increased by 10.5% and 5.6%, respectively.

关键词： Internet of things wireless sensor networks topology wolf pack algorithm coverage optimization

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optimization of coverage for OFDMA Femtocell Networks based on MADM

Optimization of Coverage for OFDMA Femtocell Networks based ...

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8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM)

作者： Huang, Zhenglei Xia, Hailun Zeng, Zhimin Liu, Yinlong Beijing Univ Posts & Telecommun Beijing Key Lab Network Syst Architecture & Conve Beijing 100876 Peoples R China Chinese Acad Sci Inst Acoust Beijing 100864 Peoples R China

ISBN: (纸本)9781612846835;9781612846828

This paper addresses how to optimize the radio coverage area of OFDMA femtocell networks in enterprise deployment. Considering some basic requirements of coverage, including coverage holes, coverage overlaps, area spectral efficiency (ASE) and load balancing, the coverage optimization problem is modeled as a Multiple Attribute Decision Making (MADM) problem. Then the MADM-based coverage optimization problem is solved by the Gray relation analysis (GRA) method. Simulation results show that the proposed scheme can achieve a better ASE performance and effectively balance the traffic load amongst all femtocells, as well as obtaining a good tradeoff between coverage holes and coverage overlap. Meanwhile, the results of sensitive analysis also show that the coverage optimization is sensitive to the variation of weight values, and all the four attributes play an important role in the coverage optimization.

关键词： coverage optimization femtocell networks multiple attribute decision making gray relation analysis

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Parallel Particle Swarm optimization (PPSO) on the coverage Problem in Pursuit-Evasion Games 12

Parallel Particle Swarm Optimization (PPSO) on the Coverage ...

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Simulation Multiconference

作者： Shiyuan Jin Damian Dechev Zhihua Qu Department of EECS University of Central Florida

ISBN: (纸本)9781618397881

A Parallel Particle Swarm optimization (PPSO) algorithm using MPI is implemented to solve the coverage problem of pursuit-evasion (PE) games where multiple pursuers need to cooperate to cover an agile evader's possible escape area within reasonable time. The area to be covered is complex and thus difficult to calculate analytically. With the use of PPSO, maximum coverage is achieved in less time using the minimum number of pursuers. The computation time can be further reduced by optimizing the fitness function based on data locality. In addition, using variable length of communication data frame performs better than fixed length in reducing inter-process communication time when the number of processors increases (more than four in the test example). Simulation results show a comparison of the speedup, the computation time before and after optimizing the fitness function, and communication time between fixed and variable data frame. Pursuers' positions and orientations are also presented to show the effectiveness of the PPSO algorithm.

关键词： Parallel computing PSO coverage optimization Pursuit-evasion games PARALLEL PROCESSING (COMPUTERS) parametric subharmonic oscillator computational time Particle swarm optimization variable data coverage locality data fixed length variable length Communication Research message passing mannose phosphate isomerase remote procedure calls

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