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Boundary Reconstruction for Wireless Sensor Networks

IEEE ACCESS 2024年 12卷 168445-168455页

作者： Sivadasan, Sreeram Govindan, Nagarajan Parakkat, Amal Dev Sathyabama Inst Sci & Technol Chennai 600119 India Inst Polytech Paris Telecom Paris LTCI F-91120 Palaiseau France

Wireless Sensor Networks (WSNs) are critical for various applications ranging from environment monitoring to industrial monitoring. The varying and continuously growing interest in this field demands an understanding of the sensor node distribution to ensure robustness and to improve resource utilization for data processing and decision making. In this paper, we focus on reconstructing the boundaries of a wireless sensor network, which also has a lot of applications in IoT and Robotics. As these sensor node locations can be considered as a set of points in the 2D plane, boundary detection of a WSN can be related to classical shape reconstruction problem in Computational Geometry. In this paper, we extend a simple and generic strategy for hole detection to a geometric solution for boundary/shape reconstruction. Furthermore, we introduce a simple and controllable heuristic algorithm to patch the coverage holes identified by our boundary reconstruction algorithm. Not only does this study improve the reliability of WSNs, but it also provides a useful tool for the extensive domain of computational geometry and shape analysis. Our different experiments show that the proposed reconstruction algorithm outperforms the existing state-of-the-art methods, and hole patching gives a simple and controllable solution for mobile node placement.

关键词： Shape measurement Wireless sensor networks Sensors Reconstruction algorithms Surveys Object recognition Mobile nodes Surveillance Smart cities Security Shape reconstruction Delaunay triangulation coverage hole detection dynamic node placement coverage optimization

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An Empirical Study on Using CNNs for Fast Radio Signal Prediction

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SN Computer Science 2022年第2期3卷 131页

作者： Ozyegen, Ozan Mohammadjafari, Sanaz Cevik, Mucahit El mokhtari, Karim Ethier, Jonathan Basar, Ayse Mechanical Industrial Engineering Department Ryerson University Toronto M5B 2K3 ON Canada Communications Research Centre Canada Ottawa Canada

Accurate radio frequency power prediction in a geographic region is a computationally expensive part of finding the optimal transmitter location using a ray tracing software. We empirically analyze the viability of deep learning models to speed up this process. Specifically, deep learning methods including CNNs and UNET are typically used for segmentation, and can also be employed in power prediction tasks. We consider a dataset that consists of radio frequency power values for five different regions with four different frame dimensions. We compare deep learning-based prediction models including RadioUNET and four different variations of the UNET model for the power prediction task. More complex UNET variations improve the model on higher resolution frames such as 256×256. However, using the same models on lower resolutions results in overfitting and simpler models perform better. Our detailed numerical analysis shows that the deep learning models are effective in power prediction and they are able to generalize well to the new regions. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2022.

关键词： CNN coverage optimization Deep learning Ray tracing UNET

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Beam Design for Energy-Efficient Wireless coverage of 5G mmWave Networks 18

Beam Design for Energy-Efficient Wireless Coverage of 5G mmW...

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18th IEEE International Wireless Communications and Mobile Computing Conference (IWCMC)

作者： Li, Fang Zhang, Guangyang Shi, Juan Shen, Chao Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Shenzhen Res Inst Big Data Shenzhen 518172 Peoples R China

ISBN: (纸本)9781665467490

This paper investigates beam design in a millimeter wave (mmWave) network, where some obstacles block the link between the base stations (BSs) and the user equipments (UEs). There is a single cell in an area where the UEs communicate with the single BS through a line of sight (LoS) link. To provide services in the network, synchronization signal blocks (SSBs) are transmitted by the BS in a fixed beam pattern. We aim at minimizing the transmit power by designing the beam while meeting the coverage requirement, which depends on the reference signal received power (RSRP) at the UEs. A non-convex power minimization problem is then formulated by jointly optimizing the beam directions, beam width and beam number subject to the coverage constraints. To resolve this problem, an alternating optimization (AO) based algorithm is proposed and the successive convex approximation (SCA) method is applied. The simulation results demonstrate that the proposed algorithm can significantly improve the performance of power consumption compared with the other two heuristic algorithms.

关键词： Millimeter wave (mmWave) networks beam design coverage optimization reference signal received power (RSRP)

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Nodes Deployment Algorithm Based on Data Fusion and Evidence Theory in Wireless Sensor Networks

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WIRELESS PERSONAL COMMUNICATIONS 2021年第2期116卷 1481-1492页

作者： Li, Qiangyi Liu, Ningzhong Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Jiangsu Peoples R China MIIT Key Lab Pattern Anal & Machine Intelligence Nanjing 211106 Jiangsu Peoples R China

Wireless sensor networks have been widely researched and developed in recent years. The node deployment problem is a multi-dimensional nonlinear optimization problem with continuous discrete variables. In order to improve the coverage effect of wireless sensor networks, a network coverage algorithm based on evidence theory is proposed. The motion direction of the wireless sensor node is calculated. The wireless sensor node is moved to the area with low perception probability. Improve the network coverage effect. Reduce the moving distance of wireless sensor nodes. Extended the service time of wireless sensor network. The simulation results show that this algorithm can improve the coverage effect of the monitoring area and reduce the moving distance of nodes effectively.

关键词： Nodes deployment algorithm Data fusion Evidence theory Wireless sensor networks coverage optimization

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optimization of Multi-Frequency Network With DVB-T2 Services for Regions With Complex Geographies: A Case Study of Nepal

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IEEE TRANSACTIONS ON BROADCASTING 2021年第1期67卷 299-312页

作者： Nepal, Subodh Thang, Duong Quang Higashino, Takeshi Okada, Minoru Nara Inst Sci & Technol Grad Sch Sci & Technol Nara 6300192 Japan

Planning for Multi-Frequency Network (MFN) with Digital Video Broadcasting-Second Generation Terrestrial (DVB-T2) services is particularly useful during the transition from analog to digital broadcasting. For efficient management of service area as well as resource allocation, it is necessary to administer the use of network parameters, e.g., transmit power, frequency channels, and antenna parameters. This article, therefore, proposes a coverage maximization scheme for the MFN with the DVB-T2 system by using the Genetic Algorithm. In order to effectively perform the optimization over regions with diverse geographical structures, a propagation prediction method considering the complex orography together with Digital Elevation Model is used to predict signal strength at each receiving location. Based on the received signal strength and standard Quality of Service criteria, the overall radio coverage of the network is maximized using the optimum values of transmit power levels, frequency channels, and antenna parameters. Although our analysis and simulations are based on the MFN network in Nepal, the methodology presented in this work can be applied in any region with some alterations in geographical and meteorological parameters.

关键词： optimization Radio transmitters Receivers Digital video broadcasting Predictive models Planning Transmitting antennas Co-channel interference coverage optimization coverage prediction DVB-T2 network parameter optimization spectrum usage

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coverage control of unicycle multi-agent network in dynamic environment

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MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2021年第0期

作者： Sun, Qihai Liu, Zhi-Wei Chi, Ming Dou, Yangming He, Dingxin Qin, Yijie Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan Peoples R China

This paper studies the coverage control problem of an unicycle multi-agent network with external disturbance in a dynamic environment which is described by a time-varying density function. It is a challenging task to design a coverage control to simultaneously handle the external disturbance, underactuated model and time-varying density function. Based on Voronoi partition, we proposed a coverage control approach which can maximize the metric function via robust tracking the Voronoi centroid with external disturbance. It is worth to mentioning that the angle of motion of the unicycle agent can align with the Voronoi centroid in finite time. Finally, the effectiveness of the proposed control is shown by simulation results.

关键词： coverage optimization multi-agent system time-varying density function unicycle model Voronoi partition

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optimization of coverage in 5G Self-Organizing Small Cell Networks

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MOBILE NETWORKS & APPLICATIONS 2018年第6期23卷 1502-1512页

作者： Chen, Yu Guo, Zhi Yang, Xiuqing Hu, Yi Zhu, Qinghua Beijing Polytech Sch Telecommun Engn Beijing 100176 Peoples R China State Radio Monitoring Ctr Beijing 100037 Peoples R China

Heterogeneous two-tier network with hybrid deployed small cells and macrocells is a promising solution for fifth generation (5G) wireless networks. However, with the higher and higher spectrum band used in 5G, the coverage and capacity of indoor environment is not good enough for the users' increasing demand. In this paper, we proposed a self-organizing capacity and coverage optimization scheme using power adaptation to enhance the capacity and improve the coverage. Simulation results show that the proposed self-organizing scheme can effectively improve the capacity and coverage.

关键词： Small cells coverage optimization Capacity optimization Self-Organizing network

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The coverage optimization for Wireless Sensor Networks Based on Quantum-Inspired Cultural Algorithm 1

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Chinese Intelligent Automation Conference (CIAC)

作者： Guo, Yi-nan Liu, Dandan Liu, Yun Chen, Meirong China Univ Min & Technol Coll Informat & Elect Engn Xuzhou 221116 Jiangsu Peoples R China

ISBN: (数字)9783642385247

ISBN: (纸本)9783642385247;9783642385230

In order to properly distribute sensor nodes in wireless sensor networks, a coverage model considering maximum coverage ratio and minimum redundancy is given and the optimization strategy based on quantum-inspired cultural algorithm is proposed. In population space, quantum-inspired evolutionary algorithm is used to increase the observed probability. In belief space, the implicit knowledge embodied in the evolution is extracted from the better individuals chosen from the population. It is used to guide the search direction of evolutionary population and influence the update of quantum individuals. Simulation results indicate that the algorithm is superior to other algorithms in coverage optimization and effectively improve the coverage performance of wireless sensor networks.

关键词： Wireless sensor networks Quantum-inspired algorithm Cultural algorithm coverage optimization

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Constrained Artificial Fish-swarm based Area coverage optimization Algorithm for Directional Sensor Networks

Constrained Artificial Fish-swarm based Area Coverage Optimi...

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IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS)

作者： Tao, Dan Tang, Shaojie Liu, Liang Beijing Jiaotong Univ Sch Elect & Informat Engn State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA Beijing Univ Posts & Telecommun Beijing Key Lab Intelligent Telecommun Software & Beijing PT-100876 Peoples R China

ISBN: (纸本)9780769551043

In this paper, we explore the area coverage optimization problem by directional sensors with tunable sensing orientations. We firstly introduce the concept of "sensing centroid", which is the geometric center of a sensing sector to simplify the pending problem. Particularly, we regard "sensing centroid" as artificial fish (AF), and search an optimal solution in the solution space by simulating fish swarm behaviors (such as prey, swarm and follow) with a tendency toward high food consistence. Fully considering that AFs have to satisfy both kinematic constraint and dynamic constraint in the process of motion, we propose a Constrained Artificial Fish-Swarm Algorithm (CAFSA), and discuss the control laws to guide the behaviors of AFs with high convergence speed. Finally, we evaluate the effect of some primary parameters on the performance of our solution through extensive simulations.

关键词： directional sensor networks swarm intelligence artificial fish-swarm area coverage coverage optimization

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Joint coverage optimization of Multiple Sectors for Cellular Networks

Joint Coverage Optimization of Multiple Sectors for Cellular...

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IEEE 78th Vehicular Technology Conference (VTC Fall)

作者： Fan, Dongdong Wu, Zhouyun Huang, Aiping Zhuang, Hongcheng Quek, Tony Q. S. Zhejiang Univ Inst Informat & Commun Engn Hangzhou 310027 Peoples R China Informat Network Technol Zhejiang Prov Key Lab Hangzhou 310027 Peoples R China Huawei Technol Co Ltd Shenzhen 518129 Peoples R China Singapore Univ Technol & Design Singapore Singapore

ISBN: (纸本)9781467361873

coverage optimization is an important task, which directly affects the performance of cellular networks. It is difficult to correct the weak coverage and the over coverage simultaneously using existing methods such as adjusting antenna downtilts and/or transmit powers of sectors. In this paper, a novel coverage optimization method based on multi-sector joint beamforming is proposed, so that weak coverage area and over coverage area can be decreased simultaneously. A heuristic algorithm based on the semidefinite relaxation is then developed to obtain antenna array excitation weights with low computational complexity. Simulation results show that the performance of our algorithm is superior to that of antenna downtilt optimization algorithm.

关键词： coverage optimization joint beamforming semidefinite relaxation downtilt optimization

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