The Channel Estimation and Modeling in High Altitude Platform Station Wireless Communication Dynamic Network

Liu, Xiaoyang; Zeng, Xiaoping; Liu, Chao; Liu, Wanping; Zhang, Yihao

doi:10.1155/2017/5939810

Cited by 5 publications

(2 citation statements)

References 31 publications

(33 reference statements)

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“…While satellite models like the CCIR model [133], [134] and FSPL model can be seen as too pessimistic and optimistic respectively, the use of FSPL with some realistic shadowing can potentially give reasonable results. Further studies on HAP channels can be found in [119], [120], [135].…”

Section: B Factors Affecting Coverage Extensionmentioning

confidence: 99%

A review of wireless communication using high-altitude platforms for extended coverage and capacity

Arum

Grace

Mitchell

2020

Computer Communications

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This paper provides an up-to-date review of wireless communications service provisioning in rural or remote areas from High-Altitude Platforms (HAPs) exploiting cellular radio spectrum. With the recent International Telecommunication Union (ITU) report showing that as much as 74% of the population in Africa, most of which are living in rural areas, do not have access to broadband, this paper focuses on the potential of using HAPs as an alternative to terrestrial systems for wireless communication in rural communities. Considering the typically low user densities in rural areas and the importance of HAP coverage maximization while ensuring harmless coexistence with terrestrial systems in rural areas, this paper explores extending the achievable wireless coverage from a HAP. This takes into consideration the coexistence of a HAP with terrestrial systems using intelligent techniques to dynamically manage radio resources and mitigate interference. Studies have shown that efficient intelligent radio resource and topology management can minimize inter-system interference and ensure coexistence with improved system performance. Potential techniques for coverage extension such as exploiting the spatial characteristics of array antennas, radio environment maps (REMs) and deviceto-device (D2D) communications are discussed. Generally, this paper presents a comprehensive review of significant HAP related studies and their outcomes.

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Section: B Factors Affecting Coverage Extensionmentioning

confidence: 99%

A review of wireless communication using high-altitude platforms for extended coverage and capacity

Arum

Grace

Mitchell

2020

Computer Communications

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“…However, the cost of the anchor node is higher than that of ordinary nodes. If 10% of the nodes are anchor nodes, the price of the network will increase 10 times [8][9][10][11][12][13]. However, when the unknown node is located, it will no longer need expensive anchor nodes.…”

Section: Background and Researchmentioning

confidence: 99%

Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

Liu

2018

Wireless Communications and Mobile Computing

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With the rapid development of wireless sensor network (WSN) technology and its localization method, localization is one of the basic services for data collection in WSN. The localization accuracy often depends on the accuracy of distance estimation. Because of the constraint in size, power, and cost of sensor nodes, the investigation of efficient location algorithms which satisfy the basic accuracy requirement for WSN meets new challenges. This paper proposes a novel intelligent node localization algorithm in WSN based on beacon nodes to improve the precision in location estimation. Firstly, system model of WSN node localization is constructed according to the WSN environment. Then traditional WSN node localization methods such as DV-HOP, GA, and PSO are studied. Localization algorithm of WSN is proposed by using dynamic mathematics modeling. And the result of simulation, which is compared to the traditional algorithm, indicated that this algorithm is better to improve the accuracy and coverage of WSN. The simulation results show that the performance of the proposed WSN location algorithm is better than the traditional localization algorithms.

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