Improved LMS predictive link triggering for handover in HAPS communication system

He, Pengfei; Cheng, Naiping; Ni, Shuyan

doi:10.1109/wcsp.2016.7752747

Cited by 6 publications

(5 citation statements)

References 11 publications

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“…The simulation parameters of HAPS communication system are consistent with [11]. The mapping relationship between AMC and SINR used in this system can refer the air interface of IEEE802.16, which can be found in [12].…”

Section: Simulation Analysismentioning

confidence: 92%

A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

Cheng

2017

MATEC Web Conf.

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Abstract. The large changing of link capacity and number of users caused by the movement of both platform and users in communication system based on high altitude platform station (HAPS) will resulting in high dropping rate of handover and reduce resource utilization. In order to solve these problems, this paper proposes an adaptive call admission control strategy based on reinforcement learning approach. The goal of this strategy is to maximize long-term gains of system, with the introduction of cross-layer interaction and the service downgraded. In order to access different traffics adaptively, the access utility of handover traffics and new call traffics is designed in different state of communication system. Numerical simulation result shows that the proposed call admission control strategy can enhance bandwidth resource utilization and the performances of handover traffics.

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Section: Simulation Analysismentioning

confidence: 92%

A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

Cheng

2017

MATEC Web Conf.

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“…Additionally, the assumption of equal distances to the centre of the neighbouring cells from the centre of the overlap area is untenable in extended coverage scenario where cells differ in size and shape due to beam broadening. He et al propose adaptive handover schemes based on received signal strength (RSS) prediction [187] and cooperative transmission between multiple HAPs [188]. In [187], the HAP predicts the RSS of a mobile user at a given time instant, considering the user's speed and then decides whether the user should be handed over to another cell or not.…”

Section: B Handovermentioning

confidence: 99%

“…He et al propose adaptive handover schemes based on received signal strength (RSS) prediction [187] and cooperative transmission between multiple HAPs [188]. In [187], the HAP predicts the RSS of a mobile user at a given time instant, considering the user's speed and then decides whether the user should be handed over to another cell or not. The authors show in [188] that three platforms can cooperate during handover of a mobile user to minimize outage probability.…”

Section: B Handovermentioning

confidence: 99%

“…The effect of platform movement on handover is investigated in [181], [187]- [196]. The impact of platform swinging motion, at a frequency dependent on wind power and platform stabilization mechanism, on handover was studied in [189], [195], with the results showing that more network resources are required to support a burst of handover and that the probability of handover increases with increasing swing angle.…”

Section: B Handovermentioning

confidence: 99%

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

Arum

Grace

Mitchell

2020

Computer Communications

106

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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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“…When the threshold is too low, frequent handoffs are likely to happen; in contrast, if the threshold is too high, the handoff will be triggered too late causing long periods of communication disruption. In [215], by considering the received signal strength, the terminal of mobile speed, and the platform disturbance factors, the author proposed an adaptive handoff algorithm that predicts the received signal strength. In a similar approach, the author in [216] propose a prediction-based handoff decision algorithm with an adaptive threshold.…”

Section: Handoff Management In Haps Networkmentioning

confidence: 99%

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

Kurt¹,

Khoshkholgh²,

Alfattani³

et al. 2020

Preprint

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A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an altitude around 20 km and is instrumental for providing communication services. Triggered by the technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels and the battery energy density, and fueled by the flourishing industry ecosystems, the HAPS exerts itself as an indispensable component of the next generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature survey. We highlight the undiscovered potential of HAPS systems, and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are delineated. The notable contribution of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The provided extensive overview of the literature is crucial for substantiating our vision that that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).

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Improved LMS predictive link triggering for handover in HAPS communication system

Cited by 6 publications

References 11 publications

A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

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

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

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