Multi-Satellite Cooperative Beamforming ALOHA for LEO Satellite IoT Networks

In this paper, we proposed a cooperative beamforming ALOHA (CBA) scheme based on linearly constrained minimum variance criterion for low Earth orbit satellite (LEO) IoT networks to solve the problem of ‘deadlock’ in multi-satellite scenario. In multi-satellite overlapping coverage areas, packets can be received by multiple satellite receivers by sending them only once, which forms the concept of spatial diversity. The cooperative beamforming collision resolution technique combined with successive interference cancellation scheme is design to efficiently resolve packet collision by iteration way at the gateway station. The performance of cooperative beamforming ALOHA scheme is evaluated via mathematical analysis and simulations. Simulation results show that the proposed CBA scheme can effectively solve the problem of ‘deadlock’ and improve the performances of random access compared with benchmark problems.

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Smart Beamforming for Direct LEO Satellite Access of Future IoT

Sensors ◽

10.3390/s21144877 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4877

Author(s):

Marius Caus ◽

Ana Perez-Neira ◽

Eduard Mendez

Keyword(s):

Resource Sharing ◽

Large Population ◽

Satellite Communications ◽

Spatial Diversity ◽

Open Loop ◽

Low Earth Orbit ◽

Collision Probability ◽

Practical Implementation ◽

Free Access ◽

Leo Satellite

Non-terrestrial networks (NTN) are expected to play a key role in extending and complementing terrestrial 5G networks in order to provide services to air, sea, and un-served or under-served areas. This paper focuses the attention on the uplink, where terminals are able to establish a direct link with the NTN at Ka-band. To reduce the collision probability when a large population of terminals is transmitting simultaneously, we propose a grant-free access scheme called resource sharing beamforming access (RSBA). We study RBSA for low Earth orbit (LEO) satellite communications with massive multiple-input multiple-output (MIMO). The idea is to benefit from the spatial diversity to decode multiple overlapped signals. We have devised a blind and open-loop beamforming technique, where neither the receiver must carry out brute-force search in azimuth and elevation, nor are the terminals required to report channel state information. Upon deriving the theoretical throughput, we show that RBSA is appropriate for grant-free access to LEO satellite, it reduces the probability of collision, and thus it increases the number of terminals that can access the media. Practical implementation aspects have been tackled, such as the estimation of the required statistics, and the determination of the number of users.

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A modular structure for implementation of linearly constrained minimum variance beamformers

IEEE Transactions on Signal Processing ◽

10.1109/78.91191 ◽

1991 ◽

Vol 39 (10) ◽

pp. 2343-2346 ◽

Cited By ~ 15

Author(s):

T.-C. Liu ◽

B. Van Veen

Keyword(s):

Minimum Variance ◽

Modular Structure ◽

Linearly Constrained

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Linearly constrained minimum variance method for spherical microphone arrays in a coherent environment

2011 Joint Workshop on Hands-free Speech Communication and Microphone Arrays ◽

10.1109/hscma.2011.5942416 ◽

2011 ◽

Cited By ~ 5

Author(s):

Yotam Peled ◽

Boaz Rafaely

Keyword(s):

Minimum Variance ◽

Microphone Arrays ◽

Variance Method ◽

Linearly Constrained ◽

Spherical Microphone Arrays ◽

Minimum Variance Method

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Energy-Constrained Design of Joint NOMA-Diversity Schemes with Imperfect Interference Cancellation

Sensors ◽

10.3390/s21124194 ◽

2021 ◽

Vol 21 (12) ◽

pp. 4194

Author(s):

Fulvio Babich ◽

Giulia Buttazzoni ◽

Francesca Vatta ◽

Massimiliano Comisso

Keyword(s):

Interference Cancellation ◽

Energy Levels ◽

Random Access ◽

Actual Performance ◽

Available Energy ◽

Fifth Generation ◽

Code Modulation ◽

Energy Constrained ◽

The Relationship ◽

The Internet Of Things

This study proposes a set of novel random access protocols combining Packet Repetition (PR) schemes, such as Contention Resolution Diversity Slotted Aloha (CRDSA) and Irregular Repetition SA (IRSA), with Non Orthogonal Multiple Access (NOMA). Differently from previous NOMA/CRDSA and NOMA/IRSA proposals, this work analytically derives the energy levels considering two realistic elements: the residual interference due to imperfect Interference Cancellation (IC), and the presence of requirements on the power spent for the transmission. More precisely, the energy-limited scenario is based on the relationship between the average available energy and the selected code modulation pair, thus being of specific interest for the implementation of the Internet of Things (IoT) technology in forthcoming fifth-generation (5G) systems. Moreover, a theoretical model based on the density evolution method is developed and numerically validated by extensive simulations to evaluate the limiting throughput and to explore the actual performance of different NOMA/PR schemes in energy-constrained scenarios.

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The Sentinel-3 SLSTR Atmospheric Motion Vectors Product at EUMETSAT

Remote Sensing ◽

10.3390/rs13091702 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1702

Author(s):

Kévin Barbieux ◽

Olivier Hautecoeur ◽

Maurizio De Bartolomei ◽

Manuel Carranza ◽

Régis Borde

Keyword(s):

Land Surface ◽

Weather Prediction ◽

Forecast Model ◽

Low Earth Orbit ◽

Reference Image ◽

Motion Vectors ◽

Infrared Imager ◽

Atmospheric Motion ◽

Atmospheric Motion Vectors ◽

Leo Satellite

Atmospheric Motion Vectors (AMVs) are an important input to many Numerical Weather Prediction (NWP) models. EUMETSAT derives AMVs from several of its orbiting satellites, including the geostationary satellites (Meteosat), and its Low-Earth Orbit (LEO) satellites. The algorithm extracting the AMVs uses pairs or triplets of images, and tracks the motion of clouds or water vapour features from one image to another. Currently, EUMETSAT LEO satellite AMVs are retrieved from georeferenced images from the Advanced Very-High-Resolution Radiometer (AVHRR) on board the Metop satellites. EUMETSAT is currently preparing the operational release of an AMV product from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellites. The main innovation in the processing, compared with AVHRR AMVs, lies in the co-registration of pairs of images: the images are first projected on an equal-area grid, before applying the AMV extraction algorithm. This approach has multiple advantages. First, individual pixels represent areas of equal sizes, which is crucial to ensure that the tracking is consistent throughout the processed image, and from one image to another. Second, this allows features that would otherwise leave the frame of the reference image to be tracked, thereby allowing more AMVs to be derived. Third, the same framework could be used for every LEO satellite, allowing an overall consistency of EUMETSAT AMV products. In this work, we present the results of this method for SLSTR by comparing the AMVs to the forecast model. We validate our results against AMVs currently derived from AVHRR and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). The release of the operational SLSTR AMV product is expected in 2022.

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