Performance Analysis of Cooperative Nonorthogonal Multiple Access Scheme in Two-Layer GEO/LEO Satellite Network

Ge, Ruixing; Bian, Dongming; An, Kang; Cheng, Jianwei; Zhu, Hongpeng

doi:10.1109/jsyst.2021.3091781

Cited by 15 publications

(6 citation statements)

References 33 publications

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“…According to the analysis of the preceding context, it is inferred that while Sat i has access to its channel coefficient h t i,n , only statistical knowledge about Sat i ′ 's channel coefficient ht i ′ ,n is available. According to [23], we have…”

Section: B Statistical Channel Modelmentioning

confidence: 99%

“…The channel fading factor, | hs | 2 , characterizes the impact of scattering and masking effects induced by barriers and obscuration around terrestrial cells in satellite communications [24]- [27]. To accurately depict the distribution of | hs | 2 , we adopt the well-established shadowed-Rician fading channel model, which has been proved to be an accurate and practical model for the satellite-to-terrestrial channel in the existing research works [23], [24], [28], [29]. Specifically, the probability density function (P.D.F) of | hs | 2 follows [29, Eq.…”

Section: B Statistical Channel Modelmentioning

confidence: 99%

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Dynamic Resource Allocation for Multi-Satellite Cooperation Networks: A Decentralized Scheme Under Statistical CSI

Zhao,

Yu,

Pan

et al. 2024

IEEE Access

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The densification of low-Earth orbit (LEO) constellations and the development of inter-satellite links enable the cooperative transmission of multiple satellites. This paper investigates a decentralized resource allocation strategy for multi-satellite cooperation networks under statistical channel state information (CSI). Our formulation aims at minimizing the total matching error between non-uniform traffic requests and achievable throughput by jointly optimizing transmit power and beam illumination pattern. The original problem is a stochastic mixed-integer quadratic programming with the long-term accumulation nature, whose stochastic objective is first addressed by incorporating the outage probability constraint. Then we decompose the deterministic problem into a series of single-timeslot subproblems on the greedy basis, each of which is further decomposed for each satellite following the decentralized decision principle with a limited number of inter-satellite interactions required to obtain the overall resource allocation. Finally, the optimization problem at each satellite is solved by sequential quadratic programming (SQP)-based alternating optimization algorithm that iterates between the transmit power allocation and beam illumination design. Numerical results show the effectiveness of the proposed decentralized algorithm in reducing the total matching error by at least 27% over other baseline approaches.

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Section: B Statistical Channel Modelmentioning

confidence: 99%

Section: B Statistical Channel Modelmentioning

confidence: 99%

Dynamic Resource Allocation for Multi-Satellite Cooperation Networks: A Decentralized Scheme Under Statistical CSI

Zhao,

Yu,

Pan

et al. 2024

IEEE Access

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“…Tengyue et al [8] use the backbone/access network model and the "moderately connected" interstellar link concept to design a dual LEO/MEO link layer network architecture that meets the quality of service while reducing the complexity of the network system. Ge et al [9] established a GEO/LEO dual-layer satellite network architecture in a frequency coexistence scenario, taking into account the channel and dynamic characteristics between satellite nodes, and improving the spectral efficiency and signal reception reliability of GEO satellites.…”

Section: Related Workmentioning

confidence: 99%

An ANN-based Intelligent Spectrum Sensing Algorithm for Space-based Satellite Networks

2023

KSII TIIS

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In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in realtime, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

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“…In another paper, the same authors have maximized the sum capacity of NOMA LEO satellite networks by jointly optimizing the user pairing and power allocation [29]. Ge et al [30] have investigated outage probability and ergodic capacity for co-existing NOMA GEO-LEO satellite networks.…”

Section: A Recent Literature On Leo Satellite Networkmentioning

confidence: 99%

“…However, they do not consider NOMA and RIS in their proposed models. Then, some works proposed NOMA in LEO satellite communication networks [22]- [30], but their system models did not consider RIS technology. Of late, researchers have integrated RIS into LEO satellite networks using conventional OMA techniques [31]- [38].…”

Section: B Motivation and Contributionsmentioning

confidence: 99%

When RIS Meets GEO Satellite Communications: A New Sustainable Optimization Framework in 6G

Khan

Lagunas

Mahmood

et al. 2022

2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)

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Low Earth Orbit (LEO) satellite networks are expected to play a crucial role in providing high-speed internet access and low-latency communication worldwide. However, some challenges can affect the performance of LEO satellite networks. For example, they can face energy and spectral efficiency challenges, such as high power consumption and spectral congestion, due to the increasing number of satellites. Furthermore, mobile ground users tend to operate with low directive antennas, which pose significant challenges in closing the LEO-toground communication link, especially when operating at a highfrequency range. To overcome these challenges, energy-efficient technologies like reconfigurable intelligent surfaces (RIS) and advanced spectrum management techniques like non-orthogonal multiple access (NOMA) can be employed. RIS can improve signal quality and reduce power consumption, while NOMA can enhance spectral efficiency by sharing the same resources among multiple users. This paper proposes an energy-efficient RIS-assisted downlink NOMA communication for LEO satellite networks. The proposed framework simultaneously optimizes the transmit power of ground terminals of the LEO satellite and the passive beamforming of RIS while ensuring the quality of services. Due to the nature of the considered system and optimization variables, the energy efficiency maximization problem is non-convex. In practice, obtaining the optimal solution for such problems is very challenging. Therefore, we adopt alternating optimization methods to handle the joint optimization in two steps. In step 1, for any given phase shift vector, we calculate satellite transmit power towards each ground terminal using the Lagrangian dual method. Then, in step 2, given the transmit power, we design passive beamforming for RIS by solving the semi-definite programming. We also compare our solution with a benchmark framework having a fixed phase shift design and a conventional NOMA framework without involving RIS. Numerical results show that the proposed optimization framework achieves 21.47% and 54.9% higher energy efficiency compared to the benchmark and conventional frameworks.

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Performance Analysis of Cooperative Nonorthogonal Multiple Access Scheme in Two-Layer GEO/LEO Satellite Network

Cited by 15 publications

References 33 publications

Dynamic Resource Allocation for Multi-Satellite Cooperation Networks: A Decentralized Scheme Under Statistical CSI

Dynamic Resource Allocation for Multi-Satellite Cooperation Networks: A Decentralized Scheme Under Statistical CSI

An ANN-based Intelligent Spectrum Sensing Algorithm for Space-based Satellite Networks

When RIS Meets GEO Satellite Communications: A New Sustainable Optimization Framework in 6G

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