Optimal Power Control for Cognitive LEO Constellation With Terrestrial Networks

Hu, Jing; Li, Guangxia; Bian, Dongming; Gou, Liang; Wang, Chuang

doi:10.1109/lcomm.2019.2961880

Cited by 17 publications

(8 citation statements)

References 12 publications

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“…In [28], with tools from stochastic geometry, authors have developed a method to characterize the magnitude of Doppler shifts in a LEO network. Resource control of a satellite-terrestrial network was investigated in [29], in order to minimize the outage probability and maximize the data rate. Focusing on only a single spotbeam, the hybrid satellite-terrestrial network supporting 5G infrastructure has been presented in [30], [31].…”

Section: A Related Workmentioning

confidence: 99%

Nonhomogeneous Stochastic Geometry Analysis of Massive LEO Communication Constellations

Okati

Riihonen

2022

IEEE Trans. Commun.

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Providing truly ubiquitous connectivity requires development of low Earth orbit (LEO) satellite Internet, whose theoretical study is lagging behind network-specific simulations. In this paper, we derive analytical expressions for the downlink coverage probability and average data rate of a massive inclined LEO constellation in terms of total interference power's Laplace transform in the presence of fading and shadowing, ergo presenting a stochastic geometry-based analysis. We assume the desired link to experience Nakagami-m fading, which serves to represent different fading scenarios by varying integer m, while the interfering channels can follow any fading model without an effect on analytical tractability. To take into account the inherent non-uniform distribution of satellites across different latitudes, we model the LEO network as a nonhomogeneous Poisson point process with its intensity being a function of satellites' actual distribution in terms of constellation size, the altitude of the constellation, and the inclination of orbital planes. From the numerical results, we observe optimum points for both the constellation altitude and the number of orthogonal frequency channels; interestingly, the optimum user's latitude is greater than the inclination angle due to the presence of fewer interfering satellites. Overall, the presented study facilitates general stochastic evaluation and planning of satellite Internet constellations without specific orbital simulations or tracking data on satellites' exact positions in space.

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Section: A Related Workmentioning

confidence: 99%

Nonhomogeneous Stochastic Geometry Analysis of Massive LEO Communication Constellations

Okati

Riihonen

2022

IEEE Trans. Commun.

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“…Power control schemes from the long-term and short-term perspectives to tackle spectrum sharing problems [74] Yes No…”

Section: Capacity Power Allocationmentioning

confidence: 99%

“…To reduce the system cost of centralized processing, Chen et al proposed a distributed power allocation scheme based on the game theory [73]. By taking the mobility of LEO satellites into account, Hu et al investigated a power control scheme to simultaneously maximize the capacity and minimize the OP [74]. Wang et al proposed a joint power allocation and channel access scheme to maximize the rate of terrestrial users [75].…”

Section: Capacitymentioning

confidence: 99%

5G Embraces Satellites for 6G Ubiquitous IoT: Basic Models for Integrated Satellite Terrestrial Networks

Fang

Feng

Wei

et al. 2021

IEEE Internet Things J.

135

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“…However, the issue of spectrum scarcity has restricted the development of them. To alleviate pressure on limited spectrum resource, CR has been introduced for the satellite terrestrial network as a promising technology [14][15][16][17][18][19][20]. In [17], the outage probability of the cognitive network with interference temperature constraint is studied, where the satellite communication network acts as the PU while the terrestrial mobile network serves as the SU.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Cooperative Spectrum Sensing in Cognitive Satellite Terrestrial Networks

Bian

et al. 2020

IEEE Access

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Having the ability to provide seamless coverage and alleviate the frequency scarcity, the cognitive satellite terrestrial network becomes a promising candidate for future communication networks. In the cognitive network, spectrum sensing plays an important role in detecting the channel state for opportunistic utilization, where cooperative spectrum sensing is employed to improve the sensing performance. Additionally, it is critical for battery-powered satellite mobile terminals to diminish energy consumption costs. In this regard, this paper proposes a novel sensing-based cognitive satellite terrestrial network (SCSTN), which integrates the cognitive satellite terrestrial network with the distributed cooperative spectrum sensing network. Specifically, we focus on energy-efficient cooperative sensing in the SCSTN, which maximizes the energy efficiency (EE) of the cognitive satellite network by a tradeoff between the average throughput and the average energy consumption. In the SCSTN, the energy detection threshold of the sensing node and the rule threshold of fusion affect the average throughput and the average energy consumption. Hence, the objective of this paper is to identify the energy detection threshold of the sensing node and the rule threshold of fusion to achieve the maximum EE. We first study the EE formulation of the rule threshold of fusion when the energy detection threshold of the sensing node is given, and transform the ratio-type objective function of EE into a parametric formulation. Subsequently, by exploring the relationship between the two formulations and making use of the monotonicity of the parametric formulation, an algorithm to obtain the optimal rule threshold of fusion for the original problem is developed. Furthermore, we study the optimal formulation of the energy sensing threshold of the sensing node and discuss the effect of the sensing duration and the number of distributed cooperative terminals on the EE. Lastly, the performance of the proposed method is evaluated through numerical simulation results.

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Optimal Power Control for Cognitive LEO Constellation With Terrestrial Networks

Cited by 17 publications

References 12 publications

Nonhomogeneous Stochastic Geometry Analysis of Massive LEO Communication Constellations

Nonhomogeneous Stochastic Geometry Analysis of Massive LEO Communication Constellations

5G Embraces Satellites for 6G Ubiquitous IoT: Basic Models for Integrated Satellite Terrestrial Networks

Energy-Efficient Cooperative Spectrum Sensing in Cognitive Satellite Terrestrial Networks

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