Auction-Based Multichannel Cooperative Spectrum Sharing in Hybrid Satellite-Terrestrial IoT Networks

Zhang, Xiaokai; Guo, Daoxing; An, Kang; Zheng, Gan; Chatzinotas, Symeon

doi:10.1109/jiot.2020.3037408

Cited by 37 publications

(12 citation statements)

References 39 publications

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“…Authors [28] proposed a method using non-orthogonal multiple access (NOMA) scheme for SIoT downlink system to overcome long-term network utility problems. Author in [29] proposed a scheme to overcome the problem of spectrum shortage in terrestrial-based IoT network. Authors [30] introduced a network utility maximization resource allocation for NOMA in SIOT.…”

Section: Literature Survey and Research Gaps Based On Leo Siotmentioning

confidence: 99%

Deep Reinforcement Learning-Based Long Short-Term Memory for Satellite IoT Channel Allocation

Durga¹,

Rajeshwari²,

Allehaibi³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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In recent years, the demand for smart wireless communication technology has increased tremendously, and it urges to extend internet services globally with high reliability, less cost and minimal delay. In this connection, low earth orbit (LEO) satellites have played prominent role by reducing the terrestrial infrastructure facilities and providing global coverage all over the earth with the help of satellite internet of things (SIoT). LEO satellites provide wide coverage area to dynamically accessing network with limited resources. Presently, most resource allocation schemes are designed only for geostationary earth orbit (GEO) satellites. For LEO satellites, resource allocation is challenging due to limited availability of resources. Moreover, due to uneven distribution of users on the ground, the satellite remains unaware of the users in each beam and therefore cannot adapt to changing state of users among the beams. In this paper, long short-term memory (LSTM) neural network has been implemented for efficient allocation of channels with the help of deep reinforcement learning (DRL) model. We name this model as DRL-LSTM scheme. Depending on the pool of resources available to the satellite, a channel allocation method based on the user density in each beam is designed. To make the satellite aware of the number of users in each beam, previous information related to the user density is provided to LSTM. It stores the information and allocates channels depending upon the requirement. Extensive simulations have been carried out which have shown that the DRL-LSTM scheme performs better as compared to the traditional and recently proposed schemes.

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Section: Literature Survey and Research Gaps Based On Leo Siotmentioning

confidence: 99%

Deep Reinforcement Learning-Based Long Short-Term Memory for Satellite IoT Channel Allocation

Durga¹,

Rajeshwari²,

Allehaibi³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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“…As a potential future communication network architecture, the integrated satellite multiple terrestrial relay network (ISMTRN) absorbs and combines the advantages of SatCom and terrestrial communication, which guarantees the communication demands of the users and diversifies the communication ways [ 3 , 4 , 5 ]. It is becoming the research hotspot and has important practical significance for future communication development.…”

Section: Introductionmentioning

confidence: 99%

Covert Performance for Integrated Satellite Multiple Terrestrial Relay Networks with Partial Relay Selection

Liu

Shuai

et al. 2022

Sensors

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Integrated satellite multiple terrestrial relay network (ISMTRN) is a new network architecture that combines satellite communication with terrestrial communication. It both utilizes the advantages of the two systems and overcomes their shortcomings. However, security issues inevitably arise in the ISMTRN resulting from the broad coverage of the satellite beams and the openness of wireless communication. One of the promising methods to achieve secure transmission is covert communication technology, which has been a hot discussion topic in recent years. In this paper, we investigate the performance of covert communication in the ISMTRN with partial relay selection. Particularly, when the satellite transmits its signal to the user, we consider the scenario that the selected relay opportunistically sends covert information to the destination. Furthermore, the closed-form error detection probability and average covert communication rate are derived. Finally, numerical simulation results are provided to reveal the impact of critical parameters on system covert performance.

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“…As a promising network architecture for the future communications, ISTN has momentous practical significance, which is able to overcome obstacles and geographical constraints [9][10][11]. In [10], the authors utilized auction mechanism to reduce the system consumption of ISTN, and Hungarian algorithm was applied to solve the optimization problem. An integrated multibeam method was designed to maximize aggregated rate of ISTN in [11].…”

Section: Introductionmentioning

confidence: 99%

NOMA-Based Overlay Cognitive Satellite-UAV-Terrestrial Networks with Multiple Primary Users

Liu

Guo

et al. 2022

Wireless Communications and Mobile Computing

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Satellite communication is becoming more and more significant in present and future communication systems for its unique advantages of strong survivability and seamless coverage, which can offset the defects of terrestrial communication such as being restricted by terrain and little coverage. Moreover, unmanned aerial vehicle (UAV)-assisted communication is considered as a promising development direction due to its flexibility and expansibility in the integrated satellite-terrestrial networks (ISTN). In addition, to overcome the spectrum shortage and low spectrum utilization problems, cognitive radio and nonorthogonal multiple access (NOMA) has been widely utilized to enhance spectrum efficiency, which is considered as the key technologies of the next generation communication. In this regard, our paper investigates the performance of cognitive satellite-UAV-terrestrial networks with NOMA scheme and multiple primary users. Specifically, the exact expressions of outage probability (OP) and ergodic capacity for both primary network and secondary network are derived. To gain further views, the asymptotic expression of OP and diversity orders for the two networks are provided. Finally, through numerical simulations, the correctness of the theoretical derivations is verified and the influences of critical variables on system indexes are also analyzed.

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Auction-Based Multichannel Cooperative Spectrum Sharing in Hybrid Satellite-Terrestrial IoT Networks

Cited by 37 publications

References 39 publications

Deep Reinforcement Learning-Based Long Short-Term Memory for Satellite IoT Channel Allocation

Deep Reinforcement Learning-Based Long Short-Term Memory for Satellite IoT Channel Allocation

Covert Performance for Integrated Satellite Multiple Terrestrial Relay Networks with Partial Relay Selection

NOMA-Based Overlay Cognitive Satellite-UAV-Terrestrial Networks with Multiple Primary Users

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