Multi-Resource Management for Multi-Tier Space Information Networks : A Cooperative Game
Mi, X., Yang, C., & Chang, Z. (2019). Multi-Resource Management for Multi-Tier Space Information Networks : A Cooperative Game. In IWCMC 2019 : Proceedings of the 15th International wireless communications and mobile computing conference (pp. 948-953). IEEE. International Wireless Communications and Mobile Computing Conference. https://doi.org/10.1109/iwcmc.2019.8766545
Date
2019Copyright
© 2019 IEEE
With the drastic increase of space information network (SIN) traffic and the diversity of network traffic types, the optimal allocation of the scarce network resources is of great significance for optimizing the SIN system capability. In this paper, we propose a multi-resource management method for multi-tier SIN using the cooperative Nash bargaining solution. Since the original problem is a non-convex problem, we firstly make logarithmic transition, and then find a tightest lower bound function to convert the initial problem into a convex one. In order to carry out the optimal bandwidth and power allocation in SIN, we construct a joint bandwidth and power allocation (JBPA) algorithm. Simulation results show the performance improvement of the JBPA scheme and the convergence of JBPA algorithm.
Publisher
IEEEParent publication ISBN
978-1-5386-7747-6Conference
Is part of publication
IWCMC 2019 : Proceedings of the 15th International wireless communications and mobile computing conferenceISSN Search the Publication Forum
2376-6492Keywords
Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/32171018
Metadata
Show full item recordCollections
Additional information about funding
This work is supported by the open research fund of National Mobile Communications Research Laboratory Southeast UniversityNo. 2019D10; by the Fundamental Research Funds for the Central Universities(2018); by the National Science Foundation of China (91638202); .License
Related items
Showing items with similar title or keywords.
-
Generative Diffusion Model-Based Deep Reinforcement Learning for Uplink Rate-Splitting Multiple Access in LEO Satellite Networks
Wang, Xingjie; Wang, Kan; Zhang, Di; Li, Junhuai; Zhou, Momiao; Hämäläinen, Timo (IEEE Computer Society Press, 2024)This work studies the joint transmit power control and receive beamforming in uplink rate splitting multiple access (RSMA)-based low earth orbit (LEO) satellite networks, using both generative diffusion model and proximal ... -
Spectrum and energy efficient solutions for OFDMA collaborative wireless networks
Chang, Zheng (University of Jyväskylä, 2013) -
Joint Spectral and Energy Efficiency Optimization for Downlink NOMA Networks
Khan, Wali Ullah; Jameel, Furqan; Ristaniemi, Tapani; Khan, Shafiullah; Sidhu, Guftaar Ahmad Sardar; Liu, Ju (Institute of Electrical and Electronics Engineers, 2020)Non-orthogonal multiple access (NOMA) holds the promise to be a key enabler of 5G communication. However, the existing design of NOMA systems must be optimized to achieve maximum rate while using minimum transmit power. ... -
Optimal Buffer Resource Allocation in Wireless Caching Networks
Liu, Tingting; Chang, Zheng; Li, Jun; Shu, Feng; Ristaniemi, Tapani; Han, Zhu (IEEE, 2019)Wireless caching systems have been exhaustively investigated in recent years. Due to limited buffer capacity, and unbalanced arrival and service rates, the backlogs may exist in the caching node and even cause buffer ... -
Cooperative spectrum sensing schemes for future dynamic spectrum access infrastructures
Abdi Mahmoudaliloo, Younes (University of Jyväskylä, 2016)