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CLC number: TN92

On-line Access: 2018-05-07

Received: 2017-01-23

Revision Accepted: 2017-04-20

Crosschecked: 2018-03-08

Cited: 0

Clicked: 1601

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yun-zheng Tao

http://orcid.org/0000-0002-8734-2729

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Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.3 P.367-378

10.1631/FITEE.1700067


A projected gradient based game theoretic approach for multi-user power control in cognitive radio network


Author(s):  Yun-zheng Tao, Chun-yan Wu, Yu-zhen Huang, Ping Zhang

Affiliation(s):  State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; more

Corresponding email(s):   yunzhengtao@bupt.edu.cn, chunyanwuarkiro@163.com, yzh_huang@sina.com, pzhang@bupt.edu.cn

Key Words:  Cognitive radio networks, Multi-user power control, Non-cooperative game, Nash equilibrium, Projected gradient


Yun-zheng Tao, Chun-yan Wu, Yu-zhen Huang, Ping Zhang. A projected gradient based game theoretic approach for multi-user power control in cognitive radio network[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(3): 367-378.

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Abstract: 
The fifth generation (5G) networks have been envisioned to support the explosive growth of data demand caused by the increasing traditional high-rate mobile users and the expected rise of interconnections between human and things. To accommodate the ever-growing data traffic with scarce spectrum resources, cognitive radio (CR) is considered a promising technology to improve spectrum utilization. We study the power control problem for secondary users in an underlay CR network. Unlike most existing studies which simplify the problem by considering only a single primary user or channel, we investigate a more realistic scenario where multiple primary users share multiple channels with secondary users. We formulate the power control problem as a non-cooperative game with coupled constraints, where the Pareto optimality and achievable total throughput can be obtained by a nash equilibrium (NE) solution. To achieve NE of the game, we first propose a projected gradient based dynamic model whose equilibrium points are equivalent to the NE of the original game, and then derive a centralized algorithm to solve the problem. Simulation results show that the convergence and effectiveness of our proposed solution, emphasizing the proposed algorithm, are competitive. Moreover, we demonstrate the robustness of our proposed solution as the network size increases.

认知无线网络中一种基于投影梯度的多用户功率控制方法

概要:5G网络被认为能够支持未来爆炸性增长的数据需求,这主要得益于不断增长的高速移动用户数量以及人与物之间的交互预期。认知无线电(cognitive radio, CR)是提高频谱利用率的有效技术之一,可适应日益增长的数据流量和稀缺的频谱资源。本文研究了基于衬垫式频谱共享的认知无线网络中的次用户功率控制问题。与现有文献大多通过假设单一主用户或者单一信道来简化问题不同,本文研究了多主用户多次用户多信道这一更符合实际的场景。我们将功率控制问题描述为一个具有耦合约束的非合作博弈,其帕累托最优性和最大次网络吞吐量可通过纳什均衡解得。为得到该纳什均衡解,首先提出一种基于投影梯度的动态模型,证明该模型的平衡点等价于原博弈的纳什均衡,并提出一种集中式算法求解该平衡点。仿真结果验证了所提出算法的收敛性、有效性和优势,并且在网络规模增大的情况下验证了算法的鲁棒性。

关键词:认知无线网络;多用户功率控制;非合作博弈;纳什均衡;投影梯度

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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