Dynamic Spectrum Allocation for Heterogeneous Cognitive Radio Networks With Multiple Channels

被引:19
作者
Zhang, Wenjie [1 ]
Sun, Yingjuan [1 ]
Deng, Lei [2 ]
Yeo, Chai Kiat [3 ]
Yang, Liwei [4 ]
机构
[1] Minnan Normal Univ, Sch Comp Sci, Key Lab Data Sci & Intelligence Applicat, Zhangzhou 363000, Peoples R China
[2] Dongguan Univ Technol, Sch Elect Engn & Intelligentizat, Dongguan 523808, Peoples R China
[3] Nanyang Technol Univ, Dept Comp Engn, Singapore 639798, Singapore
[4] China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
来源
IEEE SYSTEMS JOURNAL | 2019年 / 13卷 / 01期
关键词
Cognitive radio (CR) networks; NP-complete; randomized rounding algorithm; spectrum allocation; RESOURCE-ALLOCATION; AUCTION; GAME;
D O I
10.1109/JSYST.2018.2822309
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The rapid growth of wireless communication technology has resulted in the increasing demand on spectrum resources. However, according to a recent study, most of the allocated frequency experiences significant underutilization. One important issue associated with spectrum management in heterogeneous cognitive radio networks is: How to appropriately allocate the spectrum to secondary sender-destination (S-D) pair for sensing and utilization. In this paper, the authors investigate the spectrum allocation problem under a more practical scenario where the heterogeneous characteristics of both the secondary S-D and primary channels are taken into consideration. With the objective to maximize the achievable throughput for secondary S-D, we formulate the spectrum allocation problem as a linear integer optimization problem under spectrum availability constraint, spectrum span constraint, and interference free constraint. This problem is proven to be Non-deterministic Polynomial (NP)-complete, and a recent result in theoretical computer science called randomized rounding algorithm with polynomial computational complexity is developed to find the rho-approximation solution. Evaluation results show that our proposed algorithm can achieve a close-to-optimal solution at a low level of computation complexity.
引用
收藏
页码:53 / 64
页数:12
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