Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels
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...
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sg-ntu-dr.10356-825072020-03-07T11:48:51Z Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels Zhang, Wenjie Sun, Yingjuan Deng, Lei Yeo, Chai Kiat Yang, Liwei School of Computer Science and Engineering Cognitive Radio (CR) Networks NP-complete DRNTU::Engineering::Computer science and engineering 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. Accepted version 2019-04-10T06:53:47Z 2019-12-06T14:56:59Z 2019-04-10T06:53:47Z 2019-12-06T14:56:59Z 2019 Journal Article Zhang, W., Sun, Y., Deng, L., Yeo, C. K., & Yang, L. (2019). Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels. IEEE Systems Journal, 13(1), 53-64. doi:10.1109/JSYST.2018.2822309 1932-8184 https://hdl.handle.net/10356/82507 http://hdl.handle.net/10220/48002 10.1109/JSYST.2018.2822309 en IEEE Systems Journal © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/JSYST.2018.2822309 11 p. application/pdf |
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Cognitive Radio (CR) Networks NP-complete DRNTU::Engineering::Computer science and engineering Zhang, Wenjie Sun, Yingjuan Deng, Lei Yeo, Chai Kiat Yang, Liwei Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels |
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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. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Zhang, Wenjie Sun, Yingjuan Deng, Lei Yeo, Chai Kiat Yang, Liwei |
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Article |
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Zhang, Wenjie Sun, Yingjuan Deng, Lei Yeo, Chai Kiat Yang, Liwei |
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Zhang, Wenjie |
title |
Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels |
title_short |
Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels |
title_full |
Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels |
title_fullStr |
Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels |
title_full_unstemmed |
Dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels |
title_sort |
dynamic spectrum allocation for heterogeneous cognitive radio networks with multiple channels |
publishDate |
2019 |
url |
https://hdl.handle.net/10356/82507 http://hdl.handle.net/10220/48002 |
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1681049070424031232 |