Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (11): 3372-3378.doi: 10.13229/j.cnki.jdxbgxb.20230006

Previous Articles    

Power allocation for a performance-selected underlay cognitive radio

Ming-yue ZHOU(),Yi-feng LI   

  1. School of Science and Engineering,Changchun University of Technology,Changchun 130012,China
  • Received:2023-01-04 Online:2024-11-01 Published:2025-04-24

Abstract:

Aiming at the different target requirements of each user in the Underlay cognitive radio network, a power allocation scheme that flexibly adjusts the target according to its actual needs is proposed. A dual-objective adjustment factor is proposed to configure the performance indicators of user power consumption and quality of service (QoS), and a performance selection objective function is constructed to effectively solve the problem of only considering unilateral performance improvement under the traditional power allocation algorithm. In order to verify the effectiveness of the scheme, the user power and signal to noise ratio under different adjustment factors are simulated and analyzed. Experiments show that by adjusting the target factor, low power consumption and high quality of service can be selected to meet the different needs of users in the same scenario.

Key words: cognitive radio, power allocation, adjustment factors

CLC Number: 

  • TN 929.5

Fig.1

Geometric figure of convex function"

Fig.2

Power of the PS algorithm and TMC algorithm"

Fig.3

Interference performance comparison between PS algorithm and TMC algorithm"

Fig.4

Performance comparison between PS algorithm and TMP algorithm"

Fig.5

Validity verification of PS algorithm adjustment factor"

1 李玲. 认知无线电技术及其典型应用探讨[J]. 中国新通信, 2021, 23(16): 92-93.
Li Ling. Discussion on cognitive radio technology and its typical application[J]. China New Telecommunications, 2021, 23(16): 92-93.
2 Riddle A. Comprehending cognitive radios[J]. IEEE Microwave Magazine, 2017, 18(5): 120-132.
3 陈威龙, 梁俊, 肖楠, 等. 能效优先的鲁棒功率控制算法[J]. 西安交通大学学报, 2021, 55(2): 143-149.
Chen Wei-long, Liang Jun, Xiao Nan, et al. A robust power control algorithm with priority of energy efficiency[J]. Journal of Xi'an Jiaotong University, 2021, 55(2): 143-149.
4 Sun M, Jin M, Guo Q, et al. Throughput maximization for cognitive radio with wirelessly powered primary users[J]. IEEE Systems Journal, 2019, 14(2): 2432-2442.
5 马蓓, 张海林, 张兆维, 等. 基于不完全信道信息的D2D功率分配算法[J]. 吉林大学学报: 工学版, 2016, 46(4): 1320-1324.
Ma Bei, Zhang Hai-lin, Zhang Zhao-wei, et al. Imperfect channel state information based D2D power allocation algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2016, 46(4):1320-1324.
6 Wang J, Chen J, You L, et al. Robust power control under location and channel uncertainty in cognitive radio networks[J]. IEEE Wireless Communications Letters, 2017, 4(2): 113-116.
7 Thanuja T C, Daman K A, Patil A S. Optimized spectrum sensing techniques for enhanced throughput in cognitive radio network[C]∥ International Conference on Emerging Smart Computing and Informatics, Pune, India, 2020: 137-141.
8 Wang H, Zhu M, Zhou M. A robust power allocation scheme in ad-hoc cognitive radio networks[J]. International Journal of Online Engineering, 2017, 13(8): 45-59.
9 Xu Y, Chen Q, Huang X. Robust power control for OFDM-based cognitive radio networks with QOS guarantee[J]. Wireless Personal Communications, 2017, 96(2): 2125-2140.
10 Zhu L, Zhao X H. Robust power allocation for OFDM based underlay cognitive radio networks with channel uncertainties[J]. Wireless Personal Communications, 2017, 94(4): 3531-3547.
11 王宏志, 姜方达, 周明月. 基于遗传粒子群优化算法的认知无线电系统功率分配[J]. 吉林大学学报: 工学版, 2019, 49(4): 1363-1368.
Wang Hong-zhi, Jiang Fang-da, Zhou Ming-yue. Power allocation of cognitive radio system based on genetic particle swarm optimization[J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(4): 1363-1368.
12 Yousefvand M, Ansari N, Khorsandi S. Maximizing network capacity of cognitive radio networks by capacity-aware spectrum allocation[J]. IEEE Transactions on Wireless Communications, 2015, 14(9): 5058-5067.
13 Pan C, Wang J, Zhang W, et al. Power minimization in multi-band multi-antenna cognitive radio networks[J]. IEEE Transactions on Wireless Communications, 2014, 13(9): 5056-5069.
14 Tsiropoulos G I, Dobre O A, Ahmed M H, et al. Joint channel assignment and power allocation in cognitive radio networks[C]∥ IEEE Global Communications Conference, Austin, USA, 2014: 876-881.
15 Waqas M, Aslam S, Ali Z, et al. Resource optimization for cognitive radio based device to device communication under an energy harvesting scenario[J]. IEEE Access, 2020, 8(1): 24862-24872.
16 Wang H, Yan Y, Zhou M. Resource allocation in OFDM-based cognitive radios under proportional rate constraint[C]∥ Communications and Networking: 12th International Conference, Xi´an, China, 2017: 416-425.
17 朱孟, 王宏志, 周明月, 等. 基于鲁棒的认知无线电功率分配算法[J]. 长春工业大学学报: 自然科学版, 2017, 38(1): 43-47.
Zhu Meng, Wang Hong-zhi, Zhou Ming-yue, et al. Robust power allocation algorithm for cognitive radio systems[J]. Journal of Changchun University of Technology (Natural Science Edition), 2017, 38(1): 43-47.
[1] Liang CHU,Li-jia DONG,Nan XU,Li-feng ZHANG,Yi-fan JIA,Zhi-hua YANG. Powertrain configuration and power distribution of extended electric vehicle based on open winding motor [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(1): 72-82.
[2] Cui-ran LI,Yong-sheng YU,Jian-li XIE. Dynamic game algorithm for spectrum sharing based on priority of secondary users [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 315-323.
[3] Hong⁃zhi WANG,Fang⁃da JIANG,Ming⁃yue ZHOU. Power allocation of cognitive radio system based on genetic particle swarm optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1363-1368.
[4] LI Zhao, RAO Zheng-fa, CAI Shen-jin. Priority queue based two-layer centralized spectrum sharing in cooperative cognitive radio networks [J]. 吉林大学学报(工学版), 2016, 46(5): 1651-1659.
[5] JIN Shun-fu, YAO Xing-hua, HUO Zhan-qiang. Performance of the dynamic channel bonding strategy with imperfect channel sensing [J]. 吉林大学学报(工学版), 2016, 46(5): 1667-1674.
[6] LUAN Lei, ZHAO Xiao-hui, XU Yong-jun. Region oriented spectrum sensing model for cognitive radio system [J]. 吉林大学学报(工学版), 2016, 46(4): 1304-1312.
[7] MA Bei, ZHANG Hai-lin, ZHANG Zhao-wei, ZHONG Ming. Imperfect channel state information based D2D power allocation algorithm [J]. 吉林大学学报(工学版), 2016, 46(4): 1320-1324.
[8] YANG Li-biao, ZHAO Hong-lin, JIA Min. Neighboring group control channel allocation or cognitive radio Ad Hoc network [J]. 吉林大学学报(工学版), 2016, 46(2): 663-670.
[9] CHEN Jian,FAN Guang-hui,KUO Yong-hong. Hierarchical optimization algorithm for resource allocation in relay-assisted cognitive radio network [J]. 吉林大学学报(工学版), 2014, 44(5): 1498-1505.
[10] ZHAO Xiao-hui,SHA Jing-qi. Resource allocation algorithm in DF relay assisted OFDM cognitive radio systems [J]. 吉林大学学报(工学版), 2014, 44(5): 1481-1487.
[11] HE Yan, ZHAO Xiao-hui. Compressed sensing based multi-user collaborative detection for wideband cognitive radio networks [J]. 吉林大学学报(工学版), 2014, 44(4): 1165-1170.
[12] ZHAO Xiao-hui, YANG Wei-wei, JIN Xiao-guang. Selective subcarrier relaying and power allocation algorithm for multi-relay-assisted OFDM systems [J]. 吉林大学学报(工学版), 2014, 44(2): 478-484.
[13] LI Mei-ling, YUAN Chao-wei, ZHAO Wei, HAN Xi. Target based cooperative spectrum sensing scheme with best relay [J]. 吉林大学学报(工学版), 2013, 43(04): 1098-1103.
[14] LI Ju-peng, TAN Zhen-hui, TAO Cheng, XU Shao-yi. Dynamic spectrum access strategy based on multi-features model clustering [J]. , 2012, 42(04): 1021-1026.
[15] SHI Yu-chen, BAI Bao-ming. Inference cancellation based on superposition modulation and adaptive power allocation [J]. 吉林大学学报(工学版), 2012, 42(01): 213-217.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!