Performance Optimization for Decode and Forward Cooperative Cognitive Radio Networks

被引:0
作者
Qin D. [1 ]
Wu W. [1 ]
Zhou T. [2 ]
机构
[1] The School of Information Engineering, Nanchang University, Nanchang
[2] The School of Information Engineering, East China Jiaotong University, Nanchang
关键词
Budget control - Cognitive radio;
D O I
10.1155/2023/8828761
中图分类号
TN8 [无线电设备、电信设备];
学科分类号
0810 ; 081001 ;
摘要
This paper considers the problem of optimizing the data rate of the cooperative cognitive system subject to the dual constraints of the interference threshold of primary users and power budget of secondary users. In particular, under a single constraint, the rate can reach its peak easily. But under the double restrictions, the peak rate problem becomes complicated and changeable. According to different interference conditions and power supplies, four scenarios are formulated: total interference threshold and total power budget, total interference threshold and separate power budget, separate interference threshold and total power budget, and separate interference threshold and separate power budget. Each scenario needs to be further divided into many situations for discussion due to the sheer particularity. Through careful comparison and classification, we summarize and formulate each situation one by one to achieve the optimal value of the rate. Extensive simulation results demonstrate that the proposed resource allocation policy represents the best compromise between enhancing the rate of the secondary users and satisfying the interference threshold requirements of the primary users. © 2023 Dong Qin et al.
引用
收藏
相关论文
共 20 条
[1]  
Soleimanpour-Moghadam M., Askarizadeh M., Talebi S., Esmaeili S., Low complexity green cooperative cognitive radio network with superior performance, IEEE Systems Journal, 13, 1, pp. 345-356, (2019)
[2]  
Xu C., Xia C., Song C., Zeng P., Yu H., Multi-hop cognitive wireless powered networks: Outage analysis and optimization, IEEE Access, 7, pp. 4338-4347, (2019)
[3]  
Yan Z., Chen S., Zhang X., Liu H.L., Outage performance analysis of wireless energy harvesting relay-assisted random underlay cognitive networks, IEEE Internet of Things Journal, 5, 4, pp. 2691-2699, (2018)
[4]  
Diamantoulakis P.D., Pappi K.N., Muhaidat S., Karagiannidis G.K., Khattab T., Carrier aggregation for cooperative cognitive radio networks, IEEE Transactions on Vehicular Technology, 66, 7, pp. 5904-5918, (2017)
[5]  
Ho-Van K., Outage analysis of opportunistic relay selection in underlay cooperative cognitive networks under general operation conditions, IEEE Transactions on Vehicular Technology, 65, 10, pp. 8145-8154, (2016)
[6]  
Chi X., Zheng M., Liang W., Haibin Y., Liang Y.-C., Outage performance of underlay multi-hop cognitive relay networks with energy harvesting, IEEE Communications Letters, 20, 6, pp. 1148-1151, (2016)
[7]  
Wang Z., Chen Z., Xia B., Luo L., Zhou J., Cognitive relay networks with energy harvesting and information transfer: Design, analysis, and optimization, IEEE Transactions on Wireless Communications, 15, 4, pp. 2562-2576, (2016)
[8]  
Park J., Jang C., Lee J.H., Outage analysis of underlay cognitive radio networks with multihop primary transmission, IEEE Communications Letters, 20, 4, pp. 800-803, (2016)
[9]  
Jaafar W., Ohtsuki T., Ajib W., Haccoun D., Impact of the CSI on the performance of cognitive relay networks with partial relay selection, IEEE Transactions on Vehicular Technology, 65, 2, pp. 673-684, (2016)
[10]  
Alsharoa A., Ghazzai H., Yaacoub E., Alouini M.-S., Kamal A.E., Joint bandwidth and power allocation for MIMO two-way relays-assisted overlay cognitive radio systems, IEEE Transactions on Cognitive Communications and Networking, 1, 4, pp. 383-393, (2015)