Robust spectrum sensing against malicious users using particle swarm optimization

ICT Express - Tập 9 - Trang 106-111 - 2023
Noor Gul1, Saeed Ahmed2, Su Min Kim3, Junsu Kim3
1Department of Electronics, University of Peshawar, Peshawar, Pakistan
2Department of Electrical Engineering, Mirpur University of Science and Technology, AJK, Pakistan
3Department of Electronics Engineering, Korea Polytechnic University, Gyeonggi-do, Republic of Korea

Tài liệu tham khảo

Agarwal, 2015, The 5th generation mobile wireless networks- key concepts, network architecture and challenges, Am. J. Electr. Electron. Eng., 3, 22 Duong, 2019, Editorial: Wireless communications and networks for 5G and beyond, Mob. Netw. Appl., 24, 443, 10.1007/s11036-019-01232-8 Ejaz, 2016, Internet of Things (IoT) in 5G wireless communications, IEEE Access, 4, 10310, 10.1109/ACCESS.2016.2646120 Ashton, 2009 R. Khan, S.U. Khan, R. Zaheer, S. Khan, Future internet: The internet of things architecture, possible applications and key challenges, in: Proc. - 10th Int. Conf. Front. Inf. Technol. FIT 2012, 2012, pp. 257–260. Wu, 2014, Cognitive internet of things: A new paradigm beyond connection, IEEE Internet Things J., 1, 129, 10.1109/JIOT.2014.2311513 Ghasemi, 2008, Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs, Commun. Mag. IEEE, 46, 32, 10.1109/MCOM.2008.4481338 Abdul Salam, 2019, Adaptive threshold and optimal frame duration for multi-taper spectrum sensing in cognitive radio, ICT Express, 5, 31, 10.1016/j.icte.2018.02.002 Haykin, 2005, Cognitive radio: Brain-empowered wireless communications, IEEE J. Sel. Areas Commun., 23, 201, 10.1109/JSAC.2004.839380 Axell, 2012, Spectrum sensing for cognitive radio: State-of-the-art and recent advances, IEEE Signal Process. Mag., 29, 101, 10.1109/MSP.2012.2183771 He, 2018, On the performance of cooperative spectrum sensing in random cognitive radio networks, IEEE Syst. J., 12, 881, 10.1109/JSYST.2016.2554464 Lee, 2020, Order statistics and recursive updating with aging factor for cooperative cognitive radio networks under SSDF attacks, ICT Express, 6, 3, 10.1016/j.icte.2019.04.003 Gul, 2021, Differential evolution based machine learning scheme for secure cooperative spectrum sensing system, Electron., 10, 1, 10.3390/electronics10141687 Gul, 2020, Boosted trees algorithm as reliable spectrum sensing scheme in the presence of malicious users, Electron., 9, 1, 10.3390/electronics9061038 Toma, 2020, AI-based abnormality detection at the PHY-layer of cognitive radio by learning generative models, IEEE Trans. Cogn. Commun. Netw., 6, 21, 10.1109/TCCN.2020.2970693 Marchang, 2015, Dynamic decision rule for cooperative spectrum, 1 S. Bhattacharjee, Optimization of probability of false alarm and probability of detection in cognitive radio networks using GA, in: Proc. ReTIS’15-2nd IEEE Int. Conf. Recent Trends Inf. Syst., Kolkata, 2015, pp. 53–57. N. Gul, A. Naveed, A. Elahi, T. Khattak, I. Qureshi, A combination of double sided neighbor distance and genetic algorithm in cooperative spectrum sensing against malicious users, in: Proc. 2017 14th Int. Bhurban Conf. Appl. Sci. Technol., Islamabad, Pakistan, 2017, pp. 746–753.