Sustainable Non-Cooperative User Detection Techniques in 5G Communications for Smart City Users

Shayla Islam, Anil Kumar Budati (), Mohammad Kamrul Hasan, Hima Bindu Valiveti and Sridhar Reddy Vulupala
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Shayla Islam: Institute of Computer Science and Digital Innovation, UCSI University, Kuala Lumpur 56000, Malaysia
Anil Kumar Budati: Institute of Computer Science and Digital Innovation, UCSI University, Kuala Lumpur 56000, Malaysia
Mohammad Kamrul Hasan: Center for Cyber Security, UKM University, Bangi 43600, Malaysia
Hima Bindu Valiveti: Department of ECE, Gokaraju Rangaraju Institute of Engineering & Technology (GRIET), Hyderabad 500090, India
Sridhar Reddy Vulupala: Department of IT, Vignana Bharathi Institute of Technology, Hyderabad 501301, India

Sustainability, 2022, vol. 15, issue 1, 1-14

Abstract: The 4G network is not sufficient for achieving the high data requirements of smart city users. The 5G network intends to meet these requirements and overcome other application issues, such as fast data transmission, video buffering, and coverage issues, providing excellent mobile data services to smart city users. To allocate a channel or spectrum to a smart city user for error-free transmission with low latency, the accurate information of the spectrum should be detected. In this study, we determined the range of non-cooperative detection techniques, such as matched filter detection with inverse covariance approach (MFDI), cyclostationary feature detection with inverse covariance approach (CFDI), and hybrid filter detection with inverse covariance approach (HFDI); based on the results of these methods, we provided highly accurate spectrum information for smart city users, enabling sustainable development. To evaluate the performance of the proposed detection techniques, the following parameters are used: probability of detection (P D ), probability of false alarms (P fa ), probability of miss detection (P md ), sensing time, and throughput. The simulation results revealed that the HFDI detection method provided sustainable results at low signal-to-noise ratio ranges and improved channel detection and throughput of approximately 17% and 10%, respectively.

Keywords: smart city users; sustainable; 5G technology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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