Hybrid Spectrum Sensing Using MD and ED for Cognitive Radio Networks

Abstract

Day by day, the demand for wireless systems is increasing while the available spectrum resources are not sufficient. To fulfil the demand for wireless systems, the spectrum hole (spectrum vacant) should be found and utilised very effectively. Cognitive radio (CR) is a device which intelligently senses the spectrum through various spectrum-sensing detectors. Based on the complexity and licensed user’s information present with CR, the appropriate detector should be utilised for spectrum sensing. In this paper, a hybrid detector (HD) is proposed to determine the spectrum hole from the available spectrum resources. HD is designed based on an energy detector (ED) and matched detector (MD). Unlike a single detector such as ED or MD, HD can sense the signal more precisely. Here, HD can work on both conditions whether the primary user (PU) information is available or not. HD is analysed under heterogeneous environments with and without cooperative spectrum sensing (CSS). For CSS, four users were used to implement OR, AND, and majority schemes under low SNR walls. To design the HD, specifications were chosen based on the IEEE Wireless Regional Area Network (WRAN) 802.22 standard for accessing TV spectrum holes. For the HD model, we achieved the best results through OR rule. Under the low SNR circumstances at −20 dB SNR, the probability of detection (PD) is maximised to 1 and the probability of a false alarm (PFA) is reduced to 0 through the CSS environment.

Spectrum Sensing Based on Hybrid Spectrum Handoff in Cognitive Radio Networks

“…In 2022, Bani and Kulkarni [ 33 ] deployed a hybrid detector (HD) to identify spectrum holes using the available resources. An energy detector (ED) and matched detector (MD) served as the foundation for the HD architecture.…”

A Spectrum Sensing and Allocation Model for Primary User Detection and Interference Mitigation in Television Whitespaces

“…Spectrum sensing and allocation approaches stand as common methods employed to tackle the issue of interference within TVWS networks (Mwaimu et al, 2022;Bani and Kulkarni, 2022). Certainly, spectrum sensing involves scanning TV bands to identify available channels suitable for use by cognitive users, aiming to prevent interference between licensed and unlicensed users (Kantikar and Yelalwar, 2018;Koçkaya and Develi, 2020).…”

“…Certainly, spectrum sensing involves scanning TV bands to identify available channels suitable for use by cognitive users, aiming to prevent interference between licensed and unlicensed users (Kantikar and Yelalwar, 2018;Koçkaya and Develi, 2020). On the other hand, spectrum allocation approaches are employed to reduce the potential for interference among users in the secondary role, thus enhancing their network capacities within the network (Politis et al, 2018;Mwaimu et al, 2022;Bani and Kulkarni, 2022). Indeed, existing literature often segregates the use of these approaches, focusing on implementing spectrum sensing and spectrum allocation as separate methods rather than integrating them comprehensively (Ujam et al, 2018;Orumwense and Abo-Al-Ez, 2020;Politis et al, 2018;Mwaimu et al, 2022;Bani and Kulkarni, 2022;Kantikar and Yelalwar, 2018;Koçkaya and Develi, 2020;Brito et al, 2021;Agarwal et al, 2022;Liang et al, 2019).…”