Optimization Analysis of Cooperative Spectrum Sensing System over Generalized $$\kappa -\mu $$
- PDF / 1,830,613 Bytes
- 20 Pages / 439.37 x 666.142 pts Page_size
- 24 Downloads / 139 Views
Optimization Analysis of Cooperative Spectrum Sensing System over Generalized − and − Fading Channels Suresh Kumar Balam1 · P. Siddaiah1 · Srinivas Nallagonda2 Accepted: 14 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract This paper presents, optimization analysis of energy detection based cooperative spectrum sensing system (CSSS) with hard-decision combining. Several system parameters are optimized to evaluate an optimal performance theoretically over noisy and generalized fading channels. In particular, wireless environments with noise plus 𝜅 − 𝜇 and 𝜂 − 𝜇 fading are considered in the sensing channels. More precisely, each secondary user (SU, also called as cognitive radio user) depend on an energy detector (ED). The SU collects the signal from the primary user (PU), is given as input to the ED, and the energy of the signal is calculated for making a binary decision locally. The locally obtained decisions are combined using hard-decision combining and a final decision about position of the PU is made. In this work, the novel mathematical expressions for detection probability of a single SU is derived first, subject to noise plus fading and validated by using Monte Carlo simulations. Next, we develop theoretical frame works for optimization analysis of CSSS using derived mathematical expressions. The channel error probability is considered in both sensing and reporting channels. Further, we derive closed-form optimal expressions of number of SUs and detection threshold subject to generalized fading and optimal values are calculated. Through receiver operating characteristics (ROC), complementary ROC and total error rate, system performance is evaluated for the significant influence of channel and network parameters. Finally, the influence of the generalized fading severity parameters, the signalto-noise ratio (SNR), the number of SUs, the detection threshold, and the channel error probability on the performance of CSSS is also investigated. Keywords Cognitive radio · Spectrum sensing · Generalized fading · Hard-decision combining · Total error rate · Optimization * Suresh Kumar Balam [email protected] P. Siddaiah [email protected] Srinivas Nallagonda [email protected] 1
Department of Electronics and Communication Engineering, University College of Engineering & Technology, Acharya Nagarjuna University, Guntur, A.P, India
2
Department of Electronics and Communication Engineering, Marri Laxman Reddy Institute of Technology and Management, Dundigal, Hyderabad, T.S, India
13
Vol.:(0123456789)
S. K. Balam et al.
1 Introduction Cognitive radio (CR) technology has advanced to growth the spectrum efficiency. It sidesteps the conflicts between unused frequency bands (i.e, spectrum holes) of licensed users, also called as primary users (PUs) and spectrum scarcity of unlicensed users, also called as CR users [1]. The CR technology is one of the most helpful technologies in the field of wireless communications. At present, using the inbu
Data Loading...
