MGF-Based Analysis of Spectrum Sensing Over $K-\mu$ Fading Channels for 5G Cognitive Networks

With the development of wireless communication techniques, higher spectrum efficiency is being pursued for the fifth generation (5G) mobile communication. Cognitive radio (CR) has attracted much attention from industry and academia due to its ability to improve spectrum efficiency. In 5G CR networks, the most important function is spectrum sensing (SS). However, SS performance deteriorates seriously for single-antenna signal detection. To improve spectrum efficiency, multiple-antenna (MA) signal-detection techniques have been proposed to improve SS performance by taking advantage of MA diversity reception. In this paper, we propose an MGF-based method for performance analysis of SS over $k-\mu $ channels for 5G CR networks. The expressions of the average detection probabilities are derived in closed form for cases of SA signal detection and MA signal detection. For MA signal detection, we mainly consider maximal ratio combining (MRC) and square law combining (SLC) diversity reception scheme over the $k-\mu $ fading channel. The improvement in detection performance is quantified for the MRC and SLC schemes. The simulation results show that the MRC and SLC diversity reception ( $L>1$ ) schemes achieve significant sensing diversity gains compared with that in the SA case.