Performance Analysis of Arbitrary Correlated Multiantenna Receiver for Mobile Cognitive User

Dhaval K. Patel, Brijesh Soni, Yong Liang Guan, Sumei Sun, Yoong Choon Chang, Joanne Mun Yee Lim

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

In limited space scenarios, the antennas in the multi-antenna cognitive radio (CR) system are closely spaced and often experience correlation among them. In this paper, the sensing performance of arbitrary correlated antennas over Nakagami-m fading channel for the mobile CR user is analysed. In particular, the analytical expression for the average detection probability for a mobile CR user employing the selection combining with triple arbitrary correlated diversity branches is derived as a special case. Furthermore, to characterize the performance of energy detector under mobility, the area under the curve of receiver operating characteristic is analysed. The derived expressions converge quickly due to the monotonically decreasing hypergeometric function of two variables. The Monte Carlo simulations substantiate the analytical expressions. Results indicate that antenna correlation deteriorates detection performance. Moreover, the high speed of CR users further decreases the detection performance, especially in the deep fading channel scenarios. This work provides a realistic sensing framework for the CR enabled vehicles.

Original languageEnglish
Article number9322312
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event2020 IEEE Global Communications Conference, GLOBECOM 2020 - Virtual, Taipei, Taiwan, Province of China
Duration: Dec 7 2020Dec 11 2020

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

ASJC Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing

Keywords

  • arbitrary correlation
  • mobility
  • Nakagami-m fading channel
  • selection combining
  • Spectrum sensing

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