Asymptotic Approximation of the Standard Condition Number Detector for Large Multi-Antenna Cognitive Radio Systems

Kobeissi, Hussein and Nasser, Youssef and Nafkha, Amor and Bazzi, Oussama and Louet, Yves (2017) Asymptotic Approximation of the Standard Condition Number Detector for Large Multi-Antenna Cognitive Radio Systems. EAI Endorsed Transactions on Cognitive Communications, 3 (11): e1. ISSN 2313-4534

[img]
Preview
Text
eai.31-5-2017.152554.pdf - Published Version
Available under License Creative Commons Attribution No Derivatives.

Download (746kB) | Preview

Abstract

Standard condition number (SCN) detector is a promising detector that can work eÿciently in uncertain environments. In this paper, we consider a Cognitive Radio (CR) system with large number of antennas (eg. Massive MIMO) and we provide an accurate and simple closed form approximation for the SCN distribution using the generalized extreme value (GEV) distribution. The approximation framework is based on the moment-matching method where the expressions of the moments are approximated using bi-variate Taylor expansion and results from random matrix theory. In addition, the performance probabilities and the decision threshold are considered. Since the number of antennas and/or the number of samples used in the sensing process may frequently change, this paper provides simple form decision threshold and performance probabilities o�ering dynamic and real-time computations. Simulation results show that the provided approximations are tightly matched to relative empirical ones.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 11 Sep 2020 09:04
Last Modified: 11 Sep 2020 09:04
URI: https://eprints.eudl.eu/id/eprint/230

Actions (login required)

View Item View Item