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Spectrum and energy efficient multi-antenna spectrum sensing for green UAV communication

Authors :
Junlin Zhang
Mingqian Liu
Nan Zhao
Yunfei Chen
Qinghai Yang
Zhiguo Ding
Source :
Digital Communications and Networks, Vol 9, Iss 4, Pp 846-855 (2023)
Publication Year :
2023
Publisher :
KeAi Communications Co., Ltd., 2023.

Abstract

Unmanned Aerial Vehicle (UAV) communication is a promising technology that provides swift and flexible on-demand wireless connectivity for devices without infrastructure support. With recent developments in UAVs, spectrum and energy efficient green UAV communication has become crucial. To deal with this issue, Spectrum Sharing Policy (SSP) is introduced to support green UAV communication. Spectrum sensing in SSP must be carefully formulated to control interference to the primary users and ground communications. In this paper, we propose spectrum sensing for opportunistic spectrum access in green UAV communication to improve the spectrum utilization efficiency. Different from most existing works, we focus on the problem of spectrum sensing of randomly arriving primary signals in the presence of non-Gaussian noise/interference. We propose a novel and improved p-norm-based spectrum sensing scheme to improve the spectrum utilization efficiency in green UAV communication. Firstly, we construct the p-norm decision statistic based on the assumption that the random arrivals of signals follow a Poisson process. Then, we analyze and derive the approximate analytical expressions of the false-alarm and detection probabilities by utilizing the central limit theorem. Simulation results illustrate the validity and superiority of the proposed scheme when the primary signals are corrupted by additive non-Gaussian noise and arrive randomly during spectrum sensing in the green UAV communication.

Details

Language :
English
ISSN :
23528648
Volume :
9
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Digital Communications and Networks
Publication Type :
Academic Journal
Accession number :
edsdoj.29e49b4636dc464c958800fd8023c911
Document Type :
article
Full Text :
https://doi.org/10.1016/j.dcan.2022.09.017