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

被引:5
|
作者
Zhang, Junlin [1 ]
Liu, Mingqian [1 ]
Zhao, Nan [2 ]
Chen, Yunfei [3 ]
Yang, Qinghai [1 ]
Ding, Zhiguo [4 ]
机构
[1] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Shaanxi, Peoples R China
[2] Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116024, Peoples R China
[3] Univ Durham, Dept Engn, Durham DH1 3LE, England
[4] Univ Manchester, Sch Elect & Elect Engn, Manchester, England
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Green communication; Multi-antenna spectrum sensing; Non-Gaussian noise; Unmanned aerial vehicle communication; COGNITIVE RADIOS;
D O I
10.1016/j.dcan.2022.09.017
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Unmanned Aerial Vehicle (UAV) communication is a promising technology that provides swift and flexible ondemand 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.
引用
收藏
页码:846 / 855
页数:10
相关论文
共 50 条
  • [21] Multi-antenna assisted spectrum sensing in spatially correlated noise environments
    Koochakzadeh, Ali
    Malek-Mohammadi, Mohammadreza
    Babaie-Zadeh, Massoud
    Skoglund, Mikael
    SIGNAL PROCESSING, 2015, 108 : 69 - 76
  • [22] Multi-antenna spectrum sensing by exploiting spatio-temporal correlation
    Sadiq Ali
    David Ramírez
    Magnus Jansson
    Gonzalo Seco-Granados
    José A López-Salcedo
    EURASIP Journal on Advances in Signal Processing, 2014
  • [23] Cyclostationarity Based Multi-Antenna Spectrum Sensing in Cognitive Radio Networks
    Zhong, Guohui
    Guo, Jiaming
    Zhao, Zhen
    Qu, Daiming
    2010 IEEE 71ST VEHICULAR TECHNOLOGY CONFERENCE, 2010,
  • [24] Multi-antenna spectrum sensing by exploiting spatio-temporal correlation
    Ali, Sadiq
    Ramirez, David
    Jansson, Magnus
    Seco-Granados, Gonzalo
    Lopez-Salcedo, Jose A.
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2014,
  • [25] Improving Spectrum Sensing and Reporting via Multi-Antenna in Cognitive Radio Networks
    Khan, Muhammad Sajjad
    Kim, Mi Ji
    Kim, Junsu
    Lee, Eung Hyuk
    Kim, Su Min
    2019 ELEVENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN 2019), 2019, : 321 - 325
  • [26] GLRT based Bartlett Detection for Spectrum Sensing in Multi-Antenna Cognitive Radio
    Dwivedi, Saumya
    Kota, Anusha
    Jagannatham, Aditya K.
    2016 INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS (SPCOM), 2016,
  • [27] A Novel Multi-Antenna Iterative Spectrum Sensing Algorithm Based on the SUMPLE Scheme
    Tong, Xin
    Hu, Yunpeng
    Shen, Zhixiang
    Shen, Caiyao
    Li, Yang
    2016 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB), 2016,
  • [28] Multi-antenna intelligent spectrum sensing in the presence of non-Gaussian interference
    Liu, Mingqian
    Zhang, Xiaobo
    Chen, Yunfei
    Tan, Hui
    DIGITAL SIGNAL PROCESSING, 2023, 140
  • [29] A Simple F-Test Based Multi-Antenna Spectrum Sensing Technique
    Getu, Tilahun M.
    Ajib, Wessam
    Landry, Rene, Jr.
    2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2018,
  • [30] Multi-Antenna Blind Spectrum Sensing for Cognitive Radios Using Path Correlations
    Soosahabi, Reza
    Orooji, Mahdi
    Naraghi-Pour, Mort
    2011 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE (GLOBECOM 2011), 2011,