The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Makalah ini membentangkan teknik pengiraan statistik baru untuk penderiaan spektrum berasaskan pengesanan tenaga dengan berbilang antena. Teknik yang dibentangkan mengira statistik untuk pengesanan isyarat selepas menggabungkan semua isyarat. Oleh kerana pengiraan statistik untuk semua isyarat yang diterima tidak diperlukan, teknik yang dibentangkan mengurangkan kerumitan pengiraan. Tambahan pula, nilai mutlak semua isyarat yang diterima digabungkan untuk mengelakkan pengecilan isyarat gabungan. Oleh kerana pengiraan statistik tidak diperlukan untuk semua isyarat yang diterima, pengurangan kerumitan pengiraan untuk pengesanan isyarat boleh dijangkakan. Tambahan pula, teknik yang dibentangkan tidak perlu memilih apa-apa, seperti pemutar fasa binari dalam teknik konvensional, dan oleh itu, kemerosotan prestasi akibat pilihan yang salah dapat dielakkan. Contoh berangka menunjukkan bahawa prestasi penderiaan spektrum teknik yang dibentangkan adalah hampir sama dengan teknik konvensional walaupun kerumitan teknik yang dibentangkan adalah kurang daripada teknik konvensional.
Shusuke NARIEDA
Mie University
Hiroshi NARUSE
Mie University
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Salinan
Shusuke NARIEDA, Hiroshi NARUSE, "Low Complexity Statistic Computation for Energy Detection Based Spectrum Sensing with Multiple Antennas" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 8, pp. 969-977, August 2020, doi: 10.1587/transfun.2019EAP1115.
Abstract: This paper presents a novel statistic computation technique for energy detection-based spectrum sensing with multiple antennas. The presented technique computes the statistic for signal detection after combining all the signals. Because the computation of the statistic for all the received signals is not required, the presented technique reduces the computational complexity. Furthermore, the absolute value of all the received signals are combined to prevent the attenuation of the combined signals. Because the statistic computations are not required for all the received signals, the reduction of the computational complexity for signal detection can be expected. Furthermore, the presented technique does not need to choose anything, such as the binary phase rotator in the conventional technique, and therefore, the performance degradation due to wrong choices can be avoided. Numerical examples indicate that the spectrum sensing performances of the presented technique are almost the same as those of conventional techniques despite the complexity of the presented technique being less than that of the conventional techniques.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019EAP1115/_p
Salinan
@ARTICLE{e103-a_8_969,
author={Shusuke NARIEDA, Hiroshi NARUSE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Low Complexity Statistic Computation for Energy Detection Based Spectrum Sensing with Multiple Antennas},
year={2020},
volume={E103-A},
number={8},
pages={969-977},
abstract={This paper presents a novel statistic computation technique for energy detection-based spectrum sensing with multiple antennas. The presented technique computes the statistic for signal detection after combining all the signals. Because the computation of the statistic for all the received signals is not required, the presented technique reduces the computational complexity. Furthermore, the absolute value of all the received signals are combined to prevent the attenuation of the combined signals. Because the statistic computations are not required for all the received signals, the reduction of the computational complexity for signal detection can be expected. Furthermore, the presented technique does not need to choose anything, such as the binary phase rotator in the conventional technique, and therefore, the performance degradation due to wrong choices can be avoided. Numerical examples indicate that the spectrum sensing performances of the presented technique are almost the same as those of conventional techniques despite the complexity of the presented technique being less than that of the conventional techniques.},
keywords={},
doi={10.1587/transfun.2019EAP1115},
ISSN={1745-1337},
month={August},}
Salinan
TY - JOUR
TI - Low Complexity Statistic Computation for Energy Detection Based Spectrum Sensing with Multiple Antennas
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 969
EP - 977
AU - Shusuke NARIEDA
AU - Hiroshi NARUSE
PY - 2020
DO - 10.1587/transfun.2019EAP1115
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2020
AB - This paper presents a novel statistic computation technique for energy detection-based spectrum sensing with multiple antennas. The presented technique computes the statistic for signal detection after combining all the signals. Because the computation of the statistic for all the received signals is not required, the presented technique reduces the computational complexity. Furthermore, the absolute value of all the received signals are combined to prevent the attenuation of the combined signals. Because the statistic computations are not required for all the received signals, the reduction of the computational complexity for signal detection can be expected. Furthermore, the presented technique does not need to choose anything, such as the binary phase rotator in the conventional technique, and therefore, the performance degradation due to wrong choices can be avoided. Numerical examples indicate that the spectrum sensing performances of the presented technique are almost the same as those of conventional techniques despite the complexity of the presented technique being less than that of the conventional techniques.
ER -