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".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Neste artigo, propomos um novo esquema que utiliza algoritmo de detecção cega para recuperar o sinal do usuário convencional em um sistema onde a comunicação esporádica máquina-máquina (M2M) compartilha o mesmo espectro com o usuário convencional. Técnicas de detecção compressiva são usadas para estimar os sinais dos dispositivos M2M. Baseado na rede neural Hopfield (HNN), o algoritmo de detecção cega é usado para recuperar o sinal convencional do usuário. Os resultados da simulação mostram que o sinal convencional do usuário pode ser efetivamente restaurado em um canal desconhecido. Comparado com os métodos existentes, como usar a sequência de treinamento para estimar o canal antecipadamente, o algoritmo de detecção cega usado neste artigo não precisa identificar o canal e pode detectar diretamente o sinal transmitido às cegas.
Yun ZHANG
Nanjing University of Posts and Telecommunications
Bingrui LI
Nanjing University of Posts and Telecommunications
Shujuan YU
Nanjing University of Posts and Telecommunications
Meisheng ZHAO
Nanjing University of Posts and Telecommunications
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Yun ZHANG, Bingrui LI, Shujuan YU, Meisheng ZHAO, "Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 1, pp. 297-302, January 2020, doi: 10.1587/transfun.2019EAP1076.
Abstract: In this paper, we propose a new scheme which uses blind detection algorithm for recovering the conventional user signal in a system which the sporadic machine-to-machine (M2M) communication share the same spectrum with the conventional user. Compressive sensing techniques are used to estimate the M2M devices signals. Based on the Hopfield neural network (HNN), the blind detection algorithm is used to recover the conventional user signal. The simulation results show that the conventional user signal can be effectively restored under an unknown channel. Compared with the existing methods, such as using the training sequence to estimate the channel in advance, the blind detection algorithm used in this paper with no need for identifying the channel, and can directly detect the transmitted signal blindly.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019EAP1076/_p
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@ARTICLE{e103-a_1_297,
author={Yun ZHANG, Bingrui LI, Shujuan YU, Meisheng ZHAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication},
year={2020},
volume={E103-A},
number={1},
pages={297-302},
abstract={In this paper, we propose a new scheme which uses blind detection algorithm for recovering the conventional user signal in a system which the sporadic machine-to-machine (M2M) communication share the same spectrum with the conventional user. Compressive sensing techniques are used to estimate the M2M devices signals. Based on the Hopfield neural network (HNN), the blind detection algorithm is used to recover the conventional user signal. The simulation results show that the conventional user signal can be effectively restored under an unknown channel. Compared with the existing methods, such as using the training sequence to estimate the channel in advance, the blind detection algorithm used in this paper with no need for identifying the channel, and can directly detect the transmitted signal blindly.},
keywords={},
doi={10.1587/transfun.2019EAP1076},
ISSN={1745-1337},
month={January},}
Copiar
TY - JOUR
TI - Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 297
EP - 302
AU - Yun ZHANG
AU - Bingrui LI
AU - Shujuan YU
AU - Meisheng ZHAO
PY - 2020
DO - 10.1587/transfun.2019EAP1076
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2020
AB - In this paper, we propose a new scheme which uses blind detection algorithm for recovering the conventional user signal in a system which the sporadic machine-to-machine (M2M) communication share the same spectrum with the conventional user. Compressive sensing techniques are used to estimate the M2M devices signals. Based on the Hopfield neural network (HNN), the blind detection algorithm is used to recover the conventional user signal. The simulation results show that the conventional user signal can be effectively restored under an unknown channel. Compared with the existing methods, such as using the training sequence to estimate the channel in advance, the blind detection algorithm used in this paper with no need for identifying the channel, and can directly detect the transmitted signal blindly.
ER -