IEICE TRANSACTIONS on Fundamentals
Blind Detection Algorithm Based on Spectrum Sharing and Coexistence for Machine-to-Machine Communication
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E103-A No.1 pp.297-302
- Publication Date
- 2020/01/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2019EAP1076
- Type of Manuscript
- PAPER
- Category
- Analog Signal Processing
Authors
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
Keyword
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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},}
Copy
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 -
English
