IEICE TRANSACTIONS on Communications
Fuzzy Inference System for Multiuser Detection in CDMA Systems
Yalc
n IIK, Necmi TAPINAR
Summary :
In this letter, multi user detection process in Code Division Multiple Access (CDMA) is performed by fuzzy inference system (FIS) and the bit error rate (BER) performance was compared with the single user bound, the matched filter receiver and neural network receiver. The BER performance of the matched filter receiver degrades as the number of the active users and the power level differences among the users increase. The neural network receiver needs the training process. Optimal receiver that has the best BER performance is too complex for practical application. The BER performance near the optimal case was obtained with the proposed receiver. The proposed receiver uses the FIS without training process and it has lower time complexity than the optimal receiver.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E89-B No.5 pp.1692-1695
- Publication Date
- 2006/05/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1093/ietcom/e89-b.5.1692
- Type of Manuscript
- LETTER
- Category
- Wireless Communication Technologies
Authors
n I
PINARKeyword
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Yalcn IIK, Necmi TAPINAR, "Fuzzy Inference System for Multiuser Detection in CDMA Systems" in IEICE TRANSACTIONS on Communications,
vol. E89-B, no. 5, pp. 1692-1695, May 2006, doi: 10.1093/ietcom/e89-b.5.1692.
Abstract: In this letter, multi user detection process in Code Division Multiple Access (CDMA) is performed by fuzzy inference system (FIS) and the bit error rate (BER) performance was compared with the single user bound, the matched filter receiver and neural network receiver. The BER performance of the matched filter receiver degrades as the number of the active users and the power level differences among the users increase. The neural network receiver needs the training process. Optimal receiver that has the best BER performance is too complex for practical application. The BER performance near the optimal case was obtained with the proposed receiver. The proposed receiver uses the FIS without training process and it has lower time complexity than the optimal receiver.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e89-b.5.1692/_p
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@ARTICLE{e89-b_5_1692,
author={Yalcn IIK, Necmi TAPINAR, },
journal={IEICE TRANSACTIONS on Communications},
title={Fuzzy Inference System for Multiuser Detection in CDMA Systems},
year={2006},
volume={E89-B},
number={5},
pages={1692-1695},
abstract={In this letter, multi user detection process in Code Division Multiple Access (CDMA) is performed by fuzzy inference system (FIS) and the bit error rate (BER) performance was compared with the single user bound, the matched filter receiver and neural network receiver. The BER performance of the matched filter receiver degrades as the number of the active users and the power level differences among the users increase. The neural network receiver needs the training process. Optimal receiver that has the best BER performance is too complex for practical application. The BER performance near the optimal case was obtained with the proposed receiver. The proposed receiver uses the FIS without training process and it has lower time complexity than the optimal receiver.},
keywords={},
doi={10.1093/ietcom/e89-b.5.1692},
ISSN={1745-1345},
month={May},}
Copy
TY - JOUR
TI - Fuzzy Inference System for Multiuser Detection in CDMA Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 1692
EP - 1695
AU - Yalcn IIK
AU - Necmi TAPINAR
PY - 2006
DO - 10.1093/ietcom/e89-b.5.1692
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E89-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2006
AB - In this letter, multi user detection process in Code Division Multiple Access (CDMA) is performed by fuzzy inference system (FIS) and the bit error rate (BER) performance was compared with the single user bound, the matched filter receiver and neural network receiver. The BER performance of the matched filter receiver degrades as the number of the active users and the power level differences among the users increase. The neural network receiver needs the training process. Optimal receiver that has the best BER performance is too complex for practical application. The BER performance near the optimal case was obtained with the proposed receiver. The proposed receiver uses the FIS without training process and it has lower time complexity than the optimal receiver.
ER -
English
