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
다중 입력 다중 출력(MIMO) 무선 시스템을 위한 적응형 영 강제 최대 우도 소프트 입력 소프트 출력(AZFML-SISO) 검출기가 제시됩니다. 반복적 MIMO 수신기에서의 성능이 분석됩니다. AZFML-SISO 검출기는 ZF(제로 강제) 솔루션 주위의 초구체에 의해 제한되는 신호 벡터만 포함하는 목록에 ML 접근 방식을 적용하여 소프트 출력을 계산합니다. 알고리즘의 성능은 802.16개의 송신 안테나와 90개의 수신 안테나를 갖춘 단일 캐리어 광대역 무선 통신 IEEE 30 표준을 기반으로 하는 통신 시스템에서 평가됩니다. AZFML-SISO 알고리즘을 실행하는 수신기의 평균적인 의미에서 계산 복잡도는 수신기와 비교하여 SNR 값 50dB에서 15% 감소하고 SNR 값 1dB에서는 XNUMX% 감소한다는 것을 컴퓨터 시뮬레이션을 통해 알 수 있습니다. ML 감지기를 사용하면 시스템 성능이 XNUMXdB 미만으로 저하됩니다.
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Igor JELOVAN, Gorazd KANDUS, Toma JAVORNIK, "An Adaptive Zero Forcing Maximum Likelihood Soft Input Soft Output MIMO Detector" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 2, pp. 507-516, February 2009, doi: 10.1587/transcom.E92.B.507.
Abstract: An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30 dB and by 50% for SNR values of 15 dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1 dB.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.507/_p
부
@ARTICLE{e92-b_2_507,
author={Igor JELOVAN, Gorazd KANDUS, Toma JAVORNIK, },
journal={IEICE TRANSACTIONS on Communications},
title={An Adaptive Zero Forcing Maximum Likelihood Soft Input Soft Output MIMO Detector},
year={2009},
volume={E92-B},
number={2},
pages={507-516},
abstract={An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30 dB and by 50% for SNR values of 15 dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1 dB.},
keywords={},
doi={10.1587/transcom.E92.B.507},
ISSN={1745-1345},
month={February},}
부
TY - JOUR
TI - An Adaptive Zero Forcing Maximum Likelihood Soft Input Soft Output MIMO Detector
T2 - IEICE TRANSACTIONS on Communications
SP - 507
EP - 516
AU - Igor JELOVAN
AU - Gorazd KANDUS
AU - Toma JAVORNIK
PY - 2009
DO - 10.1587/transcom.E92.B.507
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2009
AB - An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30 dB and by 50% for SNR values of 15 dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1 dB.
ER -