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
CMA(Constant Modulus Algorithm)는 전송된 신호 파형이 일정한 포락선을 갖는다는 점 외에는 신호에 대한 지식이 필요하지 않기 때문에 블라인드 적응형 빔포밍으로 널리 알려진 방법입니다. CMA는 이러한 블라인드 연산의 장점을 가지고 있지만 수렴성에 문제가 있습니다. 본 논문에서는 CMA와 또 다른 주요 적응형 알고리즘 SMI(Sample Matrix Inversion)을 결합하여 이 알고리즘에 내재된 문제를 해결합니다. 아이디어는 SMI를 사용하여 CMA 작업의 초기 가중치를 결정하는 것입니다. CMA가 블라인드 알고리즘이라는 이점을 충분히 활용하지는 못하더라도 SMI와 CMA의 장점을 모두 도입할 수 있습니다. 이 접근 방식을 사용하면 CMA의 수렴 속성에 관한 두 가지 주요 문제를 해결할 수 있습니다. 이러한 문제 중 하나는 신뢰성이며 이는 특정 경우의 수렴 성능과 관련이 있습니다. 간섭 신호가 원하는 신호보다 강하면 알고리즘은 더 강한 전력을 갖는 간섭 신호를 캡처하여 잘못된 솔루션을 찾는 경향이 있습니다. 또한 이 알고리즘의 수렴 시간이 느리기 때문에 동적 환경에서의 적용이 제한됩니다. 그러나 CMA의 느린 수렴 시간은 이전에 연구되었으며 이 결함을 극복하기 위한 여러 가지 방법이 제안되었습니다. 제안된 방법을 사용하면 이 두 가지 문제로 인한 열화를 완화할 수 있다. 이론을 확인하기 위해 시뮬레이션 결과가 표시됩니다. 또한, 페이딩 특성에 관한 평가도 행해진다. 개인 이동통신에서도 이 방법의 추적 성능은 충분하다고 시뮬레이션을 통해 확인하였다.
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부
Rumiko YONEZAWA, Isamu CHIBA, "A Combination of Two Adaptive Algorithms SMI and CMA" in IEICE TRANSACTIONS on Communications,
vol. E84-B, no. 7, pp. 1768-1773, July 2001, doi: .
Abstract: Constant Modulus Algorithm (CMA) is a method that has been widely known as blind adaptive beamforming because it requires no knowledge about the signal except that the transmitted signal waveform has a constant envelope. Although CMA has the merit of this blind operation, it possesses problems in its convergence property. In this paper, problems that are inherent to this algorithm is resolved using a combination of CMA and another major adaptive algorithm SMI (Sample Matrix Inversion). The idea is to use SMI to determine the initial weights for CMA operation. Although the benefit of CMA being a blind algorithm is not fully taken advantage of, good aspects of both SMI and CMA can be introduced. By using this approach, two major problems in convergence properties of CMA can be solved. One of these problems is the reliability and this relates to the convergence performance in certain cases. When the interfering signal is stronger than the desired signal, the algorithm tends to come up with the wrong solution by capturing the interfering signal which has the stronger power. Also, the convergence time of this algorithm is slow, limiting its application in dynamic environment, although the slow convergence time of CMA has been studied previously and several methods have been proposed to overcome this defect. Using the proposed method, the deterioration due to both of these problems can be mitigated. Simulation results are shown to confirm the theory. Furthermore, evaluations are done concerning the fading characteristics. It is also confirmed from the simulation that the tracking performance of this method can be regarded as sufficient in personal mobile communication.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e84-b_7_1768/_p
부
@ARTICLE{e84-b_7_1768,
author={Rumiko YONEZAWA, Isamu CHIBA, },
journal={IEICE TRANSACTIONS on Communications},
title={A Combination of Two Adaptive Algorithms SMI and CMA},
year={2001},
volume={E84-B},
number={7},
pages={1768-1773},
abstract={Constant Modulus Algorithm (CMA) is a method that has been widely known as blind adaptive beamforming because it requires no knowledge about the signal except that the transmitted signal waveform has a constant envelope. Although CMA has the merit of this blind operation, it possesses problems in its convergence property. In this paper, problems that are inherent to this algorithm is resolved using a combination of CMA and another major adaptive algorithm SMI (Sample Matrix Inversion). The idea is to use SMI to determine the initial weights for CMA operation. Although the benefit of CMA being a blind algorithm is not fully taken advantage of, good aspects of both SMI and CMA can be introduced. By using this approach, two major problems in convergence properties of CMA can be solved. One of these problems is the reliability and this relates to the convergence performance in certain cases. When the interfering signal is stronger than the desired signal, the algorithm tends to come up with the wrong solution by capturing the interfering signal which has the stronger power. Also, the convergence time of this algorithm is slow, limiting its application in dynamic environment, although the slow convergence time of CMA has been studied previously and several methods have been proposed to overcome this defect. Using the proposed method, the deterioration due to both of these problems can be mitigated. Simulation results are shown to confirm the theory. Furthermore, evaluations are done concerning the fading characteristics. It is also confirmed from the simulation that the tracking performance of this method can be regarded as sufficient in personal mobile communication.},
keywords={},
doi={},
ISSN={},
month={July},}
부
TY - JOUR
TI - A Combination of Two Adaptive Algorithms SMI and CMA
T2 - IEICE TRANSACTIONS on Communications
SP - 1768
EP - 1773
AU - Rumiko YONEZAWA
AU - Isamu CHIBA
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E84-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2001
AB - Constant Modulus Algorithm (CMA) is a method that has been widely known as blind adaptive beamforming because it requires no knowledge about the signal except that the transmitted signal waveform has a constant envelope. Although CMA has the merit of this blind operation, it possesses problems in its convergence property. In this paper, problems that are inherent to this algorithm is resolved using a combination of CMA and another major adaptive algorithm SMI (Sample Matrix Inversion). The idea is to use SMI to determine the initial weights for CMA operation. Although the benefit of CMA being a blind algorithm is not fully taken advantage of, good aspects of both SMI and CMA can be introduced. By using this approach, two major problems in convergence properties of CMA can be solved. One of these problems is the reliability and this relates to the convergence performance in certain cases. When the interfering signal is stronger than the desired signal, the algorithm tends to come up with the wrong solution by capturing the interfering signal which has the stronger power. Also, the convergence time of this algorithm is slow, limiting its application in dynamic environment, although the slow convergence time of CMA has been studied previously and several methods have been proposed to overcome this defect. Using the proposed method, the deterioration due to both of these problems can be mitigated. Simulation results are shown to confirm the theory. Furthermore, evaluations are done concerning the fading characteristics. It is also confirmed from the simulation that the tracking performance of this method can be regarded as sufficient in personal mobile communication.
ER -