Improved Cholesky Decomposition using Channel Element Relocation for MIMO Systems
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초록
This paper newly proposed a channel element relocation which can reduces multiplication complexity of ML by applying cholesky decomposition. In wireless communication, maximum likelihood(ML) detection scheme that shows the best bit error rate(BER) performance is usually used; however, a huge amount of multiplication complexity has been pointed out as a default. To lower multiplication complexity of ML detection scheme, various methods have been proposed. Among of them, QRM-MLD algorithm which uses QR decomposition was proposed. The QRM-MLD algorithm maintains the optimal BER performance of ML and reduces the huge amount of multiplication complexity of ML detection. But, QR decomposition shows a huge increase according to augmentation of a number of antennas because of amount of complexity of decomposition process of QR decomposition. For this reason, cholesky decomposition which has low complexity on decomposition process was proposed. Cholesky decomposition does not have high complexity on decomposition process but show reduced complexity than QR decomposition when a number of antennas increase. However, despite reduced complexity, there is a need of additional decrease of ML complexity. To satisfy the need, this paper proposes channel element relocation which applies to Cholesky decomposition and shows additional complexity reduction. Comparision with proposed method and QRM-MLD and conventional Cholesky decomposition shows that proposed method has low complexity.
Abstract
This paper newly proposed a channel element relocation which can reduces multiplication complexity of ML by applying cholesky decomposition. In wireless communication, maximum likelihood(ML) detection scheme that shows the best bit error rate(BER) performance is usually used; however, a huge amount of multiplication complexity has been pointed out as a default. To lower multiplication complexity of ML detection scheme, various methods have been proposed. Among of them, QRM-MLD algorithm which uses QR decomposition was proposed. The QRM-MLD algorithm maintains the optimal BER performance of ML and reduces the huge amount of multiplication complexity of ML detection. But, QR decomposition shows a huge increase according to augmentation of a number of antennas because of amount of complexity of decomposition process of QR decomposition. For this reason, cholesky decomposition which has low complexity on decomposition process was proposed. Cholesky decomposition does not have high complexity on decomposition process but show reduced complexity than QR decomposition when a number of antennas increase. However, despite reduced complexity, there is a need of additional decrease of ML complexity. To satisfy the need, this paper proposes channel element relocation which applies to Cholesky decomposition and shows additional complexity reduction. Comparision with proposed method and QRM-MLD and conventional Cholesky decomposition shows that proposed method has low complexity.
참고문헌 (10)
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