スーパーハイビジョン映像の素材伝送に向けたブロックQR分解を用いた演算量削減型MLD

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  • Complexity-reduced Maximum Likelihood Detection with Block QR Decomposition for Super Hi-Vision Television Wireless Transmission System

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We have been developing a portable digital transmission system for next generation television called “Super Hi-Vision (SHV)” with hundreds of Mbps-class transmission and high link reliability. To fulfill these requirements, we have been researching a multiple-input multiple-output (MIMO) multiplexing technology using a millimeter-wave (42/55-GHz) band allocated for broadcasting organizations. In this paper, we propose a low-complexity MIMO detection scheme that uses block QR decomposition with M-algorithm to reduce the computational complexity of the maximum likelihood detection (MLD) method. In the proposed algorithm, a MIMO channel is converted into a block upper triangular matrix multiplied by a unitary matrix and divided into some small block matrices. Then, the transmit signals are selected by Manhattan metrics to reduce the complexity, and squared Euclidean metrics of the selected signal candidates are calculated in these block matrices. Computer simulations with a correlated 4 x 4 MIMO channel demonstrate that the proposed scheme shows almost the same BER performance as that of the MLD and better BER performance than that of the conventional QRM-MLD (QR decomposition with M-algorithm MLD) with less complexity.

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