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A new precoding for linear dispersion codes to reduce the spatial correlation in transmitter

Qi Wang, Wen Chen

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Abstract

In this paper we study the data-error performance of Linear Dispersion (LD) codes under spatial correlated multiple-input multiple-output (MIMO) channels. We propose a new precoding algorithm for LD codes by minimizing the pairwise error probability (PEP). This precoding can totally remove the spatial correlation existing in the transmitter. Particularly, the precoding process can be integrated into the LD codes design process, which means that there is no extra computation required in the coding process.

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What this paper is about

In this paper we study the data-error performance of Linear Dispersion (LD) codes under spatial correlated multiple-input multiple-output (MIMO) channels. We propose a new precoding algorithm for LD codes by minimizing the pairwise error probability (PEP). This precoding can totally remove the spatial correlation existing in the transmitter. Particularly, the precoding process can be integrated into the LD codes design process, which means that there is no extra computation required in the coding process.

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Available abstract

In this paper we study the data-error performance of Linear Dispersion (LD) codes under spatial correlated multiple-input multiple-output (MIMO) channels. We propose a new precoding algorithm for LD codes by minimizing the pairwise error probability (PEP). This precoding can totally remove the spatial correlation existing in the transmitter. Particularly, the precoding process can be integrated into the LD codes design process, which means that there is no extra computation required in the coding process.

Key concepts: Precoding, Spatial correlation, Pairwise error probability, Zero-forcing precoding, Transmitter, Computer science, MIMO, Algorithm

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