FrFT-Domain Precoding for Line-of-Sight Extremely Large-Scale MIMO Systems

Precoding is a key technique in multiple-input multiple-output (MIMO) systems, with angular-domain precoding, which leverages the channel's sparsity in the angular domain, being the most widely used approach in prior studies. In contrast to these angular-domain methods, this paper pioneers the...

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Vydané v:IEEE International Conference on Communications (2003) s. 1748 - 1753
Hlavní autori: Xu, Peng-zheng, Yu, Qi-yue
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 08.06.2025
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ISSN:1938-1883
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Shrnutí:Precoding is a key technique in multiple-input multiple-output (MIMO) systems, with angular-domain precoding, which leverages the channel's sparsity in the angular domain, being the most widely used approach in prior studies. In contrast to these angular-domain methods, this paper pioneers the use of the fractional Fourier transform (FrFT) domain for analyzing line-of-sight (LoS) MIMO near-field channels and designs a corresponding precoding algorithm. Specifically, by decomposing the MIMO channel into a series of multiple-input single-output (MISO) channels and transforming them into the FrFT domain, we reveal the energy-concentration characteristics of the LoS MIMO near-field channel in this domain. Based on these findings, we propose a hybrid precoding algorithm called FrFT-domain energy concentrated precoding (FrFT-ECP), which first identifies the FrFT domain basis with the most concentrated channel energy distribution to form the analog precoding matrix, and then derives the corresponding digital precoding matrix by projecting the optimal fully digital precoder onto the span of these basis vectors. Simulation results demonstrate that the proposed FrFTECP method not only approximates the performance of fully digital precoding with fewer radio frequency (RF) chains but also achieves a higher rate when a sufficient number of RF chains are available compared to existing algorithms.
ISSN:1938-1883
DOI:10.1109/ICC52391.2025.11161023