Within the communication techniques, communication indicators often undergo a number of paths from the transmitter to the receiver, throughout which inter-symbol interference (ISI) is launched into the obtained indicators. Channel equalization is the primary approach to get rid of the ISI.
In concept, the utmost a posteriori (MAP) equalizer is perfect, however its complexity will increase exponentially with the channel size. Researchers often design the channel equalizer primarily based on the minimal mean-squared error (MMSE) criterion. Nevertheless, these equalizers have giant efficiency loss.
With a purpose to allow the low-complexity optimum equalization, researchers from the Institute of Acoustics (IOA) of the Chinese language Academy of Sciences and Southeast College proposed a Hadamard-Haar random precoding (HHRP) scheme, and obtained near-optimal performance with a linear complexity primarily based on the vector approximate message passing (VAMP) algorithm on the receiver facet.
They proposed an HHRP scheme that concatenates the Hadamard-Haar rework (HHT), random symbol-interleaver, and the quick Fourier rework.
The HHRP enabled a right-rotationally invariant (RRI) channel matrix, which was a essential situation for the VAMP to attain the Bayes optimum estimation. In the meantime, it introduced the time and frequency diversities, facilitating image detection. As well as, the self-iterative HHRP-VAMP equalizer incurred linear complexity because the HHT may very well be carried out by solely addition operations.
Simulation outcomes confirmed that below the extreme frequency-selectivity Proakis C channel, each the efficiency and the convergence of the HHRP-VAMP equalizer had been comparable with the optimum MAP equalizer and had been superior to different current VAMP equalizers.
Dong Li et al. Close to-Optimum Self-Iterative VAMP Equalization enabled by Hadamard-Haar Random Precoding, IEEE Communications Letters (2020). DOI: 10.1109/LCOMM.2020.2981073
Chinese Academy of Sciences
Hadamard-Haar random precoding to allow low-complexity optimum channel equalization (2020, May 12)
retrieved 12 May 2020
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