Blind Numerology Identification for Mixed Numerologies
Ahmad M. Jaradat, Ebubekir Memisoglu, and Huseyin Arslan

TL;DR
This paper presents a blind method for identifying mixed numerologies in 5G NR systems, using autocorrelation and spectral variance analysis to improve system efficiency without prior knowledge of numerology types.
Contribution
It introduces a novel blind identification technique combining autocorrelation and spectral variance analysis for mixed numerologies in 5G NR.
Findings
High identification accuracy under AWGN and frequency-selective channels
Robust performance with satisfactory BER compared to non-blind methods
Effective in diverse channel conditions
Abstract
5G New Radio (NR) introduces new flexibility that different numerologies can be selected to meet the requirements of a wide variety of services. For this new structure, blind numerology identification can increase system efficiency. Therefore, we propose a blind identification method for mixed numerologies. An autocorrelation method is applied in the time domain by correlating the cyclic prefix (CP) signal of the candidate numerology in the received composite signal for numerology type identification. Then, the location of each numerology in the frequency domain is identified by the variance difference in the power spectral density (PSD) of the subbands, on which different numerologies are occupied. The simulation results are obtained under additive white Gaussian noise (AWGN) and frequencyselective channels. The obtained results show that the proposed method has a robust identification…
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