Efficient Cross-Correlation Algorithm for Correction of Common Phase Error Employing Preamble for Orthogonal Frequency Division Multiplexing (OFDM) Receivers
Autor: | Lingfei Zhang, Kashif Habib, Chen Liu, Ziqin Wu, Yiming Wang, Jun Ma |
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Rok vydání: | 2021 |
Předmět: |
Mean squared error
Orthogonal frequency-division multiplexing Computer science business.industry 020206 networking & telecommunications Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology Noise (electronics) Computer Science Applications symbols.namesake Additive white Gaussian noise Frequency domain 0202 electrical engineering electronic engineering information engineering Bit error rate symbols Wireless 020201 artificial intelligence & image processing Electrical and Electronic Engineering business Algorithm Communication channel |
Zdroj: | Wireless Personal Communications. 118:535-549 |
ISSN: | 1572-834X 0929-6212 |
DOI: | 10.1007/s11277-020-08030-6 |
Popis: | In this paper, we propose a cross-correlation algorithm for correction of common phase error (CPE) in orthogonal frequency division multiplexing (OFDM) systems with high implementation efficiency. CPE resulting from the impairment of orthogonality among subcarriers is due to phase noise. It leads to the offset of demodulated data and increases the bit error rate (BER) of the receivers. As a result, it significantly degrades the performance of wireless communication systems that use OFDM. Therefore, offset compensation algorithm must be adopted in the OFDM system. The phase offset is traditionally estimated and compensated by introducing pilots in each OFDM symbol. However, the BER performance of the traditional algorithm PCP is poor because it is limited by the quantity of the pilot constraints of the wireless communication standard. A novel CPE correction algorithm involved in time and frequency domain can be developed to solve this problem. The proposed algorithm takes advantage of preamble sequences to remove the limitation of the pilots and improve the BER performance. Numerical analyses show that the proposed algorithm presents better estimation performance in additive white Gaussian noise (AWGN) channel. And the mean square error (MSE) is reduced to 10−3, which is lower than that of the traditional algorithm (10−2) at 10 dB signal-to-noise ratio (SNR). The BER is approximately down to10−5 at 12 dB SNR. The proposed algorithm can be easily implemented with low complexity of hardware for practical applications. |
Databáze: | OpenAIRE |
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