Joint estimation and compensation of transceiver IQ imbalance for PDM CO-OFDM system

Ma, Xu; Yang, Meng; Shan, Yunlong; Li, Jingjing

doi:10.1007/s11801-021-0049-y

Cited by 1 publication

(2 citation statements)

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“…𝑣 𝑠 (10) Due to data symbols, 𝑣 𝑠 contains the residual noise plus the term. By employing SVR algorithms, a regularised cost function of the channel is minimised.…”

Section: Support Vector Regression Modelmentioning

confidence: 99%

“…Channel estimation (CE) is basic for an OFDM-based wireless communication receiver [7], [8]. Using wireless channel's frequency or time correlation features, blind methods or those based on adaptive or non-adaptive methods, training pilots, channel estimation can be performed in different ways: with or without the use of a parametric model [9]- [10]. Pilot-aided phase noise is a method of correction that takes into account continuing professional education (CPE) by using OFDM subcarriers as pilots [11], [12].…”

Section: Introductionmentioning

confidence: 99%

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Estimation of channel distortion in orthogonal frequency division multiplexing system using pilot technique

Joseph

Gowda

2022

IJEECS

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Orthogonal frequency-division multiplexing (OFDM) is resistant to frequency selective fading due to the longer symbol duration. However, mobile applications channel timing fluctuations in one OFDM signal cause intercarrier-interference (ICI), which reduces performance. This research presented the support vector regression (SVR) model-based channel estimation technique for coherent optical communication systems. Due to the coherent optical orthogonal frequency-division-multiplexed (COOFDM) system, a channel model is developed that includes linear fibre dispersion effects, noise from optical amplifiers, and inter-carrier interference generated by laser phase noise. As a result, for such a system, an accurate channel estimate is essential. Based on this concept, derivation of channel estimation and phase estimation for the system of CO-OFDM. The proposed method is tested and evaluated using MATLAB software. Computer simulation results for several standard methods such as extreme learning machines (ELM) and artificial neural networks (ANN) validate the feasibility of the suggested methodology. The CO-OFDM system’s transmission experiments and computer simulations prove that the support vector machine-based model following pilot-assisted phase estimation gives the optimal performance. Therefore, results depicted that the channel estimation utilizing the SVR model gives good performance than the other methods, thus the proposed model gives an accurate CE process, respectively.

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“…𝑣 𝑠 (10) Due to data symbols, 𝑣 𝑠 contains the residual noise plus the term. By employing SVR algorithms, a regularised cost function of the channel is minimised.…”

Section: Support Vector Regression Modelmentioning

confidence: 99%