Deep clipping noise mitigation using ISTA with the specified observations for LED‐based DCO‐OFDM system. Issue 20 (2nd November 2018)

• Record Type: Journal Article
• Authors: Miao, Pu; Qi, Chenhao; Fang, Lanting; Song, Kang; Bu, Qingkai
• Is Part Of: IET communications. Volume 12:Issue 20(2018)
• Page Start: 2582
• Page End: 2591
• Publication Date: 2018-11-02
• Subjects: OFDM modulation -- light emitting diodes -- iterative methods -- error statistics -- vectors -- interference suppression; direct current requirement -- light emitting diodes -- LEDs -- bit‐resolution requirement -- digital‐to‐analogue converters -- deep clipping noise mitigation scheme -- iterative shrinkage/thresholding algorithm -- ISTA -- bit error rate performance -- channel noise -- specified observations -- measurement noise -- observation vector -- peak‐to‐average power ratio -- DCO‐OFDM system -- observation interference -- optical orthogonal frequency division multiplexing system -- sparse recovery performance -- reconstruction quality -- nonlinearity mitigation -- generalised cross validation -- signal distortions; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2018.5222
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Deep clipping is beneficial for the optical orthogonal frequency division multiplexing (O‐OFDM) system, since it can lower the peak‐to‐average power ratio, reduce the direct current requirement in light emitting diodes (LEDs), and relax the bit‐resolution requirement in digital‐to‐analogue converters (DACs). However, it is accompanied by more signal distortions. In this study, a deep clipping noise mitigation scheme using iterative shrinkage/thresholding algorithm (ISTA) with three steps is proposed to improve bit error rate (BER) performance of the LED‐based DCO‐OFDM systems. In the first step, the estimated observation interference is eliminated from the received symbols to minimise the negative effect of channel noise. In the second step, two strategies are presented to generate the specified observations thus reduce the component of measurement noise in the whole observation vector. In the last step, combining the generalised cross validation and the estimation of observation interference, the appropriate regularisation parameter are calculated for ISTA to improve the robustness of the sparse recovery performance. They use simulations to show that the proposed scheme can correct the deep clipping noise with favourable reconstruction quality, which significantly improves the BER performance and therefore assist the LED non‐linearity mitigation.