PAPR reduction using iterative clipping/filtering and ADMM approaches for OFDM-based mixed-numerology systems

Liu, X., Zhang, X., Zhang, L. , Xiao, P., Wei, J., Zhang, H. and Leung, V. C.M. (2020) PAPR reduction using iterative clipping/filtering and ADMM approaches for OFDM-based mixed-numerology systems. IEEE Transactions on Wireless Communications, 19(4), pp. 2586-2600. (doi: 10.1109/TWC.2020.2966600)

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Mixed-numerology transmission is proposed to support a variety of communication scenarios with diverse requirements. However, as the orthogonal frequency division multiplexing (OFDM) remains as the basic waveform, the peak-to average power ratio (PAPR) problem is still cumbersome. In this paper, based on the iterative clipping and filtering (ICF) and optimization methods, we investigate the PAPR reduction in the mixed-numerology systems. We first illustrate that the direct extension of classical ICF brings about the accumulation of inter-numerology interference (INI) due to the repeated execution. By exploiting the clipping noise rather than the clipped signal, the noise-shaped ICF (NS-ICF) method is then proposed without increasing the INI. Next, we address the in-band distortion minimization problem subject to the PAPR constraint. By reformulation, the resulting model is separable in both the objective function and the constraints, and well suited for the alternating direction method of multipliers (ADMM) approach. The ADMM-based algorithms are then developed to split the original problem into several subproblems which can be easily solved with closed-form solutions. Furthermore, the applications of the proposed PAPR reduction methods combined with filtering and windowing techniques are also shown to be effective.

Item Type:Articles
Additional Information:This work was supported in part by the National Natural Science Foundation of China (61931020, 61822104, 61771044), the U.K. Engineering and Physical Sciences Research Council (EP/S02476X/1, EP/P03456X/1) and the Fundamental Research Funds for the Central Universities (RC1631, FRF-TP-19-002C1).
Glasgow Author(s) Enlighten ID:Zhang, Professor Lei
Authors: Liu, X., Zhang, X., Zhang, L., Xiao, P., Wei, J., Zhang, H., and Leung, V. C.M.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:IEEE Transactions on Wireless Communications
ISSN (Online):1558-2248
Published Online:21 January 2020
Copyright Holders:Copyright © 2020 IEEE
First Published:First published in IEEE Transactions on Wireless Communications 19(4): 2586-2600
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
304481Resource Orchestration for Diverse Radio SystemsLei ZhangEngineering and Physical Sciences Research Council (EPSRC)EP/S02476X/1ENG - Systems Power & Energy