On Minimizing the Cubic Metric of OFDM Signals Using Convex Optimization

• Published in: IEEE transactions on broadcasting Vol. 60; no. 3; pp. 511 - 523
• Main Authors: Zhu, Xiaodong, Hu, Haichao, Meng, Zhonglou, Xia, Jinxiang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: clipping and filtering; Computing time; Convergence; Convex functions; convex optimization; Convexity; Envelopes; Fluctuation; Masks; Measurement; Minimization; OFDM; Optimization; Orthogonal Frequency Division Multiplexing; Peak to average power ratio; Radio frequency; Spectra; Symbols; convex optimization; OFDM; peak-to-average power ratio; clipping and filtering
• ISSN: 0018-9316; 1557-9611
• DOI: 10.1109/TBC.2014.2339534

A main disadvantage of orthogonal frequency division multiplexing (OFDM) signals is the large envelope fluctuation that limits transmitter power efficiency. Peak-to-average power ratio and cubic metric (CM) are two metrics commonly used to quantify this envelope fluctuation, and now the latter is attracting increasing attention as it can more accurately predict the power de-rating of power amplifier. In this paper, convex optimization is introduced to minimize CM, subject to the constraints on error vector magnitude (EVM) and spectral mask. To solve the formulated optimization problem, a customized interior-point method (IPM) is developed. Simulation results verify the high efficiency of the proposed IPM. For an 802.11a compliant OFDM system, subject to the maximum allowed EVM=5%, 10%, 15% and spectral mask constraints, after three iterations the performance gaps between our IPM and the optimal solution are less than 0.2dB for 99.9% of the symbols.