The cubic metric (CM) is being regarded as a more accurate metric for envelope fluctuations of orthogonal frequency division multiplexing (OFDM) signals than peak-to-average power ratio (PAPR). Iterative clipping and filtering (ICF) is a simple and efficient technique for PAPR reduction. However, analysis shows that it cannot achieve sufficient CM reduction due to the difference between the two metrics. Proposed is a new technique called descendent clipping and filtering (DCF) for CM reduction. Unlike ICF, DCF introduces a new parameter termed descent factor to improve its performance. Simulation results show that DCF can achieve better performance with only one iteration than ICF with multiple iterations

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 interiorpoint 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.Index Terms-OFDM, peak-to-average power ratio, clipping and filtering, convex optimization.

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Orthogonal frequency division multiplexing (OFDM) has been adopted by several communication standards. A major disadvantage of OFDM is the large envelope fluctuations which cause the degradation of system performance. Peak-to-average power ratio (PAPR) is a well-known measure for the envelope fluctuations. However, recently, another metric, known as cubic metric (CM), has been attracting increasing attention since it can predict the power de-rating of power amplifier more accurately. In this paper, our analysis shows that minimizing CM, subject to the in-band distortion and out-of-band radiation, can be formulated as a convex optimization problem. By solving this convex problem, the minimum CM satisfying the given requirements can be obtained. Simulation results verify the effectiveness of the proposed method.