一种降低OFDM误码率及立方度量值的凸优化算法

相比于功率峰均比（PAPR），立方度量能够更加准确地预测功放的功率回退量，因此被认为是更有效的衡量正交频分复用（OFDM）信号包络变化的度量。为了提高功放效率，常用优化方法是直接最小化信号的立方度量值。然而，这样会引入严重的带内失真，造成系统误码率性能的恶化。该文提出了一种在立方度量值约束下最小化系统带内失真的凸优化模型，并设计了内点法定制方案求解此优化问题。仿真结果显示该算法相比现有优化算法能够显著提高系统误码率及立方度量性能。

A Convex Optimization Algorithm for Reducing the Ber and Cubic Metric in OFDM Systems

Since cubic metric (CM) can more accurately predict the power de-rating of power amplifier (PA), it is recognized as a better metric to characterize the envelope fluctuations of orthogonal frequency division multiplexing (OFDM) signals than peak-to-average power ratio (PAPR). To improve the PA efficiency, a common scheme is minimizing the CM value of signals. However, this aggravates the in-band distortion, resulting in bit error ratio (BER) degradation of systems. This paper formulates the problem as an in-band distortion optimization subject to CM constraint, and a customized interior-point algorithm is developed to solve the optimization problem. Simulation results show that the proposed algorithm provides better BER and CM-reduction performance than existing optimization schemes.