Orthogonal frequency division multiplexing (OFDM) has been investigated for the high-speed transmission of data in radio frequency and optical wireless communications. The OFDM systems usually experience high amplitude variations called peak-to-average power ratio (PAPR). The high PAPR makes non-linear distortion and performance degradation because of clipping the signal. To alleviate the high PAPR, we introduce a new technique based on the compressive sensing approach. In the offered method, the OFDM signal is compressed in the time domain and then transmitted. At the receiver, a G-LASSO (group least absolute shrinkage and selection operator) recovery algorithm is applied to reconstruct the original signal. The reconstruction accuracy of the suggested G-LASSO algorithm is compared with the original LASSO algorithm. Numerical results indicate the effectiveness of the offered approach in terms of PAPR reduction and bit error rate performance.

正交频分复用 (OFDM) 已被研究用于射频和光无线通信中数据的高速传输。OFDM 系统通常会经历称为峰均功率比 (PAPR) 的高幅度变化。由于削波信号，高 PAPR 会导致非线性失真和性能下降。为了缓解高 PAPR，我们引入了一种基于压缩感知方法的新技术。在所提供的方法中，OFDM信号在时域中被压缩然后被传输。在接收端，应用 G-LASSO（组最小绝对收缩和选择算子）恢复算法来重建原始信号。将建议的 G-LASSO 算法的重建精度与原始 LASSO 算法进行了比较。