正交频分复用(OFDM)技术作为第四代无线通信的核心,其主要缺陷就是有很高的峰均功率比(PAPR)。目前，低复杂度的PAPR减小技术研究主要侧重于切削和子载波保留两种方法。由于已有的文献中，设计切削噪声估计和消除算法以及在时域优化峰值抵消的信号，均存在计算复杂度较高的缺点，因此无法满足实际系统的设计要求。本课题着重研究利用压缩感知技术来设计低复杂度的切削噪声估计和消除算法以及在子载波保留方法中如何利用改进的压缩感知技术来估计峰值抵消的信号。不同于传统的切削方法，我们从切削后的OFDM信号的稀疏性入手，在接收端，利用部分而非全部数据子载波，通过压缩感知技术来设计复杂度更低的重构切削噪声算法。 对子载波保留方法，无需预先在时域优化峰值抵消的信号。通过利用压缩感知技术和预先保留的部分子载波，来正确估计发射OFDM信号的被切削部分，从而设计复杂度更低的恢复峰值抵消信号的算法。

As the core of the fourth generation of wireless communication, one of the major drawbacks of OFDM is the high peak to average power ratio (PAPR) of the transmitted signals. At present, The technologies of PAPR reduction with low complexity mainly focus on clipping and tone reservation(TR). The algorithms of designing clipping noise estimation and optimizing peak reduction's signals in the time domain have drawbacks with high computational complexity, so the design requirement on practical systems can't be satisfied. In the subject, we focus on designing clipping noise estimation and cancellation algorithms with lower complexity by compressed sensing (CS) and estimating peak reduction signals by improved CS for the TR technology, Unlike the traditional clipping，using a fraction of the data tones instead of the whole data tones at the receiver, the CS technique is applied to reconstruct the clipping noise due to clipped signal's sparseness. Moreover, it isn't necessary to optimize peak reduction's signals in the time domain in advance for the TR technology. The clipped fraction of transmited OFDM signals can be exactly estimated by CS and reserved tones, so reconstructing a peak cancellation algorithm with lower complexity can be designed.