مشخصات پژوهش

عنوان	Modified Compressive Sensing Reconstruction Algorithm for Clipping Noise Estimation in OFDM Systems
نوع پژوهش	مقاله ارائه شده
کلیدواژه‌ها	OFDM systems, PAPR problem, compressive sensing, Clipping noise estimation
چکیده	A simple technique to reduce the peak-to-average power ratio (PAPR) is clipping the signal before the power amplifier. The noise resulted from the clipping process increases bit error rate (BER) which degrades the system performance. In this paper we have used d[n] as the distance between the clipped signal and the clipping level to modify compressive sensing (CS) algorithm to estimate the clipping noise. This modification is made in the sensing matrix by removing the redundant columns which is done by comparing d[n] with a parameter called εopt. The performance of the proposed scheme depends on this parameter which is calculated by numerical experiments on different signal-to-noise ratio (SNR) values. Simulation results demonstrated that the proposed scheme leads to improved estimation for clipping noise and also complexity reduction for the reconstruction algorithm.
پژوهشگران	کمال محامدپور (نفر دوم)، محمدجواد عزیزی پور (نفر اول)