Noise Effects on a Proposed Algorithm for Signal Reconstruction and Bandwidth Optimization


  • Ahmed F. Ashour Electrical and Computer Engineering Department, Idaho State University 921 S 8th Ave 83201, Pocatello, USA
  • Ashraf A. M. Khalaf Department of Electronics and Communications Engineering, Faculty of Engineering, Department of Computer Science, Minia University Damaris 61519, El-Minia, Egypt
  • Aziza I. Hussein Electrical and Computer Engineering Department, Effat University Al-Nazlah Al-Yamaniyah 34689, Jeddah, KSA
  • Hesham F. A. Hamed Faculty of Engineering, Egyptian Russian University Faculty of Engineering, Minia University Badr 11829, Cairo, Egypt Damaris 61519, El-Minia, Egypt
  • Ashraf Ramadan Electrical and Computer Engineering Department, Higher Technological Institute Industrial Area2 44629, 10th of Ramadan, Egypt



signal reconstruction, bandwidth optimization, AWGN, noise reduction, baseband signal, NMSE, noise reject filter


The development of wireless technology in recent years has increased the demand for channel resources within a limited spectrum. The system's performance can be improved through bandwidth optimization, as the spectrum is a scarce resource. To reconstruct the signal, given incomplete knowledge about the original signal, signal reconstruction algorithms are needed. In this paper, we propose a new scheme for reducing the effect of adding additive white Gaussian noise (AWGN) using a noise reject filter (NRF) on a previously discussed algorithm for baseband signal transmission and reconstruction that can reconstruct most of the signal’s energy without any need to send most of the signal’s concentrated power like the conventional methods, thus achieving bandwidth optimization. The proposed scheme for noise reduction was tested for a pulse signal and stream of pulses with different rates (2, 4, 6, and 8 Mbps) and showed good reconstruction performance in terms of the normalized mean squared error (NMSE) and achieved an average enhancement of around 48%. The proposed schemes for signal reconstruction and noise reduction can be applied to different applications, such as ultra-wideband (UWB) communications, radio frequency identification (RFID) systems, mobile communication networks, and radar systems.






Original Scientific Papers