Author(s)

Mohammed Abo-Zahhad^1,2, Sabah M. Ahmed^2,3, Mohammed Farrag^2,4, Khaled Ali BaAli^2,5

¹Electronics and Communication Engineering Department, School of Electronics, Communications and Computer Engineering, Egypt-Japan University for Science and Technology, Alexandria, Egypt.
²Electrical and Electronics Engineering Department, Faculty of Engineering, Assiut University, Assiut, Egypt.
³Mechatronics and Robotics Engineering Department, School of Innovative Design Engineering, Egypt-Japan University for Science and Technology, Alexandria, Egyp.
⁴Electrical Engineering Department, King Khalid University (KKU), Abha, KSA.
⁵Electronics and Communication Department, Faculty of Engineering and Petroleum, Hadhramaut University, Mukalla, Republic of Yemen.

Spectrum sensing is a core function at cognitive radio systems to have spectrum awareness. This could be achieved by collecting samples from the frequency band under observation to make a conclusion whether the band is occupied, or it is a spectrum hole. The task of sensing is becoming more challenging especially at wideband spectrum scenario. The difficulty is due to conventional sampling rate theory which makes it infeasible to sample such very wide range of frequencies and the technical requirements are very costly. Recently, compressive sensing introduced itself as a pioneer solution that relaxed the wideband sampling rate requirements. It showed the ability to sample a signal below the Nyquist sampling rate and reconstructed it using very few measurements. In this paper, we discuss the approaches used for solving compressed spectrum sensing problem for wideband cognitive radio networks and how the problem is formulated and rendered to improve the detection performance.

Cognitive Radio, Spectrum Sensing, Compressive Sensing, Compressed Measurements, Nyquist Sampling Rate

Abo-Zahhad, M. , Ahmed, S. , Farrag, M. and BaAli, K. (2018) Wideband Cognitive Radio Networks Based Compressed Spectrum Sensing: A Survey. Journal of Signal and Information Processing, 9, 122-151. doi: 10.4236/jsip.2018.92008.