Optimization of Cooperative Spectrum Sensing Using Quantized Data Fusion Scheme for Cognitive Radio Network

Abstract

Cognitive Radio (CR) is used to maximize spectrum utilization. When the licensed user is not using the
spectrum, at that time CR will use spectrum to communicate with other CR. Hence, spectrum sensing which is the
procedure to observe primary user’s existence, is important to CR. Cooperative spectrum sensing have a efficiency to
detect spectrum holes in cognitive radio network (CRN) by cooperating the sensing information of multiple cognitive radio
users . In cooperative spectrum sensing, combining the local observations of the secondary users and the fusion centre is
the most crucial factor that determines the overall performance of cooperative sensing. Detection performance is
determined by the quality of local observations and the quality of the information received by the fusion centre (FC).
Therefore, the number of bits sent to fusion centre (FC), and the global decision logic affect the system performance. but
the bandwidth of the control channel used for collecting the sensing information is limited, it is necessary to quantize the
received signal energy information in each user In this paper, we investigate the energy detection based cooperative
spectrum sensing technique and propose a quantized cooperative spectrum sensing. we obtain an optimal quantized data
fusion scheme that maximizes the detection probability for a given false alarm probability through the optimization
algorithm which is based on Neyman-Pearson criterion We also compare performance of conventional hard data fusion
scheme like AND, OR, MAJRITY logic as well as soft data fusion scheme i.e. equal gain combiner (EGC) with proposed
data fusion scheme. Simulation result shows that the performance of proposed optimized quantized data fusion scheme is
better than conventional hard data fusion scheme and close to standard soft data fusion scheme i.e EGC which requited
larger bandwidth and energy of reporting channel. Proposed optimal data fusion scheme require less bandwidth and
energy of convention soft data fusion by just increase the overhead of 3 bit.