Area-Efficient and Scalable Data-Fusion Based Cooperative Spectrum Sensor for Cognitive Radio

This brief presents an area-efficient technique for the cooperative spectrum sensing (CSS) in data fusion based cognitive radio network. Subsequently, we propose resource-shared and scalable architecture of cooperative spectrum sensor (CSR) by using such technique. It is capable of collectively processing the received signals from six secondary users to reliably detect the spectrum occupancy by primary user. Performance analysis using 16-QAM modulation under fading channel environment indicated that suggested area-efficient based CSS algorithm outperformed the stand-alone spectrum sensing algorithm by 9.45 dB at 0.5 detection probability with a false alarm rate of 0.1. Furthermore, FPGA prototyping of the proposed CSR and its functional validation using real-world hardware test-setup are presented here. Additionally, this CSR architecture has been ASIC synthesized and post-layout simulated in UMC 90 nm-CMOS process. Hence, it occupies 2.47 mm
²
of area, consumes 32 mw of total power at a maximum clock frequency of 101 MHz and delivers an area-efficiency of 0.024 mm
²
- μ\texts. Comparison results have shown that the proposed CSR occupies 63% lesser area and is 47% area-efficient than the conventional implementation.