FPGA Implementation of Adaptive Absolute SCORE Algorithm for Cognitive Radio Spectrum Sensing with WTM and LFA

Abstract

Cognitive Radio (CR) is generally a wireless communication system that has the ability to improve the network’s system-capacity. Since, the white space or temporally unused spectrum are used to enhance the systemcapacity and the important operation involved in the cognition cycle is spectrum sensing. This spectrum sensing supports the Cognitive Radio users to adjust with the environment by identifying the white/vacant spaces without creating any interference to the primary user communication. The traditional filters such as Finite Impulse Response (FIR) filters and median filters used in the spectrum sensing obtains high area utilization in Cognitive Radio. In order to overcome this, an Adaptive Absolute SCORE (AAS) technique is developed based on the FIR for improving the sensing function and radio sensitivity. The area and frequency of the AAS are enhanced by using the Wallace tree multiplier (WTM) and Ladner-Fischer Adder (LFA) in the design of the FIR. The proposed architecture used for the spectrum sensing is named as AAS-WTM-LFA. This AAS-WTM-LFA architecture is developed in the Xilinx tool for different Virtex devices. The performance of AAS-WTM-LFA is analyzed in terms of LUT, slices, flip flops, bonded Input and Output Block (IOB), frequency and power. Additionally, the quality of signal processed through the AAS-WTM-LFA architecture is analyzed as Bit Error Rate (BER) and False Acceptance Rate (FAR). Additionally, the AAS-WTM-LFA architecture is compared with ACS, AAS, AAS-CSLA, AAS-R8-CSA and AASR8-CSLA. The number of LUT for AAS-WTM-LFA architecture is 247 for Spartan 6 device, that is less when compared to the remaining architectures.