Adaptive absolute SCORE algorithm for spectrum sensing in cognitive radio

摘要

The Cognitive Radio (CR) is one of the significant technology to enhance the spectrum utilization efficiency. The Radio Frequency (RF) spectrum is the most valuable natural resource. Due to an increased usage of the cognitive radio, the sensing issues in spectrum are increasing day by day. The CR is emerging technologies that increase the effectiveness and efficiency of the spread spectrum communication. Generally, the spectrum sensing is based on the energy detection and cyclostationary feature detection. The energy detection is a fundamental basic spectrum sensing technique. However, it performs poorly under a low Signal-to-Noise Ratio (SNR) environment. The cyclostationary based sensing technique improves Primary Users (PUs) detection performance with the high complexity of implementation and hardware utilization. Traditional median and Finite Impulse Response (FIR) filters are utilized complex adder and multiplier, which requires large memory space to store the filter coefficients and more hardware utilization. Hence, these filters have computational complexity and more hardware utilization. To overcome above-mentioned problems, Adaptive Absolute SCORE (AA-SCORE) architecture is designed based on optimal FIR filter for further reducing the system complexity to enhance the spectrum utilization efficiency in CR. In this research, the FIR filter is designed by using Radix-8 and Carry Select Adder (CSLA) for reducing the filter complexity. The proposed method is named as AAS-R8-CSLA architecture. The AAS-R8-CSLA architecture was implemented in the Field Programmable Gate Array (FPGA) platform through Verilog code. In order to improve the spectrum utilization efficiency of CR by using AAS-R8-CSLA. The experimental outcome showed that the proposed AAS-R8-CSLA architecture has improved FPGA performance up to 2-3% compared to existing methods like MS and ACS architecture. (C) 2019 Elsevier B.V. All rights reserved.