A power-efficient spectrum-sensing scheme using 1-bit quantizer and modified filter banks

Abstract

Spectrum sensing is an efficient way to determine the spectrum availabilities over the frequency range of interest, aiding in improving the spectrum utilization in the cognitive radio (CR) systems. Conventional Nyquist multiband sensing entails higher computational capability for sampling, quantization, and subsequent processing, lending the approach infeasible for applications with limited power budgets. In this brief, a power-efficient spectrum-sensing technique is proposed, which explores an accuracy-complexity tradeoff. The presented spectrum-sensing architecture is based on 1-bit quantization at the CR receiver and implements it in hardware by a resource- and power-efficient approach, using a finite-impulse-response (FIR) filter-bank channelizer. The proposed scheme allows the complex operators like multipliers and quantizers to be replaced by the inverter logic and high-speed comparators, reducing the hardware complexity and power consumption. We validate the proposed scheme on a field-programmable gate-array (FPGA) emulator for an aeronautical L-band digital aeronautical communication system (LDACS) application, and our results show that the proposed scheme achieves substantial resource reduction with at most 5% degradation in the detection accuracy in this case.