Cognitive-radio wireless-sensor based on energy detection with improved accuracy: Performance and hardware perspectives

Abstract

This paper presents new system-level design for the cognitive sensor based on energy detection to boast the performance accuracy by maintaining a queue of energy samples and computing their average to determine the decision threshold. Thereafter, these values summed over average number of samples are again compared with the recent energy value to decide whether the spectrum is occupied or unoccupied more accurately. The performance of such technique is evaluated analytically for various decision thresholds. Such evaluations indicate that the some advancements made to the energy detection algorithm has demonstrated improvements in the spectrum sensing accuracy under varying signal to noise ratio (SNR) values. Subsequently, we have shown the benefits of the proposed scheme in increasing the agility of cognitive radio systems. The performance is measured by using the receiver operating characteristic (ROC) curves under varying number of levels for different SNR values like: −5 dB, −10 dB, −15 dB and −20 dB. With small tradeoffs between the detection probability and the false alarm probability, the scheme improves the spectrum sensing ability greatly in low SNR situations when tested with 10, 100, 1000, 10000 and 100000 samples. Thereby, enhancing the performance of such hardware friendly sensors under low SNR has been a potential achievement of our work. Finally, field-programmable gate-array (FPGA) prototyping of the proposed sensor architecture has been carried out and it has a latency of 21760 nS.