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 increas-  ing 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.  Index Terms—Digital Design, FPGA, cognitive radio, detection  probability, spectrum sensing and energy detection