Distributed spectrum sensing in rem based cognitive radio networks

Ever increasing development of wireless devices and wireless networks have increased the value of spectral space‎. ‎Many efforts have been conducted to increase spectral utilization‎. The radio environment mapping opens new gates for developing low cost wireless devices. ‎In this paper‎, ‎a new method is proposed for increasing spectral utilization in distributed networks‎. ‎In this method‎ ‎distributed Kalman filter, which is modified to increase estimation accuracy, is used to estimate position‎, ‎velocity and power of primary transmitters‎. ‎These data are used to select spectrum holes optimally and increase spectral utilization compared to centralized methods‎. Obtained r‎esults are evaluated through practical implementations and simulations‎. ‎Innovations of this research include introducing and employing a linear model for estimating position of a transmitter using received power in line of sight (LoS) and non-line of sight (NLS) conditions, ‎‎‎modifying extended kalman filter and‎ ‎implementation of distributed spectrum sensing; advantages of this method are illustrated compared to centralized methods.‎‎