Cognitive Engine with Dynamic Priority Resource Allocation for Wireless Networks

A cognitive engine with dynamic priority resource allocation (CE-DPRA) is proposed for wireless networks by utilizing a maximum likelihood estimation method. The receiving signal strength (RSS) from an unlicensed cognitive radio (CR) user can be measured through estimating the unknown position of a licensed mobile user. The priority algorithm for access control enables the selection of a proper CR user waiting for transmission. Both data rate and spectral efficiency can be increased after adapting CE-DPRA. Also the power constraint method can avoid excessive interference caused by signal transmitting from CR users so as to improve the communication quality of mobile users. Simulation results show that the proposed CE-DPRA achieves the performance of high transmission data rate, less interference power, and low average outage probability.