Optimal censor-based detection in cooperative spectrum sensing
Cooperative spectrum sensing is one of the most important proposed methods to combat with fading, shadowing, and hidden primary user problems. Also, censoring idea was proposed to reduce the communication overhead in cooperative spectrum sensing. In this paper, optimal censor-based strategies are investigated. Optimization problem is formulated under the bandwidth constraint for fixed local rule scenario, fixed fusion rule (OR) scenario, and also joint optimization of local and fusion rules. Solutions to the first two problems are found analytically and the joint optimization problem is solved by means of an iterative search algorithm. Simulation results are also presented to study the impact of the communication constraint on the censoring scheme and the detection performance.
In allusion to the transmission of a new type of truck with three shafts four levels, it's Collaborative Optimization framework including mathematical model is set up. Through taking multidisciplinary optimization software iSIGHT as optimization design platform to integrate disciplinary analysis tool ANSYS and Response Surface Method, Collaborative Optimization of transmission is completed and satisfying optimization scheme is obtained, where Multi-Island Genetic Algorithm is adopted for system-level optimization and Sequential Quadratic Programming is adopted for subsystem-level optimization. The optimization method used in the paper provides important references for optimization design of other complex systems.