The simulations of QBFO based spectrum allocation have been conducted as compared to a very popular spectrum allocation algorithm known as CSGC and QGA, with respect to the following performance measures: solution quality and convergence speed.
The general CR spectrum allocation model in  called graph coloring model assumes that the environmental conditions are static during the time it takes to perform spectrum assignment, and CSGC is used to solve the allocation problem.
The commonly used algorithm to solve the spectrum allocation problem is Color Sensitive Graph Coloring (CSGC) algorithm.
It is obvious that the proposed QBFO-based spectrum allocation algorithm can obtain better sum reward, compared to the CSGC and QGA.
In order to validate the performance of this algorithm, we compare it with the classic spectrum allocation algorithm CSGC , immune clonal selection algorithm , and GA-SA (GA-spectrum allocation) .
Meanwhile, with the increase of iteration times (CSGC is deterministic algorithm and does not change with the iteration times), convergence speed of this algorithm is faster than that of serial immune algorithms, which shows that this algorithm has satisfactory result with fast solution speed.
By reducing the optimal allocation to one of color-sensitive graph coloring (CSGC), we show that it is an NP-hard problem.
The results of the CSGC
's study are available in the Pew Forum's report Global Christianity: A Report on the Size and Distribution of the World's Christian Population (www.pewforum.org /christian/global-christianity-worlds-christian-population.
Peng and Zheng first considered color sensitive graph coloring (CSGC
) algorithm for the heterogeneity in the spectrum rewards in Ref.