CAJ | 학술논문

该文研究了认知无线电多信道联合感知的数学模型，并将此模型转换为以认知系统总吞吐率最大化为目标的带约束优化问题，进而提出一种基于免疫克隆的多信道联合感知算法。仿真实验表明所提算法在收敛速度以及稳定性上均明显优于已有的基于遗传算法的感知方法，并且所提算法在对主用户造成相同的干扰条件下能提供更高的系统总吞吐率。
해문연구료인지무선전다신도연합감지적수학모형，병장차모형전환위이인지계통총탄토솔최대화위목표적대약속우화문제，진이제출일충기우면역극륭적다신도연합감지산법。방진실험표명소제산법재수렴속도이급은정성상균명현우우이유적기우유전산법적감지방법，병차소제산법재대주용호조성상동적간우조건하능제공경고적계통총탄토솔。
This paper studies the mathematical model of Multiband Joint Detection (MJD). The MJD problem can be formulated as a constrained optimization problem with the goal of maximizing the aggregated opportunistic throughput of a cognitive radio system under some constraints on the interference to the Primary User (PU). An Immune Clone Algorithm (ICA) is proposed to solve this problem. The performance of the proposed method is analyzed and compared with the Genetic Algorithm (GA) based technique through computer simulations. Experiment results show that the proposed method offers higher aggregated opportunistic throughput rates under the same interference to PU than GA, and the results demonstrate the stability and effectiveness of the method.