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遗传算法是由受生物进化过程启发而形成的进行优化和机器学习的算法。受遗传算法善于解决复杂的组合优化问题的启发，对应用遗传算法到无线多媒体通信中的可能性进行了探讨。并通过介绍基于蜂窝的无线多媒体通信中的多址协议所希望的性能，强调了理解网络所载通信量负荷的属性的重要性。在对一些候选的多址协议进行了评价后，提出了一种基于遗传算法的自适应对策，以提高在有多种通信载荷存在的环境中的无线局域网的网络性能。这种自适应多址协议对策能够在时域以和从所运行的网络环境相互作用中获得的网络载荷反馈成一定函数关系进行自我适应、调节。
Genetic algorithms are algorithms developed for optimization and machine learning inspired by the biological evolutionary process. The genetic algorithm is good at solving complex combinatorial optimization problems inspired by the application of genetic algorithms to wireless multimedia communication possibilities are discussed. And emphasizes the importance of understanding the attributes of the traffic load on the network by introducing the desired performance of the multiple-access protocol in cellular-based wireless multimedia communications. After evaluating some candidate multiple access protocols, an adaptive strategy based on genetic algorithm is proposed to improve the network performance of wireless LAN in environments with multiple communication loads. This adaptive multiple-access protocol countermeasure can self-adapt and adjust in the time domain by a certain function relationship with the network load obtained from the interaction of the running network environment.