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出 处:《电视技术》2015年第19期54-58,77,共6页Video Engineering
摘 要:在认知无线网络中,如何保证认知用户的传输质量,满足其QoS要求是值得关注的问题。首先根据认知用户的Qo S要求,将其分成两种等级,实时用户和非实时用户,并分别被建模成M/G/1排队模型,降低了对应的系统时延均值。然后根据系统传输时间均值,讨论了多信道接入策略,通过经典的遗传算法可得最优接入策略,考虑到遗传算法的高复杂度,实际应用中采用反比例接入算法求得次优解,实验数据表明反比例接入算法可以取得与最优接入策略相近的结果且能极大地降低计算时间。An important issue in cognitive radio networks is the achievable Quality of Service(QoS) performance and high transmission performance for SUs'. Firstly, the SU traffic in the system is classified into two priority classes based on QoS requirements, namely delay-sensitive SU and delay-insensitive SU. The transmission of PU and SUs traffic are modeled as M/G/1 queues, and the overall system time of the prioritized SUs is evaluated based on Preemptive Repeat Priority M/G/1 queueing theory. Then, the access strategy is further investigated with respect to the expected overall system time for SU traffic. The classic Genetic Algorithm (GA) is adopted to minimize the expected overall system time. Considering the complexity of GA, the inverse proportional access strategy is adopted to obtain near-optimal results in practice. The results show that the overall system time by means of the algorithm proposed in this paper is close to that by means of GA and reduces the time.
关 键 词:认知无线电 M/G/1排队模型 多信道接入策略:实时性
分 类 号:TN92[电子电信—通信与信息系统]
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