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首页> 外文期刊>IEEE transactions on wireless communications >Performance Analysis of Device-to-Device Communications with Dynamic Interference Using Stochastic Petri Nets
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Performance Analysis of Device-to-Device Communications with Dynamic Interference Using Stochastic Petri Nets

机译:随机Petri网动态干扰的设备间通信性能分析

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In this paper, we study the performance of Device-to-Device (D2D) communications with dynamic interference. In specific, we analyze the performance of frequency reuse among D2D links with dynamic data arrival setting. We first consider the arrival and departure processes of packets in a non-saturated buffer, which result in varying interference on a link based on the change of its backlogged state. The packet-level system behavior is then represented by a coupled processor queuing model, where the service rate varies with time due to both the fast fading and the dynamic interference effects. In order to analyze the queuing model, we formulate it as a Discrete Time Markov Chain (DTMC) and compute its steady-state distribution. Since the state space of the DTMC grows exponentially with the number of D2D links, we use the model decomposition and some iteration techniques in Stochastic Petri Nets (SPNs) to derive its approximate steady state solution, which is used to obtain the approximate performance metrics of the D2D communications in terms of average queue length, mean throughput, average packet delay and packet dropping probability of each link. Simulations are performed to verify the analytical results under different traffic loads and interference conditions.
机译:在本文中,我们研究了具有动态干扰的设备到设备(D2D)通信的性能。具体来说,我们使用动态数据到达设置来分析D2D链路之间的频率复用性能。我们首先考虑数据包在非饱和缓冲区中的到达和离开过程,这会导致基于其积压状态的变化而对链路产生不同的干扰。然后,通过耦合处理器排队模型来表示数据包级系统的行为,其中服务速率由于快速衰落和动态干扰效应而随时间变化。为了分析排队模型,我们将其表示为离散时间马尔可夫链(DTMC)并计算其稳态分布。由于DTMC的状态空间随D2D链接的数量呈指数增长,因此我们在随机Petri网(SPN)中使用模型分解和一些迭代技术来推导其近似稳态解,该解可用于获得DTMC的近似性能指标。 D2D通信的平均队列长度,平均吞吐量,平均数据包延迟和每个链路的数据包丢弃概率。进行仿真以验证不同交通负载和干扰条件下的分析结果。

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