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Modeling End-to-End Wireless Lossy Channels: A Finite-State Markov Approach

机译:建模端到端无线有损信道:有限状态马尔可夫方法

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In this paper, we present a model for wireless losses in packet transmission data networks. The model provides information about the wireless channel status that can be used in congestion control schemes. A Finite State Markov Channel (FSMC) approach is implemented to model the wireless slow fading for different modulation schemes. The arrival process statistics of the packet traces determine the channel state transition probabilities, where the statistics of both error-free and erroneous bursts are captured. Later, we establish SNR partitioning scheme that uses the transition probabilities as a basis for the state margins. The crossover probability associated with each state is calculated accordingly. We also propose an end-to-end approach to loss discrimination based on the channel state estimation at the receiver. Finally, we present a scheme for finding the channel optimal number of states as a function of the SNR. The presented FSMC approach does not restrict the state transitions to the adjacent states, nor does impose constant state duration as compared to some literature studies. We validate our model by experimental packet traces. Our simulation results show the feasibility of building a fading channel model for better wireless-loss awareness.
机译:在本文中,我们提出了分组传输数据网络中无线损耗的模型。该模型提供有关可以在拥塞控制方案中使用的无线信道状态的信息。实现了有限状态马尔可夫信道(FSMC)方法,以对不同调制方案的无线慢衰落建模。数据包跟踪的到达过程统计信息确定了信道状态转换概率,其中捕获了无错误突发和错误突发的统计信息。稍后,我们建立SNR划分方案,该方案使用转移概率作为状态余量的基础。相应地计算与每个状态关联的交叉概率。我们还提出了一种基于接收器的信道状态估计的端到端损耗鉴别方法。最后,我们提出了一种根据SNR确定信道最佳状态数的方案。与某些文献研究相比,所提出的FSMC方法不将状态转换限制为相邻状态,也不施加恒定的状态持续时间。我们通过实验数据包跟踪来验证我们的模型。我们的仿真结果表明建立衰落信道模型以更好地了解无线丢失的可行性。

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