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arXiv 1506.06296cs.ITcs.NImath.IT
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基于非Poisson点过程的异构无线网络建模

On Modeling Heterogeneous Wireless Networks Using Non-Poisson Point Processes

Young Jin Chun, Mazen Omar Hasna, Ali Ghrayeb, Marco Di Renzo

摘要:

未来的无线网络需要支持比当前LTE标准高1000倍的数据率。为了满足日益增长的需求,未来的无线网络将不可避免地发展多种技术之间的无缝互连。这种想法的一种表现是不同类型的网络层(如宏小区和小小区)之间的协作,从而导致所谓的异构网络(HetNet)。研究人员使用随机几何来分析这些网络,并了解它们的真正潜力。毫不奇怪,它已被揭示,干扰对性能有不利影响,特别是如果没有正确建模。干扰可以在空间和/或时间上相关,这在过去被忽视了。例如,通常假设节点彼此完全独立,并遵循齐次泊松点过程(PPP),这在真实网络中不一定正确,因为节点位置是空间相关的。此外,由相关随机过程产生的干扰相关性大多被忽略。为此,我们采取了不同的方法来建模干扰,我们使用非PPP,以及我们研究的空间和时间相关性对HetNet的性能的影响。为了说明相关性对性能的影响,我们考虑三个案例研究,从现实生活中的场景。具体来说,我们使用大规模多输入多输出(MIMO)来了解空间相关性的影响;我们使用随机介质访问协议来研究时间相关性;我们使用协作中继网络来说明时空相关性。我们提出了几个数值例子,通过这些例子我们展示了各种相关类型对HetNet性能的影响。

英文摘要:

Future wireless networks are required to support 1000 times higher data rate, than the current LTE standard. In order to meet the ever increasing demand, it is inevitable that, future wireless networks will have to develop seamless interconnection between multiple technologies. A manifestation of this idea is the collaboration among different types of network tiers such as macro and small cells, leading to the so-called heterogeneous networks (HetNets). Researchers have used stochastic geometry to analyze such networks and understand their real potential. Unsurprisingly, it has been revealed that interference has a detrimental effect on performance, especially if not modeled properly. Interference can be correlated in space and/or time, which has been overlooked in the past. For instance, it is normally assumed that the nodes are located completely independent of each other and follow a homogeneous Poisson point process (PPP), which is not necessarily true in real networks since the node locations are spatially dependent. In addition, the interference correlation created by correlated stochastic processes has mostly been ignored. To this end, we take a different approach in modeling the interference where we use non-PPP, as well as we study the impact of spatial and temporal correlation on the performance of HetNets. To illustrate the impact of correlation on performance, we consider three case studies from real-life scenarios. Specifically, we use massive multiple-input multiple-output (MIMO) to understand the impact of spatial correlation; we use the random medium access protocol to examine the temporal correlation; and we use cooperative relay networks to illustrate the spatial-temporal correlation. We present several numerical examples through which we demonstrate the impact of various correlation types on the performance of HetNets.

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