A Bayesian Perspective on RSS Based Localization for Visible Light Communication With Heterogeneous Networks Extension
A Bayesian Perspective on RSS Based Localization for Visible Light Communication With Heterogeneous Networks Extension
复制标题
DOI：
10.1109/access.2017.2746141
复制
发表时间：
2017-08
期刊：
影响因子：
3.9
通讯作者：
Saliha Buyukcorak;Günes Karabulut-Kurt
中科院分区：
文献类型：
--
作者：
Saliha Buyukcorak;Günes Karabulut-Kurt
在本文中，我们提出了一种新的概率定位方法，依赖于一个大都市黑斯廷斯（MH）算法为基础的贝叶斯方法可见光通信（VLC）系统。由于使用的MH算法从马尔可夫链蒙特卡罗方法，所提出的方法的定位能力变得更加强大，对不同的信道传播条件和测量的不确定性。所提出的方法的有效性证明了数值分析的基础上，在3-D室内环境中的模拟比较的方式与最小二乘（LS）和差分LS算法为基础的定位解决方案，同时规避基于LS的方法的缺点。为了解决基于VLC的定位系统中的短距离挑战，还为多层异构网络（HetNet）开发了一种高效的混合定位框架，该框架联合考虑VLC和射频网络。我们的方法主要考虑独立的定位解决方案的分支，每个估计的目标位置，利用MH为基础的贝叶斯方法。基于仿真结果，所提出的多层HetNet框架提供了一个强大的性能。总的来说，我们表明，与新的VLC定位方案，在短距离的性能得到了增强，而与HetNets的本地化的有效性，在长距离的提高。
In this paper, we propose a novel probabilistic localization approach that relies on a Metropolis–Hastings (MH) algorithm-based Bayesian approach to visible light communication (VLC) systems. Due to the usage of the MH algorithm from Markov chain Monte Carlo methods, the positioning capability of the proposed approach becomes more robust against varying channel propagation conditions and measurement uncertainties. The validity of the proposed approach is demonstrated by numerical analyses based on simulations in 3-D indoor environments in a comparative manner with the least square (LS) and the differential LS algorithms-based localization solutions, while circumventing the shortcomings of LS-based approaches. Addressing the short range challenge in the VLC-based positioning system, an efficient hybrid localization framework is also developed for multi-tier heterogeneous networks (HetNets), jointly considering VLC and radio frequency networks. Our methodology mainly considers independent positioning solution branches that each estimate the target location by utilizing the MH-based Bayesian approach. Based on simulation results, the proposed framework for multi-tier HetNets provides a robust performance. Overall, we show that with the new VLC localization scheme, the performance in the short range is enhanced, while with HetNets the effectiveness of the localization in the long range is improved.