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Neural network based mobile phone localization using Bluetooth connectivity

机译:使用蓝牙连接的基于神经网络的手机定位

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摘要

Location information is useful for mobile phones. There exists a dilemma between the relatively high price of GPS devices and the dependence of location information acquisition on GPS for most phones in current stage. To tackle this problem, in this paper, we investigate the position inference of phones without GPS according to Bluetooth connectivity and positions of beacon phones. With the position of GPS-equipped phones as beacons and with the Bluetooth connections between neighbor phones as constraints, we formulate the problem as an optimization problem defined on the Bluetooth network. The solution to this optimization problem is not unique. Heuristic information is employed to improve the performance of the result in the feasible set. Recurrent neural networks are developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. The hardware implementation of the proposed neural network is also explored in this paper. Simulations and comparisons with different application backgrounds are considered. The results demonstrate the effectiveness of the proposed method.
机译:位置信息对于手机很有用。在现阶段大多数手机中,相对昂贵的GPS设备价格与GPS的位置信息获取之间存在着矛盾。为了解决这个问题,在本文中,我们根据蓝牙连接和信标电话的位置,研究了没有GPS的电话的位置推断。以配备GPS的手机的位置为信标,并以相邻手机之间的蓝牙连接为约束,我们将问题表述为在蓝牙网络上定义的优化问题。此优化问题的解决方案并非唯一。使用启发式信息来改善可行集中结果的性能。开发了递归神经网络以实时分布式解决问题。理论上证明了神经网络的收敛性和所定义问题的解决方案可行性。本文还探讨了所提出的神经网络的硬件实现。考虑了不同应用背景下的仿真和比较。结果证明了该方法的有效性。

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