Vladimir Savic
Linköping University
44 Papers
330 Citations
Vladimir Savic is an academic researcher from Linköping University. The author has contributed to research in topics: Belief propagation & Wireless sensor network. The author has an hindex of 19, co-authored 44 publications. Previous affiliations of Vladimir Savic include Chalmers University of Technology & Technical University of Madrid.
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Papers
Fingerprinting-Based Positioning in Distributed Massive MIMO Systems
Vladimir Savic,Erik G. Larsson +1 more
- 01 Sep 2015
TL;DR: In this article, a vector of received signal strengths is used for positioning of mobile stations in highly-cluttered multipath environments, in contrast to standard range-based and angle-based techniques.
Belief consensus algorithms for fast distributed target tracking in wireless sensor networks
TL;DR: A unified comparison of the convergence speed and communication cost is provided and a novel BC algorithm based on belief propagation (BP) is proposed that is the fastest in loopy graphs and tree graphs, and it is found that BC-based DPF methods have lower communication overhead than data flooding when the network is sufficiently sparse.
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Cooperative localization in mobile networks using nonparametric variants of belief propagation
Vladimir Savic,Santiago Zazo +1 more
- 01 Jan 2013
TL;DR: This article proposes more flexible and efficient variants of NBP for cooperative localization in mobile networks, and provides an optional 1-lag smoothing done almost in real-time, a novel low-cost communication protocol based on package approximation and censoring, and a higher robustness of the standard mixture importance sampling (MIS) technique.
Kernel Methods for Accurate UWB-Based Ranging with Reduced Complexity
TL;DR: Novel ranging methods based on kernel principal component analysis (kPCA) are proposed, in which the selected channel parameters are projected onto a nonlinear orthogonal high-dimensional space, and a subset of these projections is then used as an input for ranging.
Measurement Analysis and Channel Modeling for TOA-Based Ranging in Tunnels
TL;DR: This paper organized a measurement campaign in a basement tunnel of Linköping university, in which ultra-wideband (UWB) complex impulse responses for line-of-sight (LOS), and three non-LOS (NLOS) scenarios were obtained, and the results indicated the rise-time and maximum excess delay should be used for NLOS identification and error mitigation respectively.