Henk Wymeersch

Bio: Henk Wymeersch is an academic researcher from Chalmers University of Technology. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 50, co-authored 477 publications receiving 10655 citations. Previous affiliations of Henk Wymeersch include Eindhoven University of Technology & Ghent University.

Cooperative Localization in Wireless Networks

Abstract: Location-aware technologies will revolutionize many aspects of commercial, public service, and military sectors, and are expected to spawn numerous unforeseen applications. A new era of highly accurate ubiquitous location-awareness is on the horizon, enabled by a paradigm of cooperation between nodes. In this paper, we give an overview of cooperative localization approaches and apply them to ultrawide bandwidth (UWB) wireless networks. UWB transmission technology is particularly attractive for short- to medium-range localization, especially in GPS-denied environments: wide transmission bandwidths enable robust communication in dense multipath scenarios, and the ability to resolve subnanosecond delays results in centimeter-level distance resolution. We will describe several cooperative localization algorithms and quantify their performance, based on realistic UWB ranging models developed through an extensive measurement campaign using FCC-compliant UWB radios. We will also present a powerful localization algorithm by mapping a graphical model for statistical inference onto the network topology, which results in a net-factor graph, and by developing a suitable net-message passing schedule. The resulting algorithm (SPAWN) is fully distributed, can cope with a wide variety of scenarios, and requires little communication overhead to achieve accurate and robust localization.

Fundamental Limits of Wideband Localization— Part II: Cooperative Networks

Abstract: The availability of position information is of great importance in many commercial, governmental, and military applications Localization is commonly accomplished through the use of radio communication between mobile devices (agents) and fixed infrastructure (anchors) However, precise determination of agent positions is a challenging task, especially in harsh environments due to radio blockage or limited anchor deployment In these situations, cooperation among agents can significantly improve localization accuracy and reduce localization outage probabilities A general framework of analyzing the fundamental limits of wideband localization has been developed in Part I of the paper Here, we build on this framework and establish the fundamental limits of wideband cooperative location-aware networks Our analysis is based on the waveforms received at the nodes, in conjunction with Fisher information inequality We provide a geometrical interpretation of equivalent Fisher information (EFI) for cooperative networks This approach allows us to succinctly derive fundamental performance limits and their scaling behaviors, and to treat anchors and agents in a unified way from the perspective of localization accuracy Our results yield important insights into how and when cooperation is beneficial

NLOS identification and mitigation for localization based on UWB experimental data

Abstract: Sensor networks can benefit greatly from location-awareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwidth (UWB) transmission is a promising technology for location-aware sensor networks, due to its power efficiency, fine delay resolution, and robust operation in harsh environments. However, the presence of walls and other obstacles presents a significant challenge in terms of localization, as they can result in positively biased distance estimates. We have performed an extensive indoor measurement campaign with FCC-compliant UWB radios to quantify the effect of non-line-of-sight (NLOS) propagation. From these channel pulse responses, we extract features that are representative of the propagation conditions. We then develop classification and regression algorithms based on machine learning techniques, which are capable of: (i) assessing whether a signal was transmitted in LOS or NLOS conditions; and (ii) reducing ranging error caused by NLOS conditions. We evaluate the resulting performance through Monte Carlo simulations and compare with existing techniques. In contrast to common probabilistic approaches that require statistical models of the features, the proposed optimization-based approach is more robust against modeling errors.

Location-Aware Communications for 5G Networks: How location information can improve scalability, latency, and robustness of 5G

Abstract: Fifth-generation (5G) networks will be the first generation to benefit from location information that is sufficiently precise to be leveraged in wireless network design and optimization. We argue that location information can aid in addressing several of the key challenges in 5G, complementary to existing and planned technological developments. These challenges include an increase in traffic and number of devices, robustness for mission-critical services, and a reduction in total energy consumption and latency. This article gives a broad overview of the growing research area of location-aware communications across different layers of the protocol stack. We highlight several promising trends, tradeoffs, and pitfalls.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Coverage control for mobile sensing networks

Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Bit-Interleaved Coded Modulation

Abstract: Zehavi (1992) showed that the performance of coded modulation over a Rayleigh fading channel can be improved by bit-wise interleaving the encoder output and by using an appropriate soft-decision metric as an input to a Viterbi decoder. The goal of this paper is to present in a comprehensive fashion the theory underlying bit-interleaved coded modulation, to provide tools for evaluating its performance, and to give guidelines for its design.