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Massachusetts Institute of Technology

Network navigation with scheduling

Abstract

dc:description.abstract

Network navigation is a promising paradigm for enabling location-awareness in dynamic wireless networks. A wireless navigation network consists of agents (mobile with unknown locations) and anchors (possibly mobile with known locations). An agent can estimate its locations based on inter- and intra-node measurements, as well as prior knowledge. In the presence of limited wireless resources, only a subset rather than all of the node pairs can perform inter-node measurements at a time. The procedure of selecting node pairs at different time instants for inter-node measurements, referred to as network scheduling, affects the time evolution of agents' localization errors. The key to achieve high navigation accuracy and efficient channel usage is to maximize the benefit from agents' inter-node measurements. Therefore, it is critical to design scheduling algorithms that decide for each agent with whom and when to perform inter-node measurements. This thesis introduces situation-aware scheduling that exploits network states to adaptively schedule agents' inter-node measurements. In particular, an analytical framework is developed to determine the effects of scheduling strategies and network settings on the localization error evolution. Furthermore, efficient and distributed situation-aware scheduling algorithms tailored for wireless navigation networks are designed, leading to high navigation accuracy and efficient channel usage. The first part of the thesis develops an analytical framework to determine the localization error evolution as a function of scheduling algorithms and network settings. In particular, both sufficient and necessary conditions for the boundedness of the error evolution are provided. Furthermore, opportunistic and random situation-aware scheduling strategies are proposed, and bounds on the corresponding time-averaged network localization errors are derived. These strategies are proved to be optimal in terms of the error scaling with the number of agents. Finally, the navigation accuracy is shown to be improved by sharing the wireless resources among multiple measurement pairs instead of allocating all the resources to a single pair at a time. The second part of the thesis designs efficient slotted and unslotted situation-aware scheduling algorithms tailored for wireless navigation networks based on the analytical results from the first part. The algorithm parameters, such as access probabilities and access rates, are optimized based on bounds for the time-averaged network localization error (NLE). The proposed algorithms lead to significant performance improvement compared with scheduling algorithms from wireless communication networks. The third part of the thesis develops a framework for the design of random-access-based distributed and asynchronous scheduling algorithms for wireless navigation networks, in which the channel access probabilities are optimized based on the evolution of agents' localization errors. The proposed algorithm achieves higher navigation accuracy and more efficient channel usage than the commonly used carrier sensing multiple access (CSMA) algorithm from wireless communication networks, at the cost of minimal communication overhead and computational complexity. The performance improvement is shown via numerical and experimental results. The contributions of this thesis provide a framework for the analysis and design of scheduling algorithms for wireless navigation networks, leading to high-accuracy, efficient, and flexible network navigation.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wang, Tianheng, Ph. D. Massachusetts Institute of Technology
Advisor dc:contributor.advisor
  • Moe Z. Win.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/115653
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/115653

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Wang, Tianheng, Ph. D. Massachusetts Institute of Technology. Network navigation with scheduling. Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115653