On the Spatial Predictability of Communication Channels

Malmirchegini, Mehrzad; Mostofi, Yasamin

doi:10.1109/twc.2012.012712.101835

Cited by 145 publications

(160 citation statements)

References 20 publications

(39 reference statements)

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“…This approach is based on a time-varying RSS variation model and a spatial correlation-based channel estimation [227], which can be done by GP [228]. While other works assume a constant RSS variation for all the APs, the solution in [72] presumes that the RSS variation for each AP varies independently in order to consider different propagation conditions over time and space.…”

Section: B Fingerprint Matchingmentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

354

171

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Abstract-Location information for events, assets, and individuals, mostly focusing on two dimensions so far, has triggered a multitude of applications across different verticals, such as consumer, networking, industrial, health care, public safety, and emergency response use cases. To fully exploit the potential of location awareness and enable new advanced location-based services, localization algorithms need to be combined with complementary technologies including accurate height estimation, i.e., three dimensional location, reliable user mobility classification, and efficient indoor mapping solutions. This survey provides a comprehensive review of such enabling technologies. In particular, we present cellular localization systems including recent results on 5G localization, and solutions based on Wireless Local Area Networks (WLAN), highlighting those that are capable of computing 3D location in multi-floor indoor environments. We overview range-free localization schemes, which have been traditionally explored in Wireless Sensor Networks (WSN) and are nowadays gaining attention for several envisioned Internet of Things (IoT) applications. We also present user mobility estimation techniques, particularly those applicable in cellular networks, that can improve localization and tracking accuracy. Regarding the mapping of physical space inside buildings for aiding tracking and navigation applications, we study recent advances and focus on smartphone-based indoor Simultaneous Localization and Mapping (SLAM) approaches.The survey concludes with service availability and system scalability considerations, as well as security and privacy concerns in location architectures, discusses the technology roadmap, and identifies future research directions.

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Section: B Fingerprint Matchingmentioning

confidence: 99%

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Laoudias¹,

Moreira

Kim

et al. 2018

IEEE Commun. Surv. Tutorials

354

171

View full text Add to dashboard Cite

show abstract

“…The radii r j are computed from the channel statistics which can be estimated using the techniques presented in [4]. Nevertheless, for lack of space we do not provide here the details on how to compute it.…”

Section: Proposed Solutionmentioning

confidence: 99%

Robust Trajectory Planning for Robotic Communications Under Fading Channels

Licea¹,

Varma²,

Lasaulce³

et al. 2017

Ubiquitous Networking

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Abstract. We consider a new problem of robust trajectory planning for robots that have a physical destination and a communication constraint. Specifically, the robot or automatic vehicle must move from a given starting point to a target point while uploading/downloading a given amount of data within a given time, while accounting for the energy cost and the time taken to download. However, this trajectory is assumed to be planned in advance (e.g., because online computation cannot be performed). Due to wireless channel fluctuations, it is essential for the planned trajectory to be robust to packet losses and meet the communication target with a sufficiently high probability. This optimization problem contrasts with the classical mobile communications paradigm in which communication aspects are assumed to be independent from the motion aspects. This setup is formalized here and leads us to determining non-trivial trajectories for the mobile, which are highlighted in the numerical result.

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“…Such a planning approach, in realistic fading environments, requires an assessment of the link qualities at places over the pre-defined trajectory that have not yet been visited by the robot. We show how our previously-proposed probabilistic channel prediction framework of [15], [16] allows the robot to assess the shadowing and path loss components of the channel over the trajectory and plan its motion and communication strategies accordingly. In particular, we prove that in order to save energy, the robot should move faster (slower) and send fewer (more) bits at the locations that have worse (better) predicted channel qualities.…”

Section: Statement Of Contributionmentioning

confidence: 99%

“…Section II describes the motion and communication models, and briefly discusses the probabilistic channel assessment framework of [15], [16]. Section III presents our proposed optimization framework, based on the probabilistic assessment of shadowing and path loss terms, and proves a number of properties of the optimum solution.…”

Section: Statement Of Contributionmentioning

confidence: 99%

“…To do so, however, the robot needs to have an assessment of the channel to the remote station along T before traversing it. In this section, we first summarize the probabilistic channel assessment framework that enables the robot to assess the channel at unvisited locations along its trajectory, based on a small number of channel measurements [15], [16]. We then introduce the motion and communication cost models that are used in the paper.…”

Section: Problem Setupmentioning

confidence: 99%

See 1 more Smart Citation

Co-Optimization of Communication and Motion Planning of a Robotic Operation under Resource Constraints and in Fading Environments

Yuan

Mostofi

2013

IEEE Trans. Wireless Commun.

Self Cite

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Abstract-We consider the scenario where a robot is tasked with sending a fixed number of given bits of information to a remote station, in a limited operation time, as it travels along a pre-defined trajectory, and while minimizing its motion and communication energy costs. We propose a co-optimization framework that allows the robot to plan its motion speed, transmission rate and stop time, based on its probabilistic prediction of the channel quality along the trajectory. We show that in order to save energy, the robot should move faster (slower) and send less (more) bits at the locations that have worse (better) predicted channel qualities. We furthermore prove that if the robot must stop, it should then stop only once and at the location with the best predicted channel quality. We also prove some properties for two special scenarios: the heavy-task load and the light-task load cases. We also propose an additional stop-time online adaptation strategy to further fine tune the stop location as the robot moves along its trajectory and measures the true value of the channel. Finally, our simulation results show that our proposed framework results in a considerable performance improvement.

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On the Spatial Predictability of Communication Channels

Cited by 145 publications

References 20 publications

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation

Robust Trajectory Planning for Robotic Communications Under Fading Channels

Co-Optimization of Communication and Motion Planning of a Robotic Operation under Resource Constraints and in Fading Environments

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