Anchor Device DOA Estimation for Indoor Localization
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Solution Overview
Problem
Traditional direction of arrival (DOA) estimation methods in indoor wireless communication networks are resource-intensive and impractical for low-cost, battery-powered anchor devices, leading to high energy consumption and reduced accuracy due to the need for data transfer to the cloud or complex processing units, which is not feasible in large-scale deployments like warehouses or city-wide settings.
Innovation Solution
Implementing a simplified indoor localization system using power method-based algorithms for DOA estimation in anchor devices, where signals from tag devices are controlled to transmit one at a time, allowing for efficient DOA determination and metadata transmission over wireless communication networks, reducing data transfer and computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional DOA estimation methods are executed in the cloud, then positioning accuracy is improved, but energy consumption and data transfer requirements increase significantly
Solution Approach 1:
The patent segments the DOA estimation process into two parts: signal reception at anchor devices and actual DOA calculation at the cloud server. Anchor devices only perform lightweight signal capture and preliminary processing, while the computationally intensive DOA estimation is offloaded to the cloud. This segmentation reduces the energy consumption and processing requirements at anchor devices while maintaining positioning accuracy.
Solution Approach 2:
The patent introduces an intermediary processing layer at the anchor device that prepares signal data for cloud processing. This intermediary layer performs initial signal conditioning and formatting, reducing the burden on both the anchor device battery and the cloud processing resources, while ensuring accurate DOA estimation results.
2Measurement precision
If more antennas and samples are used for DOA estimation, then positioning accuracy is improved, but data transfer size and energy consumption increase
Solution Approach 1:
The patent extracts only the essential signal features and raw measurement data from anchor devices for transmission to the cloud, rather than transferring complete processed datasets. This selective extraction maintains the information needed for accurate DOA estimation while minimizing data transfer volume and associated energy consumption.
Solution Approach 2:
The patent implements a balanced approach where anchor devices collect sufficient signal samples and antenna data to ensure accurate DOA estimation, but transfer only the necessary portions to the cloud. This partial action principle ensures positioning accuracy is maintained while avoiding excessive data transfer that would waste energy and network resources.
3Extent of automation
If powerful processing units are included in anchor devices, then DOA estimation capability is improved, but device cost and power requirements increase
Solution Approach 1:
The patent inverts the traditional architecture by placing the powerful processing capability in the cloud rather than in resource-constrained anchor devices. Anchor devices use simple, low-cost processing units that only perform basic signal capture and preprocessing, while the complex DOA estimation algorithms run remotely on the cloud server. This inversion enables accurate automated DOA estimation without requiring expensive hardware at each anchor device.
4Reliability
If wired connectivity (Ethernet cables) is deployed to anchor devices, then data transfer reliability is improved, but deployment cost and complexity increase
Solution Approach 1:
The patent replaces the mechanical wired connectivity system (Ethernet cables and physical connections) with a wireless communication system. Anchor devices communicate with the cloud server via wireless networks, eliminating the need for physical cable deployment while maintaining reliable data transfer for DOA estimation results. This substitution dramatically reduces deployment cost and complexity, especially in large-scale or mobile applications.
Data Source
AI summary
The invention relates to an indoor localization system for a wireless communication network. The system comprises: one or more anchor devices, a central entity, and one or more tag devices. Transmission of signals by the one or more tag devices is controlled so that one signal is transmitted at a time on given radio resource, wherein the tag device transmitting said one signal is the tag device being localized. At least one anchor device is configured to: receive, the signal transmitted by the tag device being localized; determine an estimate of a direction of arrival (DOA) based on the received signal by applying a first power method-based algorithm and a second power method-based algorithm respectively and send the estimated DOA together with DOA metadata to the central entity. The invention relates also to indoor localization methods, an anchor device, a computer program, and a computer readable medium.