Dynamic AP Partitioning for Indoor GNSS Geolocation
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Solution Overview
Problem
The computational complexity of geolocating a large number of network devices in indoor environments grows exponentially, leading to significant processing time and resource requirements, making existing solutions impractical for large-scale implementations.
Innovation Solution
The approach involves partitioning network devices into smaller batches and determining their geolocation on a batch-by-batch basis using a combination of GNSS pseudorange measurements and inter-network device ranging measurements, with anchor devices and iterative processes to enhance accuracy and manage complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If centralized optimization methods are used to geolocate network devices, then measurement precision is improved, but device complexity and processing time increase exponentially
Solution Approach 1:
The patent divides the network devices into multiple batches or groups, processing each batch separately rather than solving a single large optimization problem. This segmentation reduces the computational complexity from exponential O(e^n) to manageable levels by breaking the problem into smaller sub-problems that can be solved independently and then combined.
Solution Approach 2:
The patent extracts and identifies anchor devices with known locations from the overall network device set. These anchor devices are removed from the optimization problem and used as reference points, simplifying the computational burden by reducing the number of unknown variables that need to be solved simultaneously.
2Area of stationary object
If the number of network devices increases, then coverage area is improved, but processing time increases exponentially
Solution Approach 1:
By segmenting the network devices into batches based on their spatial distribution and connectivity, the patent enables parallel processing of multiple device groups. This allows the system to handle larger coverage areas with more devices without proportionally increasing processing time, as smaller batches can be processed more efficiently and potentially in parallel.
Solution Approach 2:
The patent performs preliminary identification and classification of devices into batches before the actual geolocation computation. Anchor devices are identified and extracted in advance, and measurement data is pre-processed and organized by batch. This preliminary action reduces the computational burden during the actual optimization phase, enabling faster processing as the network scale increases.
3Productivity
If more network devices are geolocated simultaneously, then productivity is improved, but use of energy and computational resources increases exponentially
Solution Approach 1:
The patent segments the geolocation task into multiple smaller batch processing operations. Instead of computing geolocation for all devices simultaneously in a single energy-intensive optimization run, the system processes devices in manageable batches, reducing peak energy consumption and computational resource requirements while maintaining overall productivity through systematic batch processing.
Solution Approach 2:
By extracting anchor devices with known locations from the optimization problem, the patent reduces the number of variables that require computational energy. This extraction simplifies the optimization problem for remaining devices, lowering the energy cost per device while maintaining the ability to gelocate large numbers of devices through iterative batch processing.
Data Source
AI summary
Described herein are devices, systems, methods, and processes for managing the computational complexity in geolocating a large number of network devices (e.g., access points (APs)) in indoor environments. A number of network devices may be partitioned into smaller groups or batches based on neighbor knowledge about the network devices. Each batch of network devices can include just devices located on a same floor, or may include devices located across different floors. Every batch may include at least one anchor network device. The geolocation of the network devices can be determined, batch-by-batch, based on fusing global navigation satellite system (GNSS) pseudorange measurements and inter-network device ranging measurements. The geolocation accuracy for each partition can be evaluated utilizing such metrics as the average residual error. If the error for a batch is greater than a threshold, remedial measures may be taken to reduce the error and improve the geolocation accuracy.