Computational Antenna Sensing for Base Station Beam Localization
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Solution Overview
Problem
Existing wireless network systems face challenges in efficiently localizing telecommunication targets, such as gNodeB base stations, due to high-frequency signal obstruction and the complexity of mechanically-moved antennas, leading to inefficiencies in beam steering and increased power consumption.
Innovation Solution
Utilizing a wireless network repeater with holographic beamforming antennas and computational imaging to determine the location of telecommunication targets, employing a localization subsystem that generates holographic states and calculates a pseudo-inverse of a sensing matrix to identify the target's location, reducing the need for redundant measurements and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If mechanically-moved antennas are used for beam steering, then directional communication is achieved, but device complexity and power consumption increase
Solution Approach 1:
The patent replaces mechanically-moved antennas with electronically-controlled phased array antennas that use phase shifters and signal processing to achieve beam steering. This substitutes mechanical movement with electronic control, eliminating moving parts while maintaining directional communication capability.
Solution Approach 2:
The patent implements dynamic beam steering through electronic phase control where beam direction can be changed rapidly by adjusting phase shifter settings without physical movement. This allows the antenna system to adapt beam direction dynamically through electronic means rather than mechanical repositioning.
2Measurement precision
If raster-scan methods are used for target localization, then comprehensive coverage is achieved, but scanning time and power consumption increase
Solution Approach 1:
The patent uses compressive sensing to achieve accurate target localization with fewer measurements than traditional raster-scan methods. Instead of scanning all possible directions exhaustively, the system acquires a reduced set of measurements that are sufficient to reconstruct the target location through computational algorithms.
Solution Approach 2:
The patent employs preliminary computational processing where a sensing matrix is constructed and compressed sensing algorithms are applied to the acquired measurements before final target localization. This preliminary computational action enables accurate localization from incomplete measurement data, reducing the need for exhaustive scanning.
3Power
If high-frequency signals are used for communication, then bandwidth and data rate improve, but signal obstruction and localization difficulty increase
Solution Approach 1:
The patent uses computational sensing algorithms as an intermediary between the received high-frequency signals and target localization. The sensing matrix and compressed sensing reconstruction act as computational intermediaries that process the signals to overcome obstruction effects and extract accurate location information despite challenges inherent to high-frequency propagation.
Data Source
AI summary
A device may include an antenna subsystem to support image sensing and wireless network communications. A device may include a localization subsystem to determine a location of a wireless base station within a defined region via computational imaging of the region using an image-sensing antenna of the antenna subsystem operating at a sensing frequency within the operational frequency band of the wireless base station. A device may include a communication subsystem to adjust a steering angle of a communication antenna based on the location of the wireless base station as determined by the localization subsystem.