Millimeter-Wave Beam Prediction Using Static and Mobile Object Locations
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Solution Overview
Problem
Millimeter-wave (mm-wave) communication systems face challenges with high path-loss and interference from mobile objects, leading to inefficient beam acquisition and potential interruptions in mm-wave communication due to the need for exhaustive beam searching and increased resource usage.
Innovation Solution
The method involves determining transmission paths between an access device and user equipment (UE) using a prediction function parameter, considering the location of the UE and mobile objects, to directly select suitable mm-wave beams, reducing beam acquisition time and minimizing overhead, and incorporating machine learning and ray tracing simulations for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If exhaustive beam searching is performed to acquire mm-wave beams, then beam acquisition reliability is improved, but beam acquisition time and system resource overhead increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-determining transmission paths using prediction function parameters before actual mm-wave communication occurs. The access device and UE use these parameters to predict suitable beams in advance, eliminating the need for exhaustive beam searching during actual communication setup, thus reducing beam acquisition time while maintaining reliability
Solution Approach 2:
The patent introduces prediction function parameters as an intermediary that mediates between the access device and UE for beam acquisition. These parameters enable both parties to independently determine suitable transmission paths and beams without performing exhaustive mutual beam searching, significantly reducing system resource overhead and acquisition time
2Reliability
If narrow beams are used to overcome high path-loss at mm-wave frequencies, then communication reliability is improved, but beam alignment precision requirements increase and system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-determining transmission paths using prediction function parameters before actual mm-wave communication occurs. The access device and UE use these parameters to predict suitable beams in advance, eliminating the need for exhaustive beam searching during actual communication setup, thus reducing beam acquisition time while maintaining reliability
Solution Approach 2:
The patent replaces the mechanical beam searching process with a prediction-based system. Instead of physically sweeping through multiple beam directions to find the optimal path, the system uses prediction function parameters to calculate and directly select suitable beams, substituting mechanical search with computational prediction to reduce complexity
3Device complexity
If mobile objects are not considered in beam selection, then system complexity is reduced, but communication reliability decreases due to potential interruptions by mobile objects
Solution Approach 1:
The patent applies preliminary action by incorporating mobile object information into the prediction function parameters in advance. The system pre-identifies potential blockages from mobile objects and adjusts beam selection accordingly, ensuring communication reliability without requiring real-time tracking or complex dynamic adjustments during communication
Solution Approach 2:
The patent introduces mobile object information as an intermediary factor in the prediction function. This information mediates between the access device and UE to select beams that avoid potential blockages, enabling reliable communication without requiring complex real-time interference management or exhaustive searching
Data Source
AI summary
Methods and apparatus are provided to realize mm-wave communication. In an embodiment, a network device inputs a user equipment (UE) location into a beam prediction engine to generate a set of mm-wave beams, and the beam prediction engine generating the set of mm-wave beams based on at least one static object within a coverage area of an access device. The network device inputs at least one mobile object location of at least one mobile object into the beam prediction engine to select a subset of mm-wave beams from the set of mm-wave beams, and the beam prediction engine selecting the subset of mm-wave beams based on the at least one static object and the at least one mobile object. The network device selects a mm-wave beam from the subset of mm-wave beams.