Location-Based Channel Estimation for Mobile mmWave User Equipment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The scarcity of available frequency band for wireless communications has led to the inclusion of millimeter Wave (mmWave) frequencies, which introduces challenges such as high path-loss and absorption-loss, and the large number of antennas in massive MIMO systems complicates channel estimation, especially in rapidly varying channels due to receiver movement.
Innovation Solution
A method involving a wireless communication node that generates a database of locations and channel parameter vectors, estimates channel parameter vectors using a position-to-channel mapping function, and compensates for distortions based on these vectors, with the function learned using an artificial neural network model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional linear channel estimation techniques are used, then the method is simple and computationally light, but the estimation accuracy deteriorates under rapid channel variations due to receiver mobility
Solution Approach 1:
The system pre-establishes a database mapping locations to channel parameter vectors before actual communication occurs. When a user device is located at a known position, the corresponding pre-stored channel parameters are retrieved and applied, eliminating the need for real-time complex estimation while maintaining high accuracy even under mobility conditions.
Solution Approach 2:
Instead of performing new channel estimation for each user device location, the system copies and reuses previously measured and stored channel parameter vectors from the database that correspond to the user's current location, thereby achieving accurate estimation without the computational complexity of conventional methods.
2Measurement precision
If more frequent channel estimation is performed to track rapid channel variations, then the estimation accuracy improves, but the computational overhead and time consumption increase
Solution Approach 1:
Channel parameters are measured and stored in advance at various locations before actual communication begins. During communication, the system simply queries the pre-built database based on the user's current location, eliminating the need for time-consuming real-time estimation while maintaining accurate tracking of channel variations.
Solution Approach 2:
The location-to-channel-parameter database acts as an intermediary that stores pre-measured channel characteristics. This intermediary structure allows the system to quickly retrieve appropriate channel parameters based on user location without performing complex real-time estimation, thereby reducing estimation time while maintaining accuracy.
3Measurement precision
If a database of location-channel parameter mappings is used, then the channel estimation accuracy in dynamic scenarios improves, but the database storage requirements and initial setup complexity increase
Solution Approach 1:
The system performs preliminary measurements of channel parameters at various locations and stores them in a database before actual communication occurs. This pre-computation approach shifts the complexity to an offline phase, allowing the online communication phase to simply query pre-stored data, thereby achieving high accuracy in dynamic scenarios while managing complexity through temporal separation.
Data Source
AI summary
Methods, apparatuses and systems for user equipment channel estimation, in accordance with some embodiments, includes: accessing a database storing a first plurality of locations, a first plurality of channels associated with respective ones of the first plurality of locations, and a first plurality of channel estimates associated with respective ones of the first plurality of channels; obtaining a second location of a first wireless communication device; determining a closest location from among the first plurality locations that has a closest distance to the second location; selecting a channel estimate from among the first plurality of channel estimates that corresponds to the closest location; determining a second channel estimate for the first wireless communication device based on the selected channel estimate; and adjusting at least one parameter of a signal transmitted between the first wireless communication node and the first wireless communication device based on the second channel estimate.