Receiver Channel Estimation via Power Control Pattern Matching
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Solution Overview
Problem
Current channel estimation in wireless communication systems, such as WCDMA and LTE, is affected by noise, making it challenging to predict data transmission speed and network capacity due to varying channel conditions.
Innovation Solution
A receiver system that processes power control commands or phase estimation to determine the type of channel, adjusts filtering parameters, and enhances channel estimation by changing averaging periods, tap spacing, or frequency tones based on the channel type, thereby improving noise reduction and tracking channel changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional channel estimation methods are used, then the estimation process is simple, but the estimation accuracy is poor due to noise affecting both data and pilot portions
Solution Approach 1:
The system dynamically adapts the filtering parameters based on detected channel types. Different channel types (e.g., Rayleigh, Rician) have different statistical characteristics, and the filtering approach is adjusted accordingly to optimize estimation accuracy for each channel condition while maintaining robustness against noise
Solution Approach 2:
The invention changes filtering parameters such as averaging period, number of taps, and tap spacing based on the detected channel type. By modifying these parameters dynamically, the system optimizes the trade-off between noise reduction and channel variation tracking for different channel conditions
2Object-affected harmful factors
If the averaging period is increased to reduce noise, then noise reduction improves, but the system's ability to track rapid channel changes deteriorates
Solution Approach 1:
The system dynamically adjusts the averaging period based on the detected channel type and current channel conditions. For slow-varying channels, a longer averaging period is used to maximize noise reduction, while for fast-varying channels, the averaging period is reduced to maintain tracking capability
Solution Approach 2:
The invention modifies the averaging period parameter adaptively according to channel characteristics. This parameter change allows the system to optimize the balance between noise filtering and tracking speed for different channel scenarios
3Measurement precision
If filtering parameters are optimized for one channel type, then estimation accuracy improves for that channel type, but performance deteriorates for other channel types
Solution Approach 1:
The system segments the channel estimation process by detecting and identifying different channel types (e.g., Rayleigh, Rician, selective fading). Each channel type is then processed with specialized filtering parameters optimized for its characteristics, allowing high accuracy for each specific channel type while maintaining overall versatility
Solution Approach 2:
The invention applies different filtering qualities and parameters locally tailored to each detected channel type. Instead of using a uniform filtering approach, the system customizes the estimation process according to the specific characteristics of each channel type, achieving optimal performance for diverse channel conditions
Data Source
AI summary
Disclosed is a receiver for enhancing estimation of a channel of a received signal. The receiver is being configured to (i) process at least one of (a) power control commands to obtain a pattern of processed power control commands or (b) phase estimation to obtain a pattern of processed phase estimation; (ii) match the pattern of at least one of (a) processed power control commands, or (b) processed phase estimation to a pattern corresponding to one or more channels; (iii) determine a type of channel of the one or more channels based on the matched pattern of at least one of (a) said processed power control commands, or (b) said processed phase estimation, (iv) determine filtering parameters based on a type of channel that is determined and (v) enhance estimation of the channel based on the filtering parameters associated with the type of channel that is determined.