Noise Estimation Using Unmasked Control Messages
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Solution Overview
Problem
Existing noise level estimation methods in CDMA communication systems, such as HSDPA, face challenges in accurately estimating noise levels for data channels using control channels, especially when control messages are not addressed to the communication terminal, leading to reduced accuracy and limited noise measurement capabilities.
Innovation Solution
A method and apparatus in a mobile communication terminal that decodes and validates control-channel messages not addressed to it, using terminal-specific codes and error detection codes, to estimate noise levels for data channels, allowing for noise level estimation even when messages are not intended for the terminal, thereby improving accuracy and expanding measurement capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If control-channel messages not addressed to the terminal are decoded and used for noise estimation, then noise measurement accuracy is improved, but device complexity increases due to additional decoding and validation operations
Solution Approach 1:
The terminal's control channel decoder is enhanced to perform dual functionality: decoding control messages addressed to the terminal (original function) and decoding control messages addressed to other terminals (new function for noise estimation). This multi-functionality allows the same hardware/software resources to serve multiple purposes, improving noise measurement accuracy without proportionally increasing device complexity.
Solution Approach 2:
The terminal uses its own existing decoding capabilities and processing resources to perform noise estimation on other terminals' control messages. Instead of requiring separate dedicated hardware for noise measurement, the system leverages its self-existing decoder infrastructure, thereby improving measurement accuracy while minimizing additional complexity.
2Measurement precision
If control messages are decoded regardless of addressing, then noise level estimation capability is improved, but loss of information increases due to processing irrelevant messages
Solution Approach 1:
The system extracts only the necessary information from control messages for noise estimation purposes. By focusing specifically on extracting noise characteristics from the decoded control messages rather than processing the entire message content, the terminal improves noise estimation capability while minimizing the processing of irrelevant information.
Solution Approach 2:
The patent introduces an intermediary validation mechanism that checks whether decoded control messages contain valid noise estimation data. This intermediary step filters out irrelevant or corrupted messages before they are used for noise estimation, thereby improving measurement precision while preventing loss of information from processing invalid data.
3Reliability
If terminal-specific code masking is applied to control-channel messages, then reliability of message identification is improved, but difficulty of detecting and measuring increases due to additional unmasking operations
Solution Approach 1:
The terminal performs preliminary unmasking operations on control-channel messages using terminal-specific codes before attempting to decode and analyze them for noise estimation. By applying this preliminary action early in the processing chain, the system maintains reliable message identification while preparing the messages for subsequent noise measurement operations.
Data Source
AI summary
A method in a communication terminal includes receiving a signal that carries a data channel and at least a control-channel message, which has a first part that is masked with a terminal-specific code. A second part of the control-channel message that is not masked with the terminal-specific code is decoded to produce a decoded second part. The validity of decoded second part is checked. In response to deciding that the decoded second part is valid, a noise level for the data channel is estimated based on the decoded second part.