Channel Estimation Using Conjugate Gradient and Noise Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing channel estimation methods for digital video broadcasting, particularly in the China Terrestrial Television Broadcasting (CTTB) system, face issues such as long delay, high computational load, and storage requirements due to phase changes in the training sequence, making them inefficient and inapplicable in practical scenarios.
Innovation Solution
A channel estimation method using a time-domain training sequence that acquires an initial channel vector, calculates an algorithm initial vector, and performs channel estimation using a conjugate gradient method based on a preprocessing matrix, followed by noise reduction processing to achieve shorter delay and lower calculation complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If MMSE based estimation method is used, then channel estimation accuracy is improved, but on-line computational load becomes heavy and delay is unacceptable
Solution Approach 1:
The patent changes the estimation criterion from MMSE to LS (least square), which has lower computational complexity. By adjusting the parameter (estimation method) to LS, the system achieves acceptable accuracy while dramatically reducing on-line computational load and delay.
Solution Approach 2:
The patent extracts the channel estimation process from the feedback loop by using training sequences transmitted in advance. This allows the system to obtain channel information without waiting for decoding feedback, thereby reducing delay and computational requirements while maintaining estimation accuracy.
2Device complexity
If LS method with training matrix storage is used, then channel estimation is simplified, but storage requirement becomes very large
Solution Approach 1:
The patent extracts the channel estimation computation from requiring large stored training matrices. Instead of storing complete training matrices for all modes, the system uses compressed training sequences and computes channel information on-demand, dramatically reducing storage requirements while maintaining estimation capability.
3Adaptability or versatility
If CTTB training sequence is used, then system compatibility is improved, but correlative characteristic becomes weak leading to performance deterioration
Solution Approach 1:
The patent uses feedback from channel estimation results to adaptively adjust processing parameters. By continuously monitoring estimation quality and adjusting the conjugate gradient iterations and threshold values accordingly, the system compensates for the weak correlative characteristics of CTTB training sequences while maintaining compatibility.
Data Source
AI summary
A channel estimation method and a channel estimation system based on time-domain training sequence are provided. The channel estimation system first acquires an initial channel vector used for channel estimation of a current frame, and calculates an algorithm initial vector based on a training sequence vector contained in a received receiving signal vector and the receiving signal vector, then performs estimation based on the initial channel vector and the algorithm initial vector and using a conjugate gradient method based on a preprocessing matrix to acquire each channel estimation value, and eventually perform noise reduction processing on each channel estimation value based on a first predetermined threshold value to acquire a final channel estimation value. Compared with the existing channel estimation methods, the present invention has a shorter delay and lower calculation complexity, and thus can be easily implemented.