Channel Impulse Response Estimation Using Toeplitz Levinson Processing
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Solution Overview
Problem
High data rate digital wireless communication systems face limitations due to frequency-selective fading and multipath effects, which cause intersymbol interference, leading to reduced data throughput and increased error rates, and existing channel impulse response estimation methods are constrained by speed and accuracy, particularly in rapidly changing environments.
Innovation Solution
A method and system for channel impulse response estimation using a pseudonoise (PN) sequence and training sequence to form a Toeplitz-type representation, enabling the use of fast algorithms like Levinson algorithms for determining coefficients representative of the channel impulse response, allowing for rapid and accurate estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional Mean Square Error algorithm is used to calculate filter coefficients, then accuracy of channel impulse response estimation is improved, but calculation time increases and speed decreases
Solution Approach 1:
The patent transforms the original Mean Square Error algorithm into a Toeplitz-form algorithm by changing the mathematical parameters and structure of the calculation. This parameter transformation maintains the accuracy of channel impulse response estimation while enabling the use of faster Levinson recursion algorithms, thus resolving the contradiction between accuracy and calculation speed.
Solution Approach 2:
The patent replaces the traditional iterative Mean Square Error calculation mechanism with a direct Toeplitz system solution using Levinson recursion. This substitution of calculation mechanism eliminates the need for iterative convergence, providing both the accuracy of traditional methods and the speed of direct solutions.
2Adaptability or versatility
If channel impulse response estimation is updated frequently to accommodate high data rates, then adaptability to rapidly changing channels is improved, but calculation time becomes a limiting factor
Solution Approach 1:
By transforming the calculation parameters into Toeplitz form, the patent enables much faster coefficient updates that can keep pace with rapidly changing channel conditions at high data rates, thus improving adaptability without suffering from time loss.
Solution Approach 2:
The patent prepares the calculation in advance by formulating the problem as a Toeplitz system that can be solved efficiently using Levinson recursion. This preliminary structural preparation allows for rapid updates when channel conditions change, reducing the time penalty associated with frequent estimations.
3Measurement precision
If training sequence is transmitted to excite all frequencies in data bandwidth, then measurement precision of channel response is improved, but transmission time and bandwidth usage increase
Solution Approach 1:
The patent changes the mathematical parameters of the estimation process by using Toeplitz-form formulation with Levinson recursion. This allows accurate channel response measurement across all frequencies to be achieved more efficiently, reducing the time required for training sequence transmission while maintaining measurement precision.
Data Source
AI summary
Channel impulse response estimation employs a training sequence to enable correction for multipath and other disturbances affecting a signal during transmission via a digital wireless communication channel. High-speed packet transmission rates, with a training sequence for each packet, are made possible by training sequence construction enabling fast algorithm processing of received signals for impulse response estimation. Upon reception, a Toeplitz-type mathematical representation is constructed based on transmitted and received versions of a training sequence. The Toeplitz-type representation may then be processed by application of fast algorithms, such as Levinson-type algorithms, to determine coefficients representative of the communication channel impulse response. These coefficients, applied to an adaptive equalizer type of filter, enable correction for signal disturbances incurred in transmission. Channel impulse response estimation methods and systems are described.