MIMO-OFDM Equalizer Coefficients With Recursive Channel Estimation
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Solution Overview
Problem
In MIMO wireless communication systems, existing channel estimation methods are computationally intensive and increase processing latency due to the need for high-order calculations, making it challenging to quickly generate the channel estimation matrix H, which is essential for effective equalization.
Innovation Solution
A recursive channel estimation method is employed in the receiver module, allowing for the estimation of matrix H as training fields are received, reducing the computational density from O(n^3) to O(n^2) and enabling faster generation of the channel estimation matrix H for channel equalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional channel estimation methods are used to generate matrix H, then measurement precision is improved, but processing time increases and productivity decreases
Solution Approach 1:
The patent applies preliminary action by performing QR decomposition on the preamble steering matrix P beforehand to obtain its inverse (P^-1). This pre-computed inverse is then reused during channel estimation to avoid repeated high-order calculations. The equalizer coefficients are computed as H_est = R^-1 * Q' * P^-1, where P^-1 is already available from preliminary processing, significantly reducing the computational burden during actual channel estimation while maintaining accuracy.
2Measurement precision
If traditional channel estimation methods are used to generate matrix H, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent reduces device complexity by performing the computationally intensive QR decomposition of the preamble steering matrix P in advance, before the actual channel estimation process. The pre-computed P^-1 is stored and reused, transforming O(n^3) operations into O(n^2) operations during runtime. This shifts the computational burden to an offline setup phase, reducing the hardware requirements and processing complexity of the main equalization module.
3Productivity
If recursive channel estimation is used to reduce processing time, then productivity is improved, but measurement precision may deteriorate
Solution Approach 1:
The patent maintains measurement precision while improving productivity by pre-computing the inverse of the preamble steering matrix P using QR decomposition. This preliminary action provides an accurate baseline (P^-1) that is then combined with the received training symbols through efficient matrix operations. The recursive update formula H_est = R^-1 * Q' * P^-1 leverages this pre-computed inverse to achieve fast yet accurate channel estimation without sacrificing precision.
Data Source
AI summary
A method of operating a multiple-input multiple-output (MIMO) receiver includes wirelessly receiving a message over a communication channel using a plurality of antennas. The message includes first data preceded by a plurality of training fields. The method includes generating a first matrix indicative of an estimation of properties of the communication channel, and determining a second matrix and a third matrix by performing a matrix decomposition of the first matrix. The method includes, as each of the plurality of training fields of the message is being received, recursively computing parameters for equalization based on (i) the plurality of training fields, (ii) the second matrix, and (iii) the third matrix. The method includes generating equalizer coefficients based on the parameters for equalization, and applying the equalizer coefficients to the first data of the message to compensate the first data.