Two-Step Least Squares Channel Estimation for OFDM

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Solution Overview

Problem

Conventional OFDM receivers face challenges in accurately estimating channel characteristics, particularly in mobile environments with time-varying channels and multiple antennas, which affects signal quality and throughput due to the complexity of existing channel estimation methods.

Innovation Solution

The implementation of a least squares channel estimation (LS-CE) method that generates an initial channel estimate through cross-correlation between a locally generated reference signal and the received signal, with successive corrections to minimize mean square error, allowing for robust and computationally efficient time-domain channel estimation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional channel estimation methods are used in mobile environments with time-varying channels, then measurement precision may be maintained, but device complexity increases significantly

Engineering Contradiction:
Improvechannel estimation accuracyVSAvoidchannel estimation complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The channel estimation process is segmented into two distinct stages: first, an initial channel estimate is obtained using correlation techniques; second, this initial estimate is refined through iterative optimization. This segmentation allows the complex estimation problem to be broken into manageable parts, reducing overall computational complexity while maintaining accuracy in time-varying channels.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary channel estimation using correlation between the received signal and known reference signals before applying more complex processing. This preliminary action provides a good initial estimate that reduces the computational burden of subsequent refinement steps, effectively lowering device complexity while preserving measurement precision.

Inventive Principle:
Principle #10Preliminary action

2Measurement precision

If complex channel estimation algorithms are implemented to handle multi-antenna scenarios, then measurement precision improves, but productivity decreases due to increased processing requirements

Engineering Contradiction:
Improvechannel estimation accuracyVSAvoidsignal processing throughput
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The estimation algorithm is divided into sequential stages: initial correlation-based estimation followed by iterative refinement only when necessary. This segmentation ensures that most processing is completed efficiently in the first stage, maintaining high productivity while achieving the measurement precision needed for multi-antenna scenarios through selective application of more computationally intensive operations.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies refinement iterations selectively based on channel conditions and performance requirements rather than always applying full complex algorithms. This partial action approach maintains productivity by avoiding unnecessary computational overhead while still achieving sufficient measurement precision for multi-antenna operations when conditions warrant it.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentEP2852073B1Two-steps least squares time domain channel estimation for OFDM systems
Publication Date: 2017.05.31 ACORN TECHNOLOGIES INC
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AI summary

An OFDM system generates a channel estimate in the time domain for use in either a frequency domain equalizer or in a time domain equalizer. Preferably channel estimation is accomplished in the time domain using a locally generated reference signal. The channel estimator generates an initial estimate from a cross correlation between the time domain reference signal and an input signal input to the receiver and generates at least one successive channel estimate. Preferably the successive channel estimate is determined by vector addition (or subtraction) to the initial channel estimate. The at least one successive channel estimate reduces the minimum mean square error of the estimate with respect to a received signal.