Carrier Frequency Offset Estimation Using Artificial Shifting
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Solution Overview
Problem
Existing methods for estimating carrier frequency offset (CFO) in RF multicarrier signals are inaccurate, especially under noisy conditions and when IQ imbalance is present, leading to performance degradation in multi-user systems like 4G cellular wireless systems.
Innovation Solution
A method that uses a preamble with multiple sets of training symbols, where a predetermined artificial CFO is introduced to shift the CFO to a range where the estimation method has higher precision, and combines CFO estimates using a direct algebraic relationship to cancel out IQ imbalance and account for noise, improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a standard CFO estimation method is used without artificial CFO shifting, then the estimation process is simple, but the estimation accuracy deteriorates under noisy conditions and with IQ imbalance
Solution Approach 1:
The patent applies preliminary action by introducing an artificial CFO offset before the estimation process. The transmitter pre-shifts the CFO by adding a known artificial offset to the training symbols. This preliminary modification ensures that the received signal falls within the optimal precision range of the estimation algorithm, thereby improving estimation accuracy before the actual measurement occurs.
Solution Approach 2:
The patent changes the CFO parameter by introducing an artificial offset. The transmitter modifies the CFO parameter of training symbols by adding a predetermined artificial CFO, which shifts the total CFO into a range where the estimation method achieves higher precision. This parameter transformation allows the estimation algorithm to operate in its optimal performance range.
2Measurement precision
If multiple CFO estimates are combined to improve accuracy, then the estimation precision improves, but the computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the CFO estimation into multiple independent stages. Each training symbol set undergoes separate CFO estimation, producing multiple individual estimates. These segmented estimates are then combined through algebraic relationships to achieve higher overall precision, allowing the system to benefit from multiple measurements without requiring a single complex estimation algorithm.
3Measurement precision
If a long preamble sequence is used to average out noise, then the CFO estimation accuracy at low SNR improves, but the overhead increases
Solution Approach 1:
The patent changes the effective CFO parameter through artificial shifting, which transforms the estimation problem into a regime where the existing estimation algorithm operates with higher precision. This parameter transformation allows accurate CFO estimation without requiring excessively long preamble sequences, thereby reducing overhead while maintaining accuracy at low SNR conditions.
Solution Approach 2:
The patent replaces the mechanical approach of using long preambles for noise averaging with a mathematical approach. Instead of extending the preamble duration to improve SNR through averaging, the system uses algebraic relationships and artificial CFO shifting to achieve accurate estimation with shorter preambles, substituting computational methods for physical signal extension.
4Measurement precision
If IQ imbalance is not taken into account in CFO estimation, then the estimation method is simpler, but the accuracy deteriorates at higher SNRs
Solution Approach 1:
The patent extracts and compensates for the IQ imbalance effect separately from the CFO estimation process. By introducing artificial CFO and using algebraic relationships that account for IQ imbalance characteristics, the method isolates and removes the distorting effect of IQ imbalance from the CFO measurement, allowing accurate CFO estimation even when IQ imbalance is present in the receiver.
Data Source
AI summary
One inventive aspect relates to a method of estimating carrier frequency offset introduced on an RF multicarrier signal received via a transmission channel on a direct downconversion analog receiver. The method comprises generating a preamble comprising at least one set of training symbols. The method further comprises transmitting the preamble to the receiver. The method further comprises determining a carrier frequency offset estimate from the received preamble by an estimation method which has a higher precision for a first range of carrier frequency offset values and a lower precision for a second range of carrier frequency offset values. The method further comprises introducing a predetermined artificial carrier frequency offset on at least one set of training symbols, the predetermined artificial carrier frequency offset being chosen for shifting the carrier frequency offset of that set of training symbols to the first range.