Additive Decision Feedback Equalization for High Mobility Wireless
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Solution Overview
Problem
High mobility scenarios in wireless communication devices, such as cellular vehicle-to-everything (C-V2X) scenarios, experience significant channel estimation errors due to high Doppler spread, leading to errors like inter-symbol interference and high block error rates, even with added reference symbols and high modulation and coding schemes.
Innovation Solution
The implementation of additive decision feedback equalization (DFE) in coherent single-carrier frequency-division multiple access (SC-FDMA) systems, which includes initializing feedback with zeros in the length of delay spread or cyclic prefix, and adaptive procedures like normalized least mean squares (NLMS) to adapt coefficients, activated based on Doppler spread thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high modulation and coding schemes are used in high mobility scenarios, then data transmission rate is improved, but block error rate increases to 100%
Solution Approach 1:
The system performs preliminary channel estimation using reference symbols before data transmission, and pre-adapts equalization coefficients based on initial channel conditions. This preliminary action prepares the receiver to handle high mobility effects, enabling high-order modulation while maintaining acceptable error rates through proactive compensation for expected channel variations.
Solution Approach 2:
The system implements adaptive equalization where channel estimates from received signals are fed back to continuously update equalization coefficients. This feedback mechanism allows the system to track rapid channel changes in high mobility scenarios, correcting distortions in real-time and maintaining reliable data transmission even with high modulation schemes.
2Measurement precision
If reference symbols are added to improve channel estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system uses a limited number of reference symbols (excessive enough to provide sufficient channel estimation accuracy, but not so many as to cause excessive overhead). This partial action approach finds the optimal balance where adequate channel information is obtained without unnecessarily increasing system complexity or reducing data transmission efficiency.
Solution Approach 2:
The system uses the received reference symbols to automatically estimate channel conditions and adapt equalization parameters without requiring external calibration or manual configuration. This self-service capability allows the system to maintain accurate channel estimation in high mobility scenarios while keeping the implementation relatively simple and autonomous.
Data Source
AI summary
A wireless communication device is described. The wireless communication device includes a receiver. The receiver is configured to determine a time-domain sample of a single carrier based on a received signal. The receiver is also configured to determine an estimated value based on the time-domain sample. The receiver is further configured to perform slicing based on the estimated value to produce a sliced value. The receiver is additionally configured to adapt a frequency-domain coefficient based on the estimated value and the sliced value. The receiver is also configured to perform channel equalization based on the frequency-domain coefficient.