Gain-Adapt Reference Signaling for High-Order Modulation Reception
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Solution Overview
Problem
Current wireless communication systems face challenges in processing high order modulation signals due to limitations in signal-to-noise ratio (SNR) caused by analog-to-digital converter (ADC) noise floor, especially in fading channels.
Innovation Solution
A method is introduced where a device measures a gain adapt reference signal (GARS) and applies an upfade based on the signal metric of the GARS and the device's speed or Doppler estimation, to control the gain at the ADC and improve the processing of high order modulation signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high order modulation (e.g., 1024-QAM, 4096-QAM, 16384-QAM) is used to increase throughput, then data rate improves, but signal-to-noise ratio deteriorates due to ADC noise floor
Solution Approach 1:
The system performs preliminary channel quality assessment and Doppler estimation before transmitting high order modulation signals. Based on these preliminary measurements, the transmitter pre-adjusts modulation order and coding rate to ensure the signal can overcome ADC noise floor limitations, thereby maintaining both high throughput and acceptable SNR
Solution Approach 2:
The system dynamically adapts modulation order, coding rate, and transmit power based on real-time channel conditions and estimated Doppler shifts. This dynamic adjustment allows the system to optimize throughput while maintaining sufficient signal-to-noise ratio by selecting appropriate modulation levels that account for ADC quantization noise
2Measurement precision
If advanced iterative receiver is used to remove RF impairments, then modulation accuracy improves, but device complexity increases
Solution Approach 1:
The patent extracts and separately compensates for specific RF impairments (phase noise, IQ imbalance) before the main detection process. By isolating these impairments and applying targeted correction algorithms, the system achieves high modulation decoding accuracy without requiring a fully complex iterative receiver for all types of distortions
Solution Approach 2:
The system introduces intermediate processing stages that estimate and compensate for RF impairments before the signal enters the main demodulation and detection pipeline. These intermediary correction steps reduce the burden on the final detection algorithm, achieving high accuracy while managing overall receiver complexity
3Use of energy by moving object
If power amplifier operates at high efficiency point, then energy consumption improves, but linearity deteriorates causing signal distortion
Solution Approach 1:
The system intentionally operates the power amplifier in a non-linear high-efficiency region and then applies digital predistortion or post-processing to compensate for the resulting distortions. By converting the harmful non-linearity into a predictable distortion pattern that can be corrected digitally, the system achieves both high energy efficiency and acceptable signal quality
Solution Approach 2:
The system dynamically adjusts power amplifier operating parameters (bias voltage, supply voltage) based on signal conditions to optimize the efficiency-linearity tradeoff. During periods requiring high linearity, the PA operates at lower efficiency points; during constant throughput periods, it operates at high efficiency points with digital compensation
Data Source
AI summary
Aspects described herein relate to receiving an indication to measure a gain adapt reference signal, measuring, based at least in part on the indication, a signal metric of the gain adapt reference signal received from a network node, and applying, based at least in part on the signal metric of the gain adapt reference signal, an upfade for receiving a downlink signal from the network node. Other aspects relate to transmitting the indication and/or the gain adapt reference signal.