In-band Full Duplex Self-Interference Cancellation via Segmented Training
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Solution Overview
Problem
In-band full-duplex (IFD) transmission systems face challenges in canceling strong self-interference signals, which complicates the implementation of Self-Interference Cancellation (SIC) technology, especially in multiple-input multiple-output (MIMO) systems, and requires effective automatic gain control (AGC) to manage signal strength at the analog-to-digital converter (ADC) to prevent saturation and maintain signal-to-noise ratio (SNR).
Innovation Solution
The method involves a training sequence-based approach where a slave node and a master node communicate to calculate and adjust filter factors for canceling self-interference signals, with AGC sequences used to match the strength of desired and self-interference signals, ensuring the gain of data signals is adjusted within the ADC's dynamic range, facilitating effective demodulation in IFD systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If self-interference cancellation technology is applied in IFD systems, then the ability to cancel strong self-interference signals is improved, but the implementation complexity of the transceiver increases
Solution Approach 1:
The self-interference cancellation process is segmented into three distinct stages: RF/analog stage cancellation, ADC stage cancellation, and digital baseband cancellation. Each stage handles specific types of interference signals with appropriate processing methods, dividing the complex cancellation task into manageable segments that can be implemented independently at different points in the signal chain.
Solution Approach 2:
Training sequences are introduced as intermediary signals to facilitate the self-interference cancellation process. These known sequences are transmitted and received to estimate the self-interference channel characteristics, which then serve as intermediaries for calculating cancellation filters. This intermediary approach enables accurate cancellation without requiring direct knowledge of the transmitted signal at the receiver.
2Manufacturing precision
If signal gain is increased to improve ADC input range, then the dynamic range utilization is improved, but the signal-to-noise ratio of the desired signal deteriorates
Solution Approach 1:
The system dynamically changes the gain parameter of the variable gain amplifier based on the estimated strength of self-interference signals. By adjusting the gain parameter adaptively, the system optimizes the input signal level to the ADC to prevent saturation while maintaining adequate signal-to-noise ratio for desired signal detection.
Solution Approach 2:
The system performs preliminary estimation of self-interference signal strength using training sequences before the actual data transmission. This preliminary action allows the system to pre-adjust the gain settings and cancellation filter parameters, ensuring optimal performance during subsequent data transmission without requiring real-time adjustments that could affect SNR.
3Reliability
If multiple cancellation stages are implemented, then the completeness of self-interference cancellation is improved, but the processing time and system complexity increase
Solution Approach 1:
The cancellation process is segmented across different time domains and processing stages. RF/analog cancellation operates continuously on strong interference, ADC cancellation processes sampled signals at moderate rates, and digital baseband cancellation handles residual interference. This temporal and functional segmentation allows parallel processing where possible and prioritizes critical cancellation stages to minimize overall processing time.
Solution Approach 2:
The system implements cancellation with varying degrees of precision at different stages. The RF/analog stage performs coarse cancellation of strong interference, the ADC stage provides moderate precision cancellation, and the digital baseband stage delivers fine-tuned residual cancellation. This graduated approach achieves sufficient cancellation completeness without applying maximum processing effort uniformly across all stages, thereby reducing overall processing time.
Data Source
AI summary
An operating method of a slave node that communicates with a master node in an in-band full duplex (IFD) system may comprise receiving a beacon signal from the master node during a training sequence period; transmitting a first self-interference (SI) training sequence including a first radio frequency (RF)/analog SI training sequence, a first automatic gain control (AGC) sequence, and a first digital SI training sequence to the master node during the training sequence period after the beacon signal is received; calculating a filter factor for canceling an analog SI signal input to the slave node on the basis of the first RF/analog SI training sequence; and canceling the analog SI signal from the first AGC sequence on the basis of the filter factor.