Iterative Multibeam Receiver for Co-Channel Interference Detection
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Solution Overview
Problem
Existing multibeam satellite systems face severe co-channel interference (CCI) due to aggressive frequency reuse, which is exacerbated by memory effects and limited by the accuracy of Channel State Information (CSI) and feeder-link bandwidth, leading to degraded performance and high complexity in CCI mitigation.
Innovation Solution
A receiver-based CCI mitigation technique that compensates for memory effects at the user terminal, employing a modular structure with a Soft-In-Soft-Out Iterative Divide-and-Conquer (IDAC) detector to jointly process desired and interfering signals, reducing computational complexity while effectively mitigating CCI.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If aggressive frequency reuse (reuse factor 1 or 2) is employed to increase spectral efficiency, then system capacity is improved, but co-channel interference severity increases
Solution Approach 1:
The patent converts the harmful CCI into a useful resource by using it as an input to the detector. The desired signal and interfering signals are jointly processed, where the interferer signals serve as known inputs that help resolve the desired signal, transforming the interference from a detrimental factor into a beneficial component for detection.
Solution Approach 2:
The patent segments the received signal into multiple components corresponding to different co-channel beams. By separating and independently processing each beam's contribution (desired signal and interferer signals) through separate detectors, the system manages interference complexity while maintaining high spectral efficiency.
2Measurement precision
If receiver-based CCI mitigation is implemented to overcome gateway limitations, then CCI compensation accuracy is improved, but receiver computational complexity increases
Solution Approach 1:
The receiver complexity is managed by segmenting the detection process into multiple independent detectors, each handling a specific co-channel beam. This modular approach allows accurate joint processing of desired and interferer signals while keeping individual detector complexity manageable.
Solution Approach 2:
The patent processes not only the desired signal but also the interferer signals through the detector. This excessive action of processing additional signals provides more information for accurate CCI compensation, achieving near-capacity performance despite the increased computational effort.
3Measurement precision
If memory effects in CCI are compensated for accurate detection, then detection accuracy is improved, but computational complexity increases exponentially
Solution Approach 1:
The patent segments the memory effects into manageable components by processing each co-channel beam separately. Each detector handles the memory effects of its specific interferer independently, avoiding the exponential complexity that would result from attempting to process all memory effects simultaneously across all interferers.
Solution Approach 2:
The system processes the interferer signals through the detector in addition to the desired signal. This partial processing of interferer memory effects provides sufficient accuracy for CCI compensation without requiring complete processing of all possible memory effects, thus avoiding exponential complexity growth.
Data Source
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AI summary
A communications apparatus to receive a composite signal including a desired signal and interferer signals, where the desired signal may include desired symbols and the interferer signals may include interferer symbols. The system may include N frameworks, each framework may include a detector to partition the desired symbols and the interferer symbols based on an interference severity into a dominant group and a non-dominant group, and to generate A Posteriori Probabilities (APP) of the desired symbols and the interferer symbols. The detector of each of the N frameworks generates the APP based on a feedback of a priori probabilities from each of the N frameworks.