Soft Symbol Decision Interference Cancellation
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Solution Overview
Problem
Existing communication systems face interference challenges, particularly in extracting interference components with power levels similar to or lower than the Signal Of Interest (SOI), leading to a 'deadzone' where interference cannot be effectively excised.
Innovation Solution
The implementation of a soft symbol decision approach within an interference cancellation device, which generates soft values to cancel interfering signals by determining differences between actual and possible symbol values using a noise level estimate, and computes probabilistic averages to improve interference removal efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If hard symbol decoding is used to generate hard symbol values, then computational complexity is reduced, but interference cancellation performance deteriorates due to inability to capture probabilistic information
Solution Approach 1:
The patent changes the parameter from hard symbol values to soft symbol values by introducing probabilistic information. The soft symbol values are computed using the formula: soft_value = sum(probability_metric * possible_symbol_value) for all possible symbol values, where probability_metric = exp((−|yj−xj|2)/2σ2). This parameter change enables the system to capture probabilistic information about interference symbols, improving cancellation performance while maintaining manageable computational complexity through efficient probability calculations.
2Reliability
If soft symbol decision approach is implemented to improve interference cancellation, then interference removal efficiency improves, but computational complexity increases due to probability computations
Solution Approach 1:
The patent transforms the computational approach by changing from hard decisions to soft decisions. The soft symbol values are computed using the probability metric exp((−|yj−xj|2)/2σ2) multiplied by possible symbol values. This parameter change improves interference removal efficiency by capturing probabilistic information, while the computational complexity is managed through efficient implementation of the probability calculations rather than exhaustive search methods.
3Measurement precision
If interference components with power levels similar to or lower than SOI are processed, then deadzone is reduced, but signal extraction accuracy deteriorates due to insufficient power differential
Solution Approach 1:
The patent changes the extraction approach from power-based filtering to probability-based soft decision. By computing soft symbol values using the probability metric exp((−|yj−xj|2)/2σ2) and multiplying by possible symbol values, the system can accurately extract interference components regardless of power differential. This parameter change enables the deadzone to be reduced to 2 dB or less while maintaining signal extraction accuracy through probabilistic estimation rather than relying on power differences.
Data Source
AI summary
Systems and methods for mitigating the effect of in-band interference. The methods comprise: receiving a signal comprising at least one interfering signal component; generating a soft value for each symbol in at least one interfering signal component; and using the soft values to cancel at least one interfering signal component from the signal to mitigate the effect of interference. The soft value represents a most likely value for the symbol which is obtained by: determining a probability metric between an actual value of the symbol and each of a plurality of possible symbol values using a scaling value representing an estimate of the noise level in the signal received by the device; generating current local probabilities for the plurality of possible symbol values using the probability metric; and using the current local probabilities to determine the soft value.