Soft Bit Reuse for Multiuser Detection Interference Cancellation
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Solution Overview
Problem
The existing multiuser detection methods in WCDMA uplink receivers face high computational complexity, which is not suitable for low-cost base stations with limited memory and processing capacity, due to the need for complex interference cancellation and reconstruction processes.
Innovation Solution
The proposed method reduces storage requirements and processing capability by reusing soft bit estimates generated during previous iterations for subsequent interference cancellation decoding, allowing for serial or parallel interference cancellation processes without storing reconstructed signals, thus simplifying the decoding process and reducing computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional multiuser detection methods are used with interference cancellation and reconstruction processes, then receiver performance is improved, but computational complexity and storage requirements increase significantly
Solution Approach 1:
The patent extracts only the essential soft bit estimates from the complete interference cancellation process, discarding the reconstructed signal storage requirement. By taking out only the necessary soft bit information and using it directly in subsequent iterations, the system maintains receiver performance while eliminating the need to store and process full reconstructed signals, thus reducing computational complexity.
Solution Approach 2:
The patent creates a simplified copy of the interference cancellation process that operates on soft bit estimates rather than full reconstructed signals. This copying approach maintains the essential functional behavior of interference cancellation while using significantly fewer resources, as soft bit estimates are much smaller data structures compared to complete signal reconstructions.
2Reliability
If conventional multiuser detection methods are used with interference cancellation and reconstruction processes, then receiver performance is improved, but storage requirements increase significantly
Solution Approach 1:
The patent extracts only the essential soft bit estimates from the complete interference cancellation process, discarding the reconstructed signal storage requirement. By taking out only the necessary soft bit information and using it directly in subsequent iterations, the system maintains receiver performance while eliminating the need to store and process full reconstructed signals, thus reducing computational complexity.
Solution Approach 2:
The patent discards the need to store reconstructed signals by recovering only the essential soft bit estimates from the interference cancellation process. These soft bit estimates are sufficient to continue the detection process without requiring the full reconstructed signals to be stored, thereby reducing storage requirements while maintaining performance.
3Measurement precision
If typical multiuser detection using Maximum Likelihood criteria is used, then detection accuracy is improved, but processing capability requirements increase exponentially
Solution Approach 1:
The patent applies partial action by implementing interference cancellation only for the necessary soft bit estimates rather than performing complete Maximum Likelihood detection for all users simultaneously. This partial approach provides sufficient detection accuracy for practical purposes while avoiding the exponential processing complexity of full ML detection, achieving a reasonable trade-off between accuracy and computational burden.
Data Source
AI summary
Methods and systems of symbol level interference cancellation at a receiver for multiuser detection is provided. In an embodiment, the method includes performing an interference cancellation based decoding for a plurality of users through a plurality of iterations for generating a plurality of soft bit estimates for each of the users during each of the iterations. Each of the iterations involves sequential cancellation of each of the user signals for performing interference cancellation based decoding for each subsequent user other than a first user. The method also includes re-using the generated plurality of soft bit estimates for performing each subsequent iteration of the interference cancellation based decoding of the plurality of users. A plurality of soft bit estimates associated with each user generated during an (N−1)th iteration is re-used during an Nth iteration for the user, N being a whole number with a minimum value of 2.