MMSE Receiver Weighting for FSTD Interference Suppression
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Solution Overview
Problem
Existing communication networks face interference issues due to signals from inter-cell and intra-cell user equipment devices, particularly when using frequency switched transmit diversity coding, which standard Minimum Mean Square Error (MMSE) solutions cannot effectively suppress.
Innovation Solution
A method and device that calculate estimated channel vectors and data covariance matrices to determine combining weight vectors, processing received signals to suppress interference by reversing orthogonal cover code spreading and cyclic shifts, and applying codeword combining and interleaving to decode soft values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If standard Minimum Mean Square Error (MMSE) solutions are used for signal reception, then the reception process is simple, but interference from inter-cell and intra-cell user devices is not adequately suppressed
Solution Approach 1:
The patent changes the parameters of the MMSE receiver by incorporating frequency-switched transmit diversity coding parameters. The receiver adapts its combining weights based on the frequency slot index and transmit antenna port mappings, transforming the standard MMSE approach into a diversity-aware receiver that maintains simplicity while improving interference suppression through parameter adaptation.
Solution Approach 2:
The patent introduces dynamic adapting of the MMSE combining weights based on the detected frequency slot and transmit antenna configuration. The receiver dynamically adjusts its processing parameters according to the received signal characteristics, enabling it to adapt to different frequency-switched transmit diversity scenarios while maintaining computational efficiency.
2Reliability
If frequency switched transmit diversity coding is used to improve signal transmission, then transmission reliability is enhanced, but interference from multiple transmit antennas is not adequately suppressed
Solution Approach 1:
The patent segments the received signal processing into separate handling for each transmit antenna port. By identifying which antenna ports are active in each frequency slot and applying separate combining weights for each port, the receiver can process signals from multiple antennas independently and then combine them optimally, maintaining the benefits of transmit diversity while suppressing interference.
Solution Approach 2:
The patent applies local quality optimization by calculating separate MMSE combining weights for each transmit antenna port based on its specific channel conditions and interference characteristics. Instead of using a single global combining strategy, the receiver optimizes the combining weights locally for each antenna port, improving overall interference suppression while maintaining transmission reliability.
3Measurement precision
If combining weight vectors are matched to data signal structure to suppress interference, then reception performance is improved, but calculation complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing the mapping relationships between frequency slots and transmit antenna ports. The receiver uses these pre-established mappings to quickly identify which antenna ports are active in each frequency slot, avoiding complex real-time analysis and reducing calculation complexity while maintaining accurate combining weight determination.
Solution Approach 2:
The patent applies partial action by focusing the combining weight calculation only on the subset of transmit antenna ports that are actually active in each frequency slot, rather than processing all possible antenna ports. This selective approach reduces the dimensionality of the calculation while still achieving optimal interference suppression for the relevant signals.
Data Source
AI summary
Devices and methods for suppressing interference in inter-cell and intra-cell network communication. First and second received signals are received at a communication device, the first and second received signals comprising, respectively, reference signals and data signals. Estimated channel vectors are calculated from the first received signals, and estimated data covariance matrices are calculated from the second received signals. A plurality of combining weight vectors are determined based on the estimated channel vectors and the estimated data covariance matrices. The second received signals are then combined with the plurality of combining weight vectors to obtain a plurality of combined signals, wherein interference in the second received signals has been suppressed in the plurality of combined signals.