MIMO Receiver Combining Signal Vectors for Linear Decoding
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Solution Overview
Problem
Current multiple-input multiple-output (MIMO) data transmission systems face challenges in effectively utilizing information from multiple transmissions of the same signal vector due to system complexity, limiting the decoder's ability to fully utilize all received data without increasing complexity.
Innovation Solution
The system combines multiple received signal vectors using symbol-level combining techniques, such as maximal ratio combining (MRC) and zero-forcing (ZF) equalization, to create a single combined signal vector, which is then decoded using a linear decoder, allowing for optimal utilization of all received information without drastically increasing system complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the decoder fully utilizes all received data from multiple transmissions, then decoding performance is improved, but system complexity increases
Solution Approach 1:
The patent segments the received signal vectors into multiple groups and processes them through separate combining operations. By dividing the complex task of processing all received data into smaller segments (different combining operations on different signal groups), the system achieves thorough utilization of received information while managing computational complexity through structured segmentation
Solution Approach 2:
The patent merges multiple received signal vectors through combining operations (such as maximal ratio combining or equal-gain combining) to create combined signal vectors. This merging process allows the decoder to fully utilize information from all transmissions by integrating multiple signal copies, thereby improving decoding performance while the structured combining approach keeps complexity manageable
2Loss of information
If symbol-level combining techniques are used to combine multiple signal vectors, then information utilization is improved, but processing complexity increases
Solution Approach 1:
The patent applies partial combining by processing signal vectors in groups rather than all at once. Different combining operations are applied to different groups of signals, which allows thorough information utilization through multiple combining passes while reducing processing complexity by breaking down the exhaustive combining task into manageable partial operations
Solution Approach 2:
The patent changes processing parameters by applying different combining strategies (such as varying combining weights, different equalization methods, or different grouping schemes) to different signal vector groups. This parameter variation allows comprehensive information extraction through multiple processing approaches while managing complexity through parameter diversity rather than structural complexity
3Measurement precision
If multiple received signal vectors are combined before decoding, then decoding accuracy is improved, but computational load increases
Solution Approach 1:
The patent segments the combining and decoding process into multiple stages, where different combining operations are applied to different groups of signal vectors before final decoding. This segmentation allows accurate decoding by combining all received information while reducing computational load by performing combining operations in manageable segments rather than processing all signals simultaneously in a single complex operation
Solution Approach 2:
The patent performs preliminary combining operations on groups of signal vectors before the final decoding step. By pre-combining signals in organized groups with simpler operations first, the system prepares the data for final decoding in a way that improves accuracy through comprehensive combining while reducing the computational burden on the final decoding operation
Data Source
AI summary
Systems and methods are provided for decoding signal vectors in multiple-input multiple-output (MIMO) systems, where the receiver has received one or more signal vectors based on the same transmitted vector. The symbols of the received signal vectors are combined, forming a combined received signal vector that may be treated as a single received signal vector. The combined received signal vector may be equalized by, for example, a zero-forcing or minimum-mean-squared error equalizer or another suitable linear equalizer. Following equalization, the equalized signal vector may be decoded using a simple, linear decoder.