Bit-Level Combining for MIMO HARQ 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 due to system complexity, particularly in decoder complexity, often limiting the use of incremental redundancy and arbitrary number of transmitted packets.
Innovation Solution
The system decodes and combines multiple received signal vectors using protocols like HARQ and repetition coding, employing maximum-likelihood decoders and log-likelihood ratios to produce a hard or soft estimate of the transmitted sequence, allowing for incremental redundancy and low hardware requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system uses multiple transmissions with incremental redundancy to improve reliability, then the reliability of data transmission is improved, but the decoder complexity increases significantly
Solution Approach 1:
The patent segments the received signal vectors and processes them through separate maximum-likelihood decoders, with each decoder handling one transmitted sequence. The soft information outputs from multiple decoders are then combined through simple addition, avoiding the need for a single complex decoder that would process all transmissions together. This segmentation maintains high reliability through incremental redundancy while keeping individual decoder complexity manageable.
Solution Approach 2:
The patent merges the soft information outputs from multiple maximum-likelihood decoders by simple addition to produce the final decoded sequence. This combining operation is computationally simple compared to alternative approaches that would require complex joint decoding algorithms, thereby maintaining low decoder complexity while achieving high transmission reliability through the accumulation of information from multiple transmissions.
2Productivity
If the system processes an arbitrary number of transmitted packets to improve throughput, then the productivity is improved, but the system complexity increases
Solution Approach 1:
The patent segments the processing of multiple transmitted packets by assigning each packet to a separate maximum-likelihood decoder. This allows the system to handle an arbitrary number of packets simultaneously with linearly increasing complexity rather than exponentially increasing complexity, thereby improving throughput while keeping system complexity manageable through modular parallel processing.
Solution Approach 2:
The patent employs multiple identical maximum-likelihood decoders that can process any number of transmitted packets universally. Each decoder is a universal processing unit capable of handling any transmitted sequence, and the system can scale to process an arbitrary number of packets by simply adding more identical decoder units, avoiding the need for complex specialized processing for different packet numbers.
3Reliability
If the system uses HARQ and repetition coding protocols to utilize information from multiple transmissions, then the reliability is improved, but the hardware requirements increase
Solution Approach 1:
The patent segments the received signal vectors and processes each through separate maximum-likelihood decoders, with outputs combined by simple addition. This segmentation approach implements HARQ and repetition coding protocols efficiently, maintaining high transmission reliability while avoiding the need for complex hardware that would be required for joint processing of all transmissions, thereby reducing overall hardware requirements.
Solution Approach 2:
The patent uses multiple copies of the same maximum-likelihood decoder structure to process different transmitted sequences. Rather than designing a single complex hardware system that handles all protocols, the system creates multiple identical decoder copies that can process HARQ, repetition coding, and other protocols uniformly, simplifying hardware design while maintaining high reliability through protocol diversity.
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 from a common digital information sequence. Each received signal vector is decoded using, for example, a maximum-likelihood decoder to produce log-likelihood ratios. The results of the decoders are combined by addition to produce a final decoding estimate. In some embodiments, each of the received signals may be processed prior to decoding. The disclosed decoding scheme may utilize all received information without increasing hardware complexity.