Sparse Space Coding With Iterative Decoding for Multi-User MIMO

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Solution Overview

Problem

Current MIMO communication systems face challenges in achieving efficient multi-user transmission and decoding due to sub-optimal word error rates and spectral efficiency, particularly in multi-user scenarios with multiple transmit and receive antennas.

Innovation Solution

The implementation of multi-user sparse space codes (MU-SSC) using low-density parity-check (LDPC) codes as outer codes and sparse space codes as inner codes, along with iterative decoding schemes, to enhance transmission efficiency and decoding accuracy in MIMO channels.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If orthogonal space-time block codes (OSTBC) are used to achieve full diversity gain in MIMO channels, then reliability is improved, but spectral efficiency deteriorates

Engineering Contradiction:

Improvediversity gainVSAvoidspectral efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The code structure is segmented into outer LDPC code and inner sparse space code layers, allowing independent optimization of reliability (through LDPC error correction) and spectral efficiency (through sparse space code diversity), resolving the trade-off by dividing the coding function into specialized components

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent employs a composite coding scheme combining LDPC codes and sparse space codes, where each code type contributes its strengths (LDPC for error correction, sparse space codes for diversity and spectral efficiency), achieving both high reliability and spectral efficiency simultaneously

Inventive Principle:

Principle #40Composite materials

2Reliability

If traditional coding schemes are used in multi-user MIMO scenarios, then device complexity is reduced, but word error rate deteriorates

Engineering Contradiction:

Improveword error rateVSAvoiddecoding complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The iterative decoding scheme implements feedback between the outer LDPC decoder and inner sparse space code decoder, where each decoder provides preliminary results to the other for refinement, progressively improving word error rate performance through multiple iterative exchanges of decoding information

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The decoding architecture nests the sparse space code decoder within the LDPC decoder framework, creating a hierarchical structure where the inner decoder processes signals first and its output feeds the outer decoder, managing complexity through organized nesting of decoding functions

Inventive Principle:

Principle #7Nested doll (Nesting)

3Productivity

If multi-user transmission is implemented in MIMO systems, then productivity is improved, but measurement precision deteriorates

Engineering Contradiction:

Improvespectral efficiencyVSAvoiddecoding accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The sparse space code structure assigns different sparsity patterns and code properties to different users and transmit antennas, allowing each user signal to be optimized locally for its specific channel conditions while maintaining overall multi-user spectral efficiency, with the iterative decoder adapting to local signal characteristics

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS8942308B2Multi-level coding and iterative decoding using sparse space codes

Publication Date: 2015.01.27 MALIKIE INNOVATIONS LTD

AI summary

A multi-level coding and iterative decoding scheme using sparse space codes as the inner-code and codes amenable to belief propagation decoding methods (such as low-density parity-check (LDPC) codes, turbo codes, and trellis codes) as the outer-code is proposed for MIMO communication channels.