NoMA Signal Spreading and Mapping for Multi-UE Decoding
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Solution Overview
Problem
Existing multiple access (MA) techniques face challenges in efficiently distinguishing and decoding signals from multiple user equipment (UEs) in non-orthogonal multiple access (NoMA) scenarios, leading to signal collisions and suboptimal performance in communication systems.
Innovation Solution
A framework for generating MA signals is proposed, incorporating signal processing operations such as FEC encoding, bit-level interleaving/scrambling, modulated symbol sequence generation, and symbol-to-resource element mapping, which are UE-specific or layer-specific to enhance signal separation and decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If non-orthogonal multiple access (NoMA) techniques are used to allow multiple UEs to share transmission resources simultaneously, then spectral efficiency and system capacity are improved, but signal collision and interference increase making signal distinction and decoding difficult
Solution Approach 1:
The patent segments the signal processing operations into distinct functional blocks including FEC encoding, bit-level interleaving/scrambling, modulated symbol sequence generation, and symbol-to-resource element mapping. Each UE is assigned specific processing operations that create unique signal characteristics, enabling the receiver to distinguish between different UEs' signals even when they share the same transmission resources
Solution Approach 2:
The patent applies UE-specific or layer-specific signal processing operations to differentiate signals from different UEs. By customizing the processing operations (such as different interleaving patterns, scrambling sequences, or mapping schemes) for each UE, the system creates locally distinct signal qualities that facilitate signal separation and decoding at the receiver
2Measurement precision
If signal processing operations are made UE-specific or layer-specific to enhance signal separation, then signal decoding efficiency is improved, but system complexity increases
Solution Approach 1:
The patent applies signal processing operations in a predetermined sequence: FEC encoding first, then bit-level interleaving/scrambling, followed by modulated symbol sequence generation, and finally symbol-to-resource element mapping. This preliminary structuring of processing operations simplifies the overall system design by establishing a clear processing pipeline that can be efficiently implemented and managed
Solution Approach 2:
The patent employs a universal framework where the same set of processing operations (FEC encoding, interleaving, scrambling, modulation, mapping) can be applied to multiple UEs and layers. By making the processing operations configurable rather than completely custom for each UE, the system achieves signal differentiation while maintaining operational universality and reducing overall complexity
Data Source
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AI summary
A framework is provided for generating a MA signal based on modulating at least one first stream of bits using a first modulation type to generate at least one first modulated symbol from each of the at least one first stream of bits, spreading each of the at least one first modulated symbols using a spreading sequence that is specific to a respective first stream of bits to generate a second set of modulated symbols, mapping at least one of the second set of modulated symbols using a resource element mapping and transmitting the mapped second sets of modulated symbols as a MA signal. The spreading of each of the at least one first modulated symbols using a spreading sequence that is specific to a respective first stream of bits may use a layer specific spreading sequence and a layer specific sparsity pattern. The mapping of the at least one of the second set of modulated symbols to a resource element may use a user equipment (UE) specific and/or layer specific spreading sequence. The mapping of the at least one of the second set of modulated symbols to a resource element may use sparse spreading.