Superposition Code Search for Wireless Signal Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing communication systems face inefficiencies in decoding wireless signals due to large sets of orthogonal scrambling codes, requiring extensive searches through millions of codes, which slows down the identification process and reduces accuracy.
Innovation Solution
The method involves computing superposition codes based on orthogonal binary codes, reducing the search space by amalgamating codes and using iterative binary searches to identify the specific code used for encoding, thereby enhancing decoding efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a large set of orthogonal scrambling codes is used to distinguish distinct transmitters, then the ability to identify multiple users is improved, but the search time and computational complexity increase significantly
Solution Approach 1:
The patent segments the large code set into multiple subsets and organizes them in a hierarchical tree structure. Instead of searching through all 16 million codes linearly, the system divides codes into groups and subgroups, allowing parallel processing and reducing the effective search path to logarithmic complexity.
Solution Approach 2:
The patent transforms the one-dimensional linear search problem into a multi-dimensional hierarchical search space. By organizing codes in a tree structure with multiple levels and dimensions, the system enables simultaneous correlation checks across different code subsets, effectively reducing search complexity from O(N) to O(log N).
2Adaptability or versatility
If a large set of orthogonal scrambling codes is used to distinguish distinct transmitters, then the ability to identify multiple users is improved, but the computational complexity increases significantly
Solution Approach 1:
The patent segments the large code set into multiple subsets and organizes them in a hierarchical tree structure. Instead of searching through all 16 million codes linearly, the system divides codes into groups and subgroups, allowing parallel processing and reducing the effective search path to logarithmic complexity.
Solution Approach 2:
The patent combines multiple orthogonal codes into superposition codes that represent groups of codes. By merging code subsets into hierarchical layers, the system performs correlation with aggregated code representations first, then drills down to individual codes only when necessary, significantly reducing computational operations.
3Measurement precision
If extensive searches through millions of codes are performed, then code identification accuracy is improved, but the decoding speed decreases
Solution Approach 1:
The patent performs preliminary correlation checks with superposition codes that represent groups of codes before examining individual codes. This preliminary action filters out large portions of the code space that do not match the received signal, allowing the system to maintain high accuracy while dramatically reducing the number of full correlation computations required.
Solution Approach 2:
The patent enables the system to skip through large portions of the code space by using the hierarchical tree structure. When a superposition code correlation indicates no match, the system can skip entire subtrees of codes, rushing through non-matching portions while still ensuring accurate identification of the correct code through targeted detailed examination.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
In some aspects, techniques for wireless signal decoding are described. In some instances, a number of superposition codes are computed based on a set of orthogonal binary codes. The set of orthogonal binary codes includes multiple subsets; each superposition code corresponds to one of the subsets and includes a combination of the binary codes in the corresponding subset. One of the subsets is selected based on a correlation between a wireless signal and the superposition code that corresponds to the subset. One of the binary codes is then selected from the selected subset based on a correlation between the wireless signal and the binary code. The wireless signal is decoded based on the selected binary code.