Unified Orthogonal Codebooks for Low-SNR UCI Transmission
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Solution Overview
Problem
Existing wireless communication systems, particularly 5G NR, face challenges in optimizing orthogonal sequence transmission for efficient communication, especially in low signal-to-noise ratios, where demodulation with demodulation reference signals (DMRS) is sub-optimal, leading to performance degradation.
Innovation Solution
The method involves selecting even-numbered rows and columns from a discrete Fourier transform (DFT) matrix to generate an orthogonal matrix, which is used to determine a codebook for transmitting signals, allowing non-coherent transmission of uplink control information (UCI) payloads without DMRS, suitable for small payloads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If demodulation reference signals (DMRS) are used for demodulation, then demodulation capability is provided, but performance degrades in low signal-to-noise ratios
Solution Approach 1:
The patent extracts and removes the dependency on DMRS for demodulation by using pre-agreed codebook indices. The receiver can demodulate signals without DMRS by selecting codebook matrices based on transmitted index information, eliminating the harmful effect of DMRS-related performance degradation in low SNR conditions.
Solution Approach 2:
The codebook matrices are pre-generated and stored at both transmitter and receiver before communication occurs. The receiver has pre-computed codebook matrices with different column numbers ready for immediate selection based on the transmitted index, enabling fast demodulation without requiring DMRS in low SNR scenarios.
2Quantity of substance
If codebook size is increased to support more UEs, then UE support capacity increases, but codebook generation complexity increases
Solution Approach 1:
The codebook is segmented into multiple codebook matrices, each with different column numbers (e.g., 1, 2, 4, 8 columns). This segmentation allows the system to support multiple UEs by assigning different codebook matrices to different UEs or UE groups, while keeping each individual matrix relatively simple to generate and manage.
Solution Approach 2:
The codebook generation uses parameterized formulas where the codebook matrix dimensions and properties change based on input parameters like the number of columns. By changing these parameters dynamically, the system can adapt the codebook size and complexity to match the number of supported UEs without regenerating the entire codebook structure.
Data Source
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AI summary
The present disclosure relates to methods and devices for wireless communication including an apparatus, e.g., a UE and/or base station. The apparatus can select one or more rows or one or more columns in a DFT matrix, the one or more rows being even-numbered rows in the DFT matrix and the one or more columns being even-numbered columns in the DFT matrix. The apparatus can also determine an orthogonal matrix based on the one or more rows or the one or more columns in the DFT matrix, the orthogonal matrix having a size of (MxN) x (MxN) with MxN rows and MxN columns. Also, the apparatus can determine a codebook based on the orthogonal matrix, the codebook including a plurality of codepoints. The apparatus can also transmit at least one signal including a first codepoint of the plurality of codepoints in the codebook.