CSI Feedback Scalar Quantization for Low-Complexity MIMO Streams

The patent changes the quantization parameter from vector-based to scalar-based operations. By transforming the latent feature vector into a quantized CSI feedback vector through scalar quantization with bounding, rounding, and normalization operations, the system reduces computational complexity while maintaining feedback precision. This parameter change from vector quantization to scalar quantization directly resolves the contradiction between precision and complexity.

The patent extracts and eliminates the computationally intensive distance calculation step from the quantization process. By using scalar quantization with direct rounding operations instead of vector-based distance calculations, the system removes the bottleneck that reduces productivity. This extraction of the harmful computational step while retaining the essential quantization function resolves the contradiction between precision and efficiency.

The patent replaces expensive vector quantization operations with cheaper scalar quantization operations. By using simple bounding, rounding, and normalization operations instead of computationally intensive vector distance calculations, the system reduces energy consumption. This substitution of expensive operations with cheaper alternatives while maintaining functional equivalence resolves the contradiction between precision and energy efficiency.