Codebook Generation Agent Reducing MIMO Memory Overhead
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Solution Overview
Problem
Closed loop multiple-input-multiple-output (MIMO) systems face significant memory challenges due to the need for storing large numbers of matrix codebooks in mobile devices, which are required for efficient beamforming, leading to increased memory consumption and overhead in communication devices.
Innovation Solution
A codebook generation agent (CGA) dynamically generates matrix codebooks from vector codebooks using techniques such as Householder reflections, reducing the need for storing pre-computed matrix codebooks and minimizing memory usage while maintaining performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-computed matrix codebooks are stored in mobile devices for closed loop MIMO beamforming, then beamforming performance is improved, but memory consumption increases significantly
Solution Approach 1:
The patent segments the codebook generation process by dividing matrix codebooks into smaller vector codebooks. Instead of storing complete matrix codebooks, the system stores decomposed vector codebooks that can be recombined through Householder reflections to reconstruct the full matrix codebooks when needed, thereby reducing memory consumption while maintaining beamforming performance
Solution Approach 2:
The patent uses mathematical transformations (Householder reflections) to generate copies of codebook structures. By storing vector codebooks and applying transformations, the system creates the necessary matrix codebook copies dynamically without storing them permanently, reducing memory requirements while providing the full set of codebooks for beamforming operations
2Productivity
If the number of transmit antennas and data streams increases to improve system capacity, then productivity is improved, but the number of required codebook combinations increases exponentially
Solution Approach 1:
The patent segments the codebook structure into vector codebooks that can be combined through mathematical transformations. This segmentation allows the system to support increased numbers of transmit antennas and data streams without requiring exponential growth in stored codebook combinations, as the vector codebooks can be recombined dynamically to generate the necessary matrix codebooks for higher capacity configurations
Solution Approach 2:
The patent changes the parameter representation from storing complete matrix codebooks to storing vector codebooks with transformation parameters. This parameter change enables the system to adapt to different numbers of transmit antennas and data streams by applying the same vector codebooks with different transformation parameters, avoiding exponential growth in codebook combinations while supporting increased system capacity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The CGA effectively reduces memory requirements and computational complexity, allowing mobile devices to utilize memory for other features while maintaining similar or better performance compared to conventional techniques, as demonstrated by simulation results.
Implementation Method 1
A codebook generation agent (CGA) dynamically generates matrix codebooks from vector codebooks using techniques such as Householder reflections
Data Source
AI summary
A codebook generation system and associated methods are generally described herein. A method of generating a precoding matrix during closed-loop spatial multiplexing of wireless data may comprise selecting a vector from among vectors stored in a memory based on a received index, applying a Householder transformation to the selected vector to produce an output matrix, forming the precoding matrix from one or more columns of the output matrix, and precoding data for transmission over a wireless channel using the precoding matrix. Other embodiments are described and claimed.