Neural Network Baseband Collaboration for MIMO Throughput
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Solution Overview
Problem
In MIMO systems, communication efficiency and throughput are limited due to mobile devices communicating with a single base station, which may not have optimal antenna orientation, leading to inefficiencies and reduced performance.
Innovation Solution
Implementing collaborative baseband processing using neural networks across multiple base stations to enable simultaneous communication with a mobile device, allowing each base station to operate in standalone or collaborative modes based on positional, environmental, and network conditions, with each station having a respective neural network that can switch between modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple base stations communicate with a mobile device simultaneously using collaborative baseband processing, then communication throughput and efficiency are improved, but system complexity increases
Solution Approach 1:
The patent segments the baseband processing function across multiple base stations, with each station handling a portion of the communication task through dedicated neural network components. This segmentation allows simultaneous communication with improved throughput while distributing system complexity across multiple independent units rather than concentrating it in a single complex system.
Solution Approach 2:
Each base station is equipped with a universal neural network architecture that can operate in multiple modes (standalone or collaborative) and handle different communication scenarios. This multi-functionality allows the system to achieve high throughput through collaboration when needed while maintaining simpler operation when base stations work independently, thus managing overall system complexity.
2Reliability
If a single base station uses all 100 antennae to communicate with a mobile device, then maximum signal strength is achieved, but some antennae may not be optimally positioned or oriented reducing efficiency
Solution Approach 1:
The patent segments the antenna resources by distributing them across multiple base stations. Instead of all 100 antennae at one station, the system uses subsets of antennae at multiple stations, allowing each antenna to be optimally oriented for its specific spatial position while achieving collective signal strength through collaborative processing.
Solution Approach 2:
Each base station uses its locally optimal antenna subset based on its specific position and orientation relative to the mobile device. This local optimization ensures that each antenna operates at its best performance characteristic, while the neural network coordinates these local optimizations to achieve global communication efficiency.
3Adaptability or versatility
If mobile devices hand off communication between base stations based on physical position, then coverage is maintained, but communication efficiency and throughput are limited
Solution Approach 1:
The patent implements dynamic mode switching where base stations can transition between standalone and collaborative operation based on real-time conditions including mobile device position, environmental factors, and network state. This dynamic adaptability maintains coverage while optimizing throughput by engaging collaboration when beneficial and using standalone mode when sufficient.
Solution Approach 2:
The system uses feedback from neural network performance metrics and communication conditions to dynamically adjust the level of collaboration between base stations. This feedback mechanism allows the system to maintain coverage adaptability while optimizing communication efficiency based on actual performance data and changing environmental conditions.
Data Source
AI summary
A system includes a first wireless communication device comprising a first baseband processor neural network configured to process at least part of data for transmission to a second wireless communication device according to a collaborative processing configuration while collaborative processing is enabled to generate a first radio frequency (RF) signal. The first wireless communication device is configured to transmit the first RF signal. The system further includes a third wireless communication device comprising a second baseband processor neural network configured to, while the collaborative processing is enabled, process at least part of the data for transmission to the second wireless communication device according to a collaborative processing configuration to generate a second RF signal. The third wireless communication device is configured to transmit the second RF signal in collaboration with transmission of the first RF signal by the first baseband processor.