Beamforming Weight Vectors for Spatial De-multiplexing
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Solution Overview
Problem
Collaborative spatial multiplexing in wireless communication systems faces challenges in adequately recovering data from multiple source devices due to the complexity of processing spatially multiplexed transmissions across multiple antennas.
Innovation Solution
The implementation of beamforming weight vectors applied to receive signals at a base station with multiple antennas to de-multiplex spatially multiplexed transmissions, allowing for the recovery of modulated data from multiple source devices, while achieving noise suppression and beamforming gain comparable to non-spatial multiplexing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If collaborative spatial multiplexing is implemented to increase system capacity, then the data transmission capacity is improved, but the complexity of recovering data from multiple transmissions deteriorates
Solution Approach 1:
The patent segments the received signal into multiple independent streams by applying separate beamforming weight vectors to each antenna's receive signal. This segmentation transforms the complex multiplexed signal into N distinct signals that can be independently processed, directly resolving the data recovery complexity issue while maintaining system capacity benefits
Solution Approach 2:
The patent introduces beamforming weight vectors as intermediary processing elements between the received signals and the final data recovery stage. These weight vectors act as mediators that filter and separate the spatially multiplexed transmissions, making the subsequent data recovery process significantly simpler while preserving the high capacity advantages
2Measurement precision
If beamforming weight vectors are applied to de-multiplex spatially multiplexed transmissions, then data recovery performance is improved, but the processing complexity increases
Solution Approach 1:
The patent changes the parameters of the receive signals by applying beamforming weight vectors, which transforms the signal characteristics to enable better separation of spatially multiplexed transmissions. This parameter transformation improves data recovery performance while the structured approach to parameter change keeps processing complexity manageable
3Productivity
If multiple antennas are used to receive spatially multiplexed transmissions, then the spatial channel capacity is improved, but the difficulty of detecting and measuring individual transmissions increases
Solution Approach 1:
The patent segments the combined signal from multiple antennas into N separate signals by applying distinct beamforming weight vectors to each antenna's receive signal. This segmentation directly addresses the detection difficulty by creating independent signal paths that can be individually processed and measured, while maintaining the high spatial channel capacity provided by multiple antennas
Data Source
AI summary
Techniques are provided herein to enable collaborative spatial multiplexing in a wireless communication system. At M plurality of antennas of a first wireless communication device, N plurality of spatially multiplexed transmissions are received from corresponding ones of N plurality of second wireless communication devices. The first wireless communication device produces M receive signals from the transmissions received at the M plurality of antennas. The first wireless communication device applies beamforming weight vectors to the M receive signals and in so doing produces N signals or signal streams, where N is less than or equal to M. The first wireless communication device then recovers the modulated data for each of the transmissions from the N signals.