Massive MIMO Pilot Signal Overhead Reduction via Eigenmode Extraction
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Solution Overview
Problem
In massive MIMO networks, efficiently determining and adapting to channel conditions for reliable and high-capacity transmission is challenging due to the need for comprehensive channel sounding and sharing of channel correlation matrices, which consumes bandwidth and resources.
Innovation Solution
A method where a terminal determines an uplink pilot signal based on the channel correlation matrix, allowing for accurate channel sounding and link adaptation with reduced overhead by combining receive properties of downlink data from multiple uplink pilot signals, thereby averaging out small-scale fading and leveraging the coherence of large-scale fading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive channel sounding is performed by mapping UL pilot signals to instantaneous channel to achieve accurate channel correlation matrix, then measurement precision is improved, but loss of information increases due to large bandwidth consumption for sharing channel correlation matrix between terminal and BS
Solution Approach 1:
The patent extracts only the essential information needed for link adaptation - specifically the dominant eigenmode of the channel correlation matrix - rather than sharing the complete channel correlation matrix. This extraction approach maintains measurement precision for determining the optimal spatial stream while significantly reducing the information that needs to be communicated between terminal and base station.
Solution Approach 2:
Instead of the terminal determining the channel correlation matrix and sharing it with the base station (conventional approach), the patent inverts the process: the terminal transmits multiple orthogonal UL pilot signals, receives DL data encoded according to each pilot signal, combines the receive properties, and locally determines the channel correlation matrix and dominant eigenmode. This inversion eliminates the need for extensive information sharing while maintaining accurate channel sounding.
2Measurement precision
If multiple orthogonal UL pilot signals are transmitted to achieve accurate channel sounding, then measurement precision is improved, but device complexity increases due to requirements for comprehensive channel correlation matrix sharing
Solution Approach 1:
The terminal performs self-service by locally determining the channel correlation matrix and dominant eigenmode through combining receive properties of DL data from multiple UL pilot signals. This self-determination eliminates the need for complex coordination and information sharing with the base station, reducing system complexity while maintaining accurate channel sounding capabilities.
3Adaptability or versatility
If comprehensive channel correlation matrix information is shared between terminal and BS, then adaptability is improved for link adaptation, but loss of time increases due to overhead consumption
Solution Approach 1:
The terminal performs preliminary channel sounding by transmitting multiple orthogonal UL pilot signals and combining receive properties before determining the dominant eigenmode. This preliminary action at the terminal side eliminates the need for subsequent time-consuming information exchange with the base station, achieving both accurate link adaptation and reduced overhead time.
Data Source
AI summary
A device controls each antenna to transmit at least one first UL pilot signal and to receive, for each first UL pilot signals DL data encoded according to the respective first UL pilot signal. The receive properties of the DL data are combined and a second UL pilot signal is determined based on the combined receive properties. The second UL pilot signal is repeatedly transmitted. The techniques may be applied in a massive multi-input multi-output scenario.