Beamforming Vector Selection via Uplink Covariance Estimation
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Solution Overview
Problem
In wireless communications networks employing beamforming techniques, the lack of information about downlink channel coefficients hampers the base transceiver station's ability to obtain optimal downlink beamforming weighting vectors, especially in fast fading environments using FDD or TDD techniques, leading to suboptimal network performance.
Innovation Solution
A method involving the estimation of a downlink channel covariance matrix from an uplink covariance matrix, generating candidate beamforming weighting vectors, and selecting the best ones based on feedback from the mobile station using a probing-and-feedback approach, which includes applying these vectors sequentially and adjusting them based on received feedback to maintain or enhance network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the BTS uses a single downlink beamforming weighting vector for signal transmission, then the device complexity is reduced, but the network performance deteriorates due to inability to adapt to changing channel conditions
Solution Approach 1:
The patent implements dynamic beamforming by transitioning from a static single weighting vector to a dynamic system that maintains multiple candidate vectors and selects the optimal one based on real-time feedback from mobile stations. This allows the beamforming configuration to adapt to changing channel conditions while maintaining manageable complexity through structured selection processes.
Solution Approach 2:
The patent pre-computes and stores multiple candidate downlink beamforming weighting vectors before actual transmission occurs. These candidate vectors are prepared in advance based on uplink channel covariance matrix estimation, enabling rapid selection and application when feedback is received without requiring complex real-time computations during transmission.
2Measurement precision
If the BTS computes downlink beamforming weighting vectors using downlink channel covariance matrix, then the measurement precision is improved, but the loss of information worsens due to lack of downlink channel coefficient information in FDD/TDD systems
Solution Approach 1:
The patent introduces the uplink channel covariance matrix as an intermediary to obtain downlink beamforming information. Since uplink channel coefficients are available at the BTS and the uplink/downlink channels are reciprocal, the uplink covariance matrix serves as a mediator that provides the necessary statistical information for downlink beamforming without requiring direct downlink channel coefficient measurements from the mobile station.
Solution Approach 2:
The patent inverts the conventional approach by using uplink channel information to derive downlink beamforming weighting vectors instead of directly measuring downlink channels. This inversion leverages channel reciprocity principles, allowing the BTS to obtain downlink spatial statistics through uplink measurements, thereby overcoming the information asymmetry in FDD and TDD systems.
3Ease of operation
If the BTS transmits signals with the same beamforming weighting vector continuously, then the ease of operation is improved, but the adaptability worsens in fast fading environments
Solution Approach 1:
The patent implements periodic beamforming updates by continuously receiving feedback messages from mobile stations at regular intervals and periodically selecting new optimal beamforming weighting vectors from candidate sets. This periodic operation maintains ease of implementation through structured intervals while achieving adaptability to time-varying channel conditions through repeated selection cycles.
Solution Approach 2:
The patent establishes a feedback mechanism where mobile stations transmit periodic feedback messages containing reception quality information about downlink signals. The BTS uses this feedback to determine how to modify beamforming weighting vectors, creating a closed-loop system that adapts to channel changes while maintaining operational simplicity through rule-based modification decisions.
Data Source
AI summary
Techniques are provided for selecting one or more downlink beamforming vectors for a wireless channel to create beamformed signals between a first wireless communication device, e.g., a base transceiver station (BTS) and a second wireless communication device, e.g., a mobile station (MS). The method comprises estimating a downlink channel covariance matrix from an uplink covariance matrix of the wireless channel, wherein the uplink covariance matrix is computed based on uplink signals received at the first wireless communication device from the second wireless communication device. A plurality of candidate downlink beamforming weighting vectors are generated from the uplink covariance matrix. Each of the candidate downlink beamforming weighting vectors are applied to a corresponding downlink signal for transmission via the plurality of antennas of the first wireless communication device to the second wireless communication device such that multiple downlink signals are transmitted from the first wireless communication device to the second wireless communication device, each downlink signal with a different one of the plurality of candidate downlink beamforming weighting vectors. Feedback messages are received at the first wireless communication device from the second wireless communication device, where the feedback messages indicate reception quality of downlink signals received by the second wireless communication device from the first wireless communication device. One or more of the candidate downlink beamforming weighting vectors is selected for use in transmitting downlink signals from the first wireless communication device to the second wireless communication device based on the feedback messages.