Adaptive Beamforming Power Constraint Selection
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Solution Overview
Problem
Existing transmit beamforming techniques vary in bit error rate (BER) or block error rate (BLER) due to different normalization methods used for beam weights, which affect the signal-to-interference-plus-noise ratio (SINR) and overall data communication efficiency.
Innovation Solution
A method and apparatus that normalize beam weights based on a code rate, using either per-symbol, per-antenna (PSPA) or per-tone, per-antenna (PTPA) power constraints, with the threshold value determined by signal-to-noise ratio, frequency selectivity, and delay spread of the estimated channel, to improve BER or BLER.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If different normalization methods are used for beam weights, then the overall transmit power is constrained, but the bit error rate (BER) or block error rate (BLER) varies and deteriorates
Solution Approach 1:
The patent applies dynamics by making the normalization method adaptive rather than fixed. The system dynamically selects between PSPA and PTPA normalization methods based on real-time channel conditions (frequency selectivity and delay spread), allowing the beamforming system to adapt its power distribution strategy to match the current wireless environment, thereby maintaining low BER across varying channel characteristics
Solution Approach 2:
The patent changes the parameter of normalization method selection based on channel characteristics. By evaluating frequency selectivity and delay spread parameters, the system selects the appropriate normalization approach (PSPA or PTPA), effectively using parameter-based adaptation to resolve the contradiction between power constraint and error rate performance
2Ease of operation
If a fixed normalization method is used, then the system is simple to implement, but the performance deteriorates under varying channel conditions
Solution Approach 1:
The system transitions from a static normalization approach to a dynamic one by automatically selecting between PSPA and PTPA methods based on channel conditions. This dynamic adaptation maintains implementation simplicity while significantly improving reliability under varying channel conditions, as the system adjusts its behavior without requiring complex manual configuration
Solution Approach 2:
The beamforming system performs self-service by autonomously evaluating its own operating conditions (frequency selectivity and delay spread) and selecting the appropriate normalization method without external intervention. This self-adaptation mechanism maintains ease of operation while improving performance across diverse channel environments
3Reliability
If adaptive normalization is implemented, then the BER and BLER performance is improved, but the device complexity increases
Solution Approach 1:
The patent applies local quality by implementing adaptive normalization only where needed - specifically in the beam weight calculation module. The rest of the beamforming system remains unchanged, using standard procedures for channel estimation and beam weight computation. This localized adaptation minimizes overall system complexity while achieving improved BER performance
Solution Approach 2:
The system manages complexity by changing only the normalization parameter selection based on channel conditions, rather than fundamentally altering the beamforming architecture. The adaptive mechanism adds minimal complexity by evaluating frequency selectivity and delay spread parameters and selecting between two established normalization methods, achieving performance improvement without substantial device complexity increase
Data Source
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AI summary
Embodiments of a method and apparatus for selecting one of several different power constraints under which sets of complex, beam weights are normalized are described herein. The embodiments of the method and apparatus specifically select the power constraint based on a code rate used to encode information carried by a transmit signal weighted by the sets of complex, beam weights. Appropriate selection of the power constraint can improve the bit error rate (BER) or block error rate (BLER) of the decoded transmit signal at a receiver.