Adaptive Beam Weights for RFIC Memory-Limited Beamforming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless communication systems face challenges in achieving enhanced beam properties due to limited memory in RFICs, which restricts the number of beam weights that can be stored, leading to suboptimal signal-to-noise ratio and resource wastage, especially in hyper-densified networks.
Innovation Solution
Adaptive beam weights are designed to satisfy pre-specified beam property specifications, such as SNR, side lobe requirements, and main lobe properties, allowing for improved beamforming and resource conservation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If adaptive beam weights are implemented to enhance beam properties, then beamforming performance and SNR are improved, but memory requirements in RFICs increase
Solution Approach 1:
The patent segments beam weights into two categories: codebook-based beam weights stored in RFIC memory and adaptive beam weights computed by the processor. This segmentation allows the system to maintain enhanced beamforming performance through adaptive weights while limiting memory usage to only the essential codebook weights, resolving the contradiction between performance and memory capacity.
Solution Approach 2:
The processor acts as an intermediary that computes adaptive beam weights based on channel state information and combines them with codebook-based weights. This intermediary computation approach enables enhanced beam properties without requiring all adaptive weights to be stored in limited RFIC memory, thus resolving the memory-capacity constraint.
2Manufacturing precision
If more beam weights are stored in RFIC memory, then beam property specifications can be better satisfied, but device complexity and cost increase
Solution Approach 1:
The patent divides beam weight functionality into stored codebook weights and computationally-generated adaptive weights. This segmentation enables satisfaction of beam property specifications through adaptive computation while maintaining simpler RFIC memory requirements, thus resolving the contradiction between specification accuracy and device complexity.
Solution Approach 2:
The system changes the parameter of beam weight representation from purely stored lookup tables to a hybrid approach combining stored codebook indices with processor-computed adaptive coefficients. This parameter change enables precise beam property control without proportionally increasing memory complexity, as adaptive weights are generated algorithmically rather than stored exhaustively.
3Quantity of substance
If codebook-based beam weights are used, then memory usage is reduced, but beamforming adaptability and performance are limited
Solution Approach 1:
The patent uses codebook-based weights as preliminary beamforming configurations that provide a foundation for adaptive enhancement. These pre-stored codebook weights reduce immediate memory requirements while the processor refines them using channel state information, thus achieving both memory efficiency and adaptability through a two-stage approach.
Solution Approach 2:
The system transitions from static codebook-based beam weights to dynamic adaptive beam weights by incorporating real-time channel state information processing. This dynamic adaptation layer is added on top of the static codebook foundation, enabling enhanced versatility without proportionally increasing memory usage, as the adaptability comes from computation rather than storage.
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit an indication of a capability for using adaptive beam weights to realize beam property specifications. The UE may receive an indication of one or more beam weights that satisfy the beam property specifications. Numerous other aspects are described.