Antenna Array Signal Weighting for Interference Suppression
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Solution Overview
Problem
Current signal processing methods for arrays of antennas struggle to effectively enhance information from a known signal source while suppressing interference, particularly in scenarios with spatially white noise and varying channel conditions.
Innovation Solution
The method involves processing sample vectors to estimate weights that maximize the energy of the desired signal and minimize interference, using expressions like minw_,c_X*Yw_-(C0c_0+Cc_)wherec_0=1, and employing Singular Value Decomposition (SVD) for pseudoinverse calculations to handle complex channel estimates and noise conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional signal processing methods are used for antenna arrays, then the system is simpler to implement, but the ability to suppress interference and enhance signal detection is insufficient
Solution Approach 1:
The patent segments the signal processing task into distinct stages: correlation computation, weight estimation, and signal combination. Each stage processes specific components (known symbols, sample vectors, weight vectors) separately, allowing complex interference suppression to be achieved through modular, manageable operations rather than a monolithic complex system.
Solution Approach 2:
The patent introduces spatial dimension processing by utilizing multiple antenna elements and computing weights across the spatial domain. The weight vector operates in the spatial dimension to combine signals from different antenna elements, adding a dimensional approach to interference suppression that goes beyond conventional single-channel processing.
2Reliability
If weight estimation maximizes desired signal energy, then signal enhancement is improved, but interference suppression may be compromised
Solution Approach 1:
The patent employs feedback through the weight estimation process where the correlation results between known symbols and received signals are used to compute optimal weights. These weights are then applied to combine antenna signals, and the process adapts based on the measured signal characteristics, creating a feedback loop that simultaneously enhances desired signals and suppresses interference.
Solution Approach 2:
The patent changes the parameter space by working with complex weight vectors that have both magnitude and phase components. By optimizing these complex parameters based on correlation measurements, the system can adjust the contribution of each antenna element to maximize signal enhancement while minimizing interference through precise parameter control.
3Adaptability or versatility
If processing is performed for each sample vector individually, then adaptability to channel variations is improved, but processing time and complexity increase
Solution Approach 1:
The patent performs preliminary correlation computation between known symbols and received signals before weight estimation. This preliminary processing extracts useful information about the channel conditions and signal characteristics in advance, allowing subsequent weight computation to be more efficient and reducing the overall processing time while maintaining adaptability.
Data Source
AI summary
Sample vectors of a signal received simultaneously by an array of antennas are processed to estimate a weight for each sample vector that maximizes the energy of the individual sample vector that resulted from propagation of the signal from a known source and/or minimizes the energy of the sample vector that resulted from interference with propagation of the signal from the known source. Each sample vector is combined with the weight that is estimated for the respective sample vector to provide a plurality of weighted sample vectors. The plurality of weighted sample vectors are summed to provide a resultant weighted sample vector for the received signal. The weight for each sample vector is estimated by processing the sample vector in accordance with the expression:minw_,c_X*Yw_-(C0c_0+Cc_)pwhere c0=1 and 0<p≦∞. The processing of the sample vector to estimate the weight w, includes a step of calculating a pseudoinverse (ZX*Y)+. The pseudoinverse is calculated by a simplified method.


