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METHODS AND SYSTEMS FOR MULTI-MODEL BLOCK LEAST SQUARES/RADIAL BASIS FUNCTION NEURAL NETWORK BASED NON-LINEAR INTERFERENCE MANAGEMENT FOR MULTI-TECHNOLOGY COMMUNICATION DEVICES
METHODS AND SYSTEMS FOR MULTI-MODEL BLOCK LEAST SQUARES/RADIAL BASIS FUNCTION NEURAL NETWORK BASED NON-LINEAR INTERFERENCE MANAGEMENT FOR MULTI-TECHNOLOGY COMMUNICATION DEVICES
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机译:基于多模型块最小二乘/径向基函数神经网络的多技术通信设备非线性干扰管理方法和系统
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摘要
The various embodiments include methods and apparatuses for canceling nonlinear interference during concurrent communication of multi-technology wireless communication devices. Nonlinear interference may be estimated using a mixed-model block least squares/radial basis function neural network by generating aggressor kernels from the aggressor signals, augmenting the aggressor kernels by weight factors and executing a linear combination of the augmented output, at an intermediate layer to produce intermediate layer outputs. At an output layer, a linear filter function may be executed on the intermediate layer outputs to produce an estimated nonlinear interference used to cancel the nonlinear interference of a victim signal.
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