Complex Trainable ISTA for Linear and Nonlinear Inverse Problems

Understand

Complex-field signal recovery problems from noisy linear/nonlinear measurements appear in many areas of signal processing and wireless communications.

• In this paper, we propose a trainable iterative signal recovery algorithm named complex-field TISTA (C-TISTA) which treats complex-field nonlinear inverse problems.
• C-TISTA is based on the concept of deep unfolding and consists of a gradient descent step with the Wirtinger derivatives followed by a shrinkage step with a trainable complex-valued shrinkage function.
• Importantly, it contains a small number of trainable parameters so that its training process can be executed efficiently.