@inproceedings{ author = {E. Beck and C. Bockelmann and A. Dekorsy}, year = {2020}, month = {Feb}, title = {Concrete MAP Detection: A Machine Learning Inspired Relaxation}, volume = {24}, publisher = {VDE-Verlag}, ISBN = {978-3-8007-5200-3}, URL = {https://www.vde.com/en/events/event-detailpage?id=17513&type=vde%7Cvdb}, address={Hamburg, Germany}, abstract={Motivated by large linear inverse problems where the complexity of the Maximum A-Posteriori (MAP) detector grows exponentially with system dimensions, e.g., large MIMO, we introduce a method to relax a discrete MAP problem into a continuous one. The relaxation is inspired by recent ML research and offers many favorable properties reflecting its quality. Hereby, we derive an iterative detection algorithm based on gradient descent optimization: Concrete MAP Detection (CMD). We show numerical results of application in large MIMO systems that demonstrate superior performance w.r.t. all considered State of the Art approaches.}, booktitle={24th International ITG Workshop on Smart Antennas (WSA 2020)} }