S. C. Birgmeier, N. Görtz:

"Approximate Message Passing for Joint Activity Detection and Decoding in Non-orthogonal CDMA";

Talk: 23rd International ITG Workshop on Smart Antennas (WSA 2019), Wien; 04-24-2019 - 04-26-2019; in: "Proceedings International ITG Workshop on Smart Antennas (WSA 2019)", VDE Verlag, (2019), 53 - 57.

In Compressive Sensing, the knowledge of an unknown vector´s statistical properties together with a small number of linear measurements makes it possible to reconstruct the vector with high accuracy in terms of minimum mean-squared error. A popular statistical property is sparsity of the unknown vector. The model can thus be applied to multi-user systems, where only a small number of users is active at a given time. In this paper, we show how the properties of the users´ channel code and approximate knowledge of the fraction of active users can be used to simultaneously detect user activity and the transmitted codeword, when the users´ code-symbols are transmitted by non-orthogonal spreading sequences. The main goal is to provide

a unified framework (based on compressed-sensing techniques) in which to describe and solve the joint detection-and-decoding problem by a single computationally highly efficient algorithm.

https://ieeexplore.ieee.org/document/8727194

In Compressive Sensing, the knowledge of an unknown vector´s statistical properties together with a small number of linear measurements makes it possible to reconstruct the vector with high accuracy in terms of minimum mean-squared error. A popular statistical property is sparsity of the unknown vector. The model can thus be applied to multi-user systems, where only a small number of users is active at a given time. In this paper, we show how the properties of the users´ channel code and approximate knowledge of the fraction of active users can be used to simultaneously detect user activity and the transmitted codeword, when the users´ code-symbols are transmitted by non-orthogonal spreading sequences. The main goal is to provide

a unified framework (based on compressed-sensing techniques) in which to describe and solve the joint detection-and-decoding problem by a single computationally highly efficient algorithm.

https://ieeexplore.ieee.org/document/8727194

Signal Processing / Compressed Sensing / Approximate Message Passing

Created from the Publication Database of the Vienna University of Technology.