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"Signal Detection in MIMO Systems with Hardware Imperfections: Message " by Dawei Gao, Qinghua Guo et al.

We investigate signal detection in multiple-input-multiple-output (MIMO) communication systems with hardware impairments, such as power amplifier nonlinearity and in-phase/quadrature imbalance. To deal with the complex combined effects of hardware imperfections, neural network (NN) techniques, in particular deep neural networks (DNNs), have been studied to directly compensate for the impact of hardware impairments. However, it is difficult to train a DNN with limited pilot signals, hindering its practical application. In this work, we investigate how to achieve efficient Bayesian signal detection in MIMO systems with hardware imperfections. Characterizing combined hardware imperfections often leads to complicated signal models, making Bayesian signal detection challenging. To address this issue, we first train an NN to ‘model’ the MIMO system with hardware imperfections and then perform Bayesian inference based on the trained NN. Modelling the MIMO system with NN enables the design ....

Approximate Message Passing Amp , Rtificial Neural Networks , Bayes Methods , Bayesian Inference , Factor Graphs , Ardware Imperfections , Iq Imbalance , Message Passing , Imo Communication , Ultiple Input Multiple Output Mimo , Eural Networks Nns , Ower Amplifier Nonlinearity , Signal Detection ,

"Efficient Channel Estimation for RIS-Aided MIMO Communications with Un" by Yabo Guo, Peng Sun et al.

Reconfigurable intelligent surface (RIS) is very promising for wireless networks to achieve high energy efficiency, extended coverage, improved capacity, massive connectivity, etc. To unleash the full potentials of RIS-aided communications, acquiring accurate channel state information is crucial, which however is very challenging. For RIS-aided multiple-input and multiple-output (MIMO) communications, the existing channel estimation methods have computational complexity growing rapidly with the number of RIS units N (e.g., in the order of N2 or N3) and/or have special requirements on the matrices involved (e.g., the matrices need to be sparse for algorithm convergence to achieve satisfactory performance), which hinder their applications. In this work, instead of using the conventional signal model in the literature, we derive a new signal model obtained through proper vectorization and reduction operations. Then, leveraging the unitary approximate message passing (UAMP), we develop a m ....

Approximate Message Passing Amp , Channel Estimation , Electronic Mail , Message Passing , Imo Communication , Econfigurable Intelligent Surface Ris , Signal Processing Algorithms , Parse Matrices ,