Massive multiple-input multiple-output (MIMO) is a key technology to meet the user demands
in performance and quality of services (QoS) for next generation communication systems …

Detection techniques for massive multiple-input multiple-output (MIMO) have gained a lot of
attention in both academia and industry. Detection techniques have a significant impact on …

The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …

Intelligent signal processing for wireless communications is a vital task in modern wireless
systems, but it faces new challenges because of network heterogeneity, diverse service …

A quasi-static flat multiple-antenna channel is considered. We show how real multilevel
modulation symbols can be detected via deep neural networks. A multi-plateau sigmoid …

This paper introduces a framework for systematic complexity scaling of deep neural network
(DNN) based MIMO detectors. The model uses a fraction of the DNN inputs by scaling their …

Belief Propagation (BP) is a simple probabilistic inference algorithm, consisting of passing
messages between nodes of a graph representing a probability distribution. Its analogy with …

Signal detection using deep learning is a challenging and promising research topic. Several
learning-based signal detectors have been proposed to produce significant results …

In this paper, a QR-decomposition-based scheduled belief propagation (BP) detector with
interference cancellation (IC) and candidate constraints is proposed for multiple-input …

Applications of deep learning have not been adequately studied in communication systems,
though it is a tremendously popular approach in many other fields. This study focuses on the …