Related papers: MIMO Channel Estimation using Score-Based Generati…
This work examines the use of two-way training to efficiently discriminate the channel estimation performances at a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. This…
This work proposes a generative modeling-aided channel estimator based on mixtures of factor analyzers (MFA). In an offline step, the parameters of the generative model are inferred via an expectation-maximization (EM) algorithm in order to…
This work examines the use of two-way training in multiple-input multiple-output (MIMO) wireless systems to discriminate the channel estimation performances between a legitimate receiver (LR) and an unauthorized receiver (UR). This thesis…
In this paper, we study the channel estimation problem in correlated massive multiple-input-multiple-output (MIMO) systems with a reduced number of radio-frequency (RF) chains. Importantly, other than the knowledge of channel correlation…
This paper addresses the problem of channel estimation in multi-cell interference-limited cellular networks. We consider systems employing multiple antennas and are interested in both the finite and large-scale antenna number regimes…
With a significant increase in area throughput, Massive MIMO has become an enabling technology for fifth generation (5G) wireless mobile communication systems. Although prototypes were built, an openly available dataset for channel impulse…
Accurate channel impulse response (CIR) is required for coherent detection and it can also help improve communication quality of service in next-generation wireless communication systems. One of the advanced systems is multi-input…
Most existing generative models are limited to learning a single probability distribution from the training data and cannot generalize to novel distributions for unseen data. An architecture that can generate samples from both trained…
In this paper, a framework of beamspace channel estimation in millimeter wave (mmWave) massive MIMO system is proposed. The framework includes the design of hybrid precoding and combining matrix as well as the search method for the largest…
This paper addresses the training signal design for the channel estimation in two-way multiple-input-and-multipleoutput (MIMO) relay systems, where the channels are correlated. We first derive the backward channel estimator with the optimal…
Distributed MIMO (D-MIMO) has emerged as a key architecture for future sixth-generation (6G) networks, enabling cooperative transmission across spatially distributed access points (APs). However, most existing studies rely on idealized…
In wireless communication systems, the use of multiple antennas at both the transmitter and receiver is a widely known method for improving both reliability and data rates, as it increases the former through transmit or receive diversity…
Massive MIMO, also known as very-large MIMO or large-scale antenna systems, is a new technique that potentially can offer large network capacities in multi-user scenarios. With a massive MIMO system, we consider the case where a base…
By employing the lens antenna array, beamspace MIMO can utilize beam selection to reduce the number of required RF chains in mmWave massive MIMO systems without obvious performance loss. However, to achieve the capacityapproaching…
Acquiring the channel state information from limited and noisy observations at pilot positions is critical for wireless multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. In this paper, we view…
We propose a channel estimation protocol to determine the uplink channel state information (CSI) at the base station for an intelligent reflecting surface (IRS) based wireless communication. More specifically, we develop a channel…
THz band enabled large scale massive MIMO (M-MIMO) is considered as a key enabler for the 6G technology, given its enormous bandwidth and for its low latency connectivity. In the large-scale M-MIMO configuration, enlarged array aperture and…
Multiple input multiple output (MIMO) system transmission is a popular diversity technique to improve the reliability of a communication system where transmitter, communication channel and receiver are the important elements. Data…
In large scale dynamic wireless networks, the amount of overhead caused by channel estimation (CE) is becoming one of the main performance bottlenecks. This is due to the large number users whose channels should be estimated, the user…
We introduce a novel physical layer scheme for single user Multiple-Input Multiple-Output (MIMO) communications based on unsupervised deep learning using an autoencoder. This method extends prior work on the joint optimization of physical…