Related papers: Detecting Abrupt Changes in Channel Covariance Mat…
This work investigates the problem of spatial covariance matrix estimation in a millimeter-wave (mmWave) hybrid multiple-input multiple-output (MIMO) system with an emphasis on the basis-mismatch effect. The basis mismatch is prevalent in…
This paper proposes a channel estimation method for hybrid wideband multiple-input-multiple-output (MIMO) systems in high-frequency bands, including millimeter-wave (mmWave) and sub-terahertz (sub-THz), in the presence of beam squint…
Massive multiple-input multiple-output (MIMO) communications using low-resolution analog-to-digital converters (ADCs) is a promising technology for providing high spectral and energy efficiency with affordable hardware cost and power…
High dimensional piecewise stationary graphical models represent a versatile class for modelling time varying networks arising in diverse application areas, including biology, economics, and social sciences. There has been recent work in…
Multiple-input multiple-output (MIMO) system is the key technology for long term evolution (LTE) and 5G. The information detection problem at the receiver side is in general difficult due to the imbalance of decoding complexity and decoding…
Wireless communication technology has seen a remarkably fast evolution due to its capability to provide a quality, reliable and high-speed data transmission amongst the users. However, transmission of information in wireless channels is…
Millimeter (mm) wave massive MIMO has the potential for delivering orders of magnitude increases in mobile data rates, with compact antenna arrays providing narrow steerable beams for unprecedented levels of spatial reuse. A fundamental…
Massive multiple-input multiple-output (MIMO) systems use antenna arrays with a large number of antenna elements to serve many different users simultaneously. The large number of antennas in the system makes, however, the channel state…
Millimeter wave provides a very promising approach for meeting the ever-growing traffic demand in next generation wireless networks. To utilize this band, it is crucial to obtain the channel state information in order to perform beamforming…
The acquisition of channel state information (CSI) is essential in MIMO-OFDM communication systems. Data-aided enhanced receivers, by incorporating domain knowledge, effectively mitigate performance degradation caused by imperfect CSI,…
The knowledge of the downlink (DL) channel spatial covariance matrix at the BS is of fundamental importance for large-scale array systems operating in frequency division duplexing (FDD) mode. In particular, this knowledge plays a key role…
We consider the problem of downlink training and channel estimation in frequency division duplex (FDD) massive MIMO systems, where the base station (BS) equipped with a large number of antennas serves a number of single-antenna users…
In this paper, we consider the use of deep neural networks in the context of Multiple-Input-Multiple-Output (MIMO) detection. We give a brief introduction to deep learning and propose a modern neural network architecture suitable for this…
In this paper, we investigate the problem of jamming detection and channel estimation during multi-user uplink beam training under random pilot jamming attacks in beamspace massive multi-input-multi-output (MIMO) systems. For jamming…
The downlink channel covariance matrix (CCM) acquisition is the key step for the practical performance of massive multiple-input and multiple-output (MIMO) systems, including beamforming, channel tracking, and user scheduling. However, this…
Channel knowledge map (CKM) is a promising paradigm for environment-aware communications by establishing a deterministic mapping between physical locations and channel parameters. Existing CKM construction methods focus on quasi-static…
A simple scheme for communication over MIMO broadcast channels is introduced which adopts the lattice reduction technique to improve the naive channel inversion method. Lattice basis reduction helps us to reduce the average transmitted…
The online monitoring data in distribution networks contain rich information on the running states of the networks. By leveraging the data, this paper proposes a spatio-temporal correlation analysis approach for anomaly detection and…
Millimeter wave provides a promising approach for meeting the ever-growing traffic demand in next generation wireless networks. It is crucial to obtain relatively accurate channel state information so that beamforming/combining can be…
Knowledge of second-order statistics of channels (e.g. in the form of covariance matrices) is crucial for the acquisition of downlink channel state information (CSI) in massive MIMO systems operating in the frequency division duplexing…