21 accepted papers
Pilot contamination (PC) is a well-known problem that affects massive multiple-input multiple-output (MIMO) systems. When frequency and pilots are reused between different cells, PC constitutes one of the main bottlenecks of the system's performance. In this paper, we propose a method based on the v…
This paper investigates using side information in minimum mean square error (MMSE) estimation. We propose a direction-of-arrival (DoA)-aided two-stage channel estimation technique that utilizes information about the dominant direction of the channel. To this end, the decomposition of the MMSE channe…
Rate splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) are two prospective technologies for improving the spectral and energy efficiency in future wireless communication systems. In this work, we investigate a rate splitting (RS) technique for an RIS-aided system in the p…
We propose to use Tomlinson-Harashima Precoding (THP) for the reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output (MIMO) broadcast channel where we assume a line of sight (LOS) connection between the base station (BS) and the RIS. In this scenario, nonlinear precoding, like…
Diffusion models (DMs) as generative priors have recently shown great potential for denoising tasks but lack theoretical understanding with respect to their mean square error (MSE) optimality. This paper proposes a novel denoising strategy inspired by the structure of the MSE-optimal conditional mea…
Learning the site-specific distribution of the wireless channel within a particular environment of interest is essential to exploit the full potential of machine learning (ML) for wireless communications and radar applications. Generative modeling offers a promising framework to address this problem…
Recent cooperative perception datasets have played a crucial role in advancing smart mobility applications by enabling information exchange between intelligent agents, helping to overcome challenges such as occlusions and improving overall scene understanding. While some existing real-world datasets…
In this work, we propose to utilize a variational autoencoder (VAE) for channel estimation (CE) in underdetermined (UD) systems. The basis of the method forms a recently proposed concept in which a VAE is trained on channel state information (CSI) data and used to parameterize an approximation to th…
In this work, we propose two methods that utilize data symbols in addition to pilot symbols for improved channel estimation quality in a multi-user system, so-called semi-blind channel estimation. To this end, a subspace is estimated based on all received symbols and utilized to improve the estimati…
This work addresses the fundamental linear inverse problem in compressive sensing (CS) by introducing a new type of regularizing generative prior. Our proposed method utilizes ideas from classical dictionary-based CS and, in particular, sparse Bayesian learning (SBL), to integrate a strong regulariz…
One way to improve the estimation of time varying channels is to incorporate knowledge of previous observations. In this context, Dynamical VAEs (DVAEs) build a promising deep learning (DL) framework which is well suited to learn the distribution of time series data. We introduce a new DVAE architec…
This paper investigates a channel estimator based on Gaussian mixture models (GMMs). We fit a GMM to given channel samples to obtain an analytic probability density function (PDF) which approximates the true channel PDF. Then, a conditional mean estimator (CME) corresponding to this approximating PD…
The model order of a wireless channel plays an important role for a variety of applications in communications engineering, e.g., it represents the number of resolvable incident wave-fronts with non-negligible power incident from a transmitter to a receiver. Areas such as direction of arrival estimat…
We consider channel estimation for systems equipped with an intelligent reflecting surface (IRS). We develop least squares (LS) and minimum mean square error (MMSE) estimation for such systems. The appropriate system models are developed and we also discuss the parameters which can be estimated in s…
In this paper, we present a machine learning approach for estimating the number of incident wavefronts in a direction of arrival scenario. In contrast to previous works, a multilayer neural network with a cross-entropy objective is trained. Furthermore, we investigate an online training procedure th…
We study the capabilities of a filter configuration where a linear filter is applied to an improper vector, and the output is processed by scalar widely linear filters afterwards. Assuming that this filter configuration is used to estimate a vector of interest from a noisy observation, we aim at fin…
MIMO Radio-over-Copper (MIMO-RoC) is a transport system for indoor coverage that leverages the pre-existing building's copper cabling infrastructure. In MIMO-RoC, the overall channel from the Base Band Units (BBU) to the end-user is the cascade of a MIMO-radio over a MIMO-cable channel and the analo…
Energy efficiency is besides higher data rates a key to success of the next generation copper access technology, G.fast [1]. Power consumption targets are not only driven by government requirements, but also by the need for access nodes without local power supply, which are fed from the subscriber v…
It is well-known that the use of improper signaling schemes can be beneficial in interference-limited networks. Here we consider an underlay cognitive radio scenario, where a multi-antenna primary user is protected by an interference temperature constraint that ensures a prescribed rate requirement.…
Interference coupling in heterogeneous networks introduces the inherent non-convexity to the network resource optimization problem, hindering the development of effective solutions. A new framework based on multi-pattern formulation has been proposed in this paper to study the energy efficient strat…
We evaluate the performance of a set of low complexity successive interference cancellation (SIC) detection algorithms in comparison to optimal maximum a-posteriori probability (MAP) detection and low complexity linear filter detection in a Turbo multiple-input multiple-output (Turbo-MIMO) system. W…