We consider multi-antenna wireless systems aided by reconfigurable intelligent surfaces (RIS). RIS presents a new physical layer technology for improving coverage and energy efficiency intelligently controlling the propagation environment. In practice however, achieving anticipated gains of requires accurate channel estimation. Recent attempts to solve this problem have considered least-squares...

Wireless channels bring in new challenges unforeseen in wireline environments, e.g., ISI becomes time varying. Traditionally the equalizers (which nullify the ISI) were designed to optimize their performance (e.g., MSE) as a standalone component (equalizers were designed using sufficient amount of training that is transmitted prior to the actual data transmission). This approach was well suited...

We investigate the problem of representing information measures in terms moments underlying random variables. First, we derive polynomial approximations conditional expectation operator. then apply these to bound best mean-square error achieved by a estimator—referred here as PMMSE. In Gaussian channels, PMMSE coincides with minimum (MMSE) if and only input is either or constant, i.e., c...

Decision-directed adaptive receivers suffer performance degradation on time varying and intersymbol interference-impaired links because of two major problems: the use of predicted channel estimates due to the unavoidable decision delay of any detector, and the unreliability of hard decisions used for channel estimation and tracking. It is shown here that combining a recursive nonlinear symbol e...

Our work is developed in context of studing Massive MIMO a 5G context. The aim to optimize spectral efficiency several users hyper system during Uplink communication multi-cell contaminated pilot environment, using new type precoders called single cell-minimum mean square eroor (S-MMSE) and multicell-minimum (MMMSE). Indeed, we address two key well-known issues massive multiuser (MU-MIMO) envir...

Abstract At cellular wireless communication systems, channel estimation (CE) is one of the key techniques that are used in Orthogonal Frequency Division Multiplexing modulation (OFDM). The most common methods Decision‐Directed Channel Estimation, Pilot-Assisted Estimation (PACE) and blind estimation. Among them, PACE commonly has a steadier performance. Applying deep learning (DL) CE getting in...

We address pilot-symbol aided channel estimation (PACE) for OFDM. To reduce the complexity of the optimum minimum mean squared error (MMSE) estimator, two sub-optimum estimators are investigated. First, an estimator utilizing an FIR filter of reduced length. The filter coefficients are determined according to a Wiener filter with model mismatch, i.e. the channel conditions which are assumed to ...

We consider the problem of robust state estimation in the presence of integrity attacks. There are m sensors monitoring a dynamical process. Subject to the integrity attacks, p out of m measurements can be arbitrarily manipulated. The classical approach such as the MMSE estimation in the literature may not provide a reliable estimate under this so-called (p,m)-sparse attack. In this work, we pr...

In this paper a time-frequency estimator for enhancement of noisy speech signals in the DFT domain is introduced. This estimator is based on modelling and filtering the temporal trajectories of the DFT components of noisy speech signal using Kalman filters. The time-varying trajectory of the DFT components of speech is modelled by a low order autoregressive process incorporated in the state equ...