相关论文: Low-Complexity Robust Adaptive Beamforming Algorit…

The efficient estimation of an approximate model order is very important for real applications with multi-dimensional data if the observed low-rank data is corrupted by additive noise. In this paper, we present a novel robust method for…

This paper proposes a robust reduced-rank scheme for adaptive beamforming based on joint iterative optimization (JIO) of adaptive filters. The scheme provides an efficient way to deal with filters with large number of elements. It consists…

This chapter presents reduced-rank linearly constrained minimum variance (LCMV) algorithms based on the concept of joint iterative optimization of parameters. The proposed reduced-rank scheme is based on a constrained robust joint iterative…

We introduce a new linearly constrained minimum variance (LCMV) beamformer that combines the set-membership (SM) technique with the conjugate gradient (CG) method, and develop a low-complexity adaptive filtering algorithm for beamforming.…

In this paper, a binaural beamforming algorithm for hearing aid applications is introduced.The beamforming algorithm is designed to be robust to some error in the estimate of the target speaker direction. The algorithm has two main…

Adapting large pre-trained language models to downstream tasks often entails fine-tuning millions of parameters or deploying costly dense weight updates, which hinders their use in resource-constrained environments. Low-rank Adaptation…

Transmit beamforming design is a fundamental problem in integrated sensing and communication (ISAC) systems. Numerous methods have been proposed to jointly optimize key performance metrics such as the signal-to-interference-plus-noise ratio…

We consider a network of agents that locate themselves in an environment through sensor measurements and aim to transmit a message signal to a base station via collaborative beamforming. The agents' sensor measurements result in…

Feature matching is a fundamental and crucial process in visual SLAM, and precision has always been a challenging issue in feature matching. In this paper, based on a multi-level fine matching strategy, we propose a new feature matching…

VARs are often estimated with Bayesian techniques to cope with model dimensionality. The posterior means define a class of shrinkage estimators, indexed by hyperparameters that determine the relative weight on maximum likelihood estimates…

In millimeter wave (mmWave) systems, it is challenging to ensure the reliable connectivity of communications due to its sensitivity to the presence of blockages. In order to improve the robustness of the mmWave system under the presence of…

In this paper, we investigate the network power minimization problem for the multicast cloud radio access network (Cloud-RAN) with imperfect channel state information (CSI). The key observation is that network power minimization can be…

Low-complexity Bayes-optimal memory approximate message passing (MAMP) is an efficient signal estimation algorithm in compressed sensing and multicarrier modulation. However, achieving replica Bayes optimality with MAMP necessitates a…

The Straight-Through Estimator (STE) is widely used for back-propagating gradients through the quantization function, but the STE technique lacks a complete theoretical understanding. We propose an alternative methodology called…

We investigate the problem of reconfigurable intelligent surface (RIS)-aided near-field localization of a user equipment (UE) served by a base station (BS) under phase-dependent amplitude variations at each RIS element. Through a…

Integrated sensing and communication (ISAC) systems may face a heavy computation burden since the sensory data needs to be further processed. This paper studies a novel system that integrates sensing, communication, and computation, aiming…

This paper investigates integrated localization and communication in a multi-cell system and proposes a coordinated beamforming algorithm to enhance target localization accuracy while preserving communication performance. Within this…

To address the complexities of spatial non-stationary (SnS) effects and spherical wave propagation in near-field channel estimation (CE) for extremely large-scale multiple-input multiple-output (XL-MIMO) systems, this paper proposes an…

A reconfigurable intelligent surface (RIS) enhanced non-orthogonal multiple access assisted backscatter communication (RIS-NOMABC) system is considered. A joint optimization problem over power reflection coefficients and phase shifts is…

The need for fast sparse optimization is emerging, e.g., to deal with large-dimensional data-driven problems and to track time-varying systems. In the framework of linear sparse optimization, the iterative shrinkage-thresholding algorithm…