Related papers: Interference-Cancellation-Based Channel Knowledge …
Inverse problems and, in particular, inferring unknown or latent parameters from data are ubiquitous in engineering simulations. A predominant viewpoint in identifying unknown parameters is Bayesian inference where both prior information…
This paper studies the intelligent reflecting surface (IRS) deployment optimization problem for IRS-enabled integrated sensing and communications (ISAC) systems, in which multiple IRSs are strategically deployed at candidate locations to…
Fundamental limits of the cognitive interference channel (CIC) with two pairs of transmitter-receiver has been under exploration for several years. In this paper, we study the discrete memoryless cognitive interference channel (DM-CIC) in…
In this work, we study a family of wireless channel simulation models called geometry-based stochastic channel models (GBSCMs). Compared to more complex ray-tracing simulation models, GBSCMs do not require an extensive characterization of…
Channel gain maps (CGMs) enable propagation-aware services in edge-intelligent wireless communication networks, while diffusion-based CGM construction is memory intensive for on-device training or adaptation. This letter proposes…
We propose a Bayesian neural network-based continual learning algorithm using Variational Inference, aiming to overcome several drawbacks of existing methods. Specifically, in continual learning scenarios, storing network parameters at each…
In this letter, the channel estimation problem is studied for wireless communication systems assisted by large intelligent surface. Due to features of assistant channel, channel estimation (CE) problem for the investigated system is shown…
We investigate how to exploit intermittent feedback for interference management by studying the two-user Gaussian interference channel (IC). We approximately characterize (within a universal constant) the capacity region for the Gaussian IC…
We study the capacity region of two-user erasure interference channels with local delayed channel state information at the transmitters. In our model, transmitters have local mismatched outdated knowledge of the channel gains. We propose a…
This paper presents a statistical block fading channel model for multiuser massive MIMO system. The proposed channel model is evolved from correlation based stochastic channel model (CBSCM) but in addition to the properties of CBSCM, it has…
This work studies the problems of channel estimation and beamforming for active reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) communication, incorporating the mutual coupling (MC) effect through an…
As network deployments become denser, interference arises as a dominant performance degradation factor. To confront with this trend, Long Term Evolution (LTE) incorporated features aiming at enabling cooperation among different base…
In this paper, we present an interference model for cognitive radio (CR) networks employing power control, contention control or hybrid power/contention control schemes. For the first case, a power control scheme is proposed to govern the…
Interference alignment has emerged as a powerful tool in the analysis of multi-user networks. Despite considerable recent progress, the capacity region of the Gaussian K-user interference channel is still unknown in general, in part due to…
We propose a novel, flexible, and efficient framework for designing Concept Bottleneck Models (CBMs) that enables practitioners to explicitly encode and extend their prior knowledge and beliefs about the concept-concept ($C-C$) and…
We propose a novel algorithm to estimate the channel covariance matrix of a desired user in multiuser massive MIMO systems. The algorithm uses only knowledge of the array response and rough knowledge of the angular support of the incoming…
Extending terrestrial networks into low-altitude airspace is a practical way to support aerial services, and accurate low-altitude radio maps are essential for characterizing terrestrial base station (BS) coverage and guiding system design.…
Accurate quantum channel parameter estimation is essential for effective information reconciliation in continuous-variable quantum key distribution (CV-QKD). However, conventional maximum likelihood (ML) estimators rely on a large amount of…
This paper proposes an environment-aware near-field channel estimation framework for integrated sensing and communication (ISAC) systems equipped with extremely large-scale antenna arrays (ELAAs). The proposed framework jointly exploits…
Filter bank multi carrier (FBMC) is considered a competitive waveform candidate for 5G that can replace orthogonal frequency division multiplexing (OFDM). However, channel estimation (CE) is a big challenge in FBMC because it suffers from…