相关论文: The One-Bit Null Space Learning Algorithm and its …

This paper provides a survey of the state-of-the-art information theoretic analysis for overlay multi-user (more than two pairs) cognitive networks and reports new capacity results. In an overlay scenario, cognitive / secondary users share…

Machine unlearning (MU) is to make a well-trained model behave as if it had never been trained on specific data. In today's over-parameterized models, dominated by neural networks, a common approach is to manually relabel data and fine-tune…

One-bit compressive sensing is concerned with the accurate recovery of an underlying sparse signal of interest from its one-bit noisy measurements. The conventional signal recovery approaches for this problem are mainly developed based on…

We investigate the coexistence of underlay spectrum sharing in cell-free massive multiple-input multiple-output (MIMO) systems. A primary system with geographically distributed primary access points (P-APs) serves a multitude of primary…

In this paper, we consider the precoder design for an underloaded or critically loaded downlink multi-user multiple-input multiple-output (MIMO) communication system. We propose novel precoding and decoding schemes which enhance system…

This paper proposes a secure users oriented multiple-input and single-output (MISO) non-orthogonal multiple access (NOMA) downlink transmission scheme, where multiple legitimate users are categorized as quality of service (QoS)-required…

Learning the embedding space, where semantically similar objects are located close together and dissimilar objects far apart, is a cornerstone of many computer vision applications. Existing approaches usually learn a single metric in the…

We propose NullSpaceNet, a novel network that maps from the pixel level input to a joint-nullspace (as opposed to the traditional feature space), where the newly learned joint-nullspace features have clearer interpretation and are more…

In this paper, we present a novel approach for joint activity detection (AD), channel estimation (CE), and data detection (DD) in uplink grant-free non-orthogonal multiple access (NOMA) systems. Our approach employs an iterative and…

With the increasing number of wireless communication systems and the demand for bandwidth, the wireless medium has become a congested and contested environment. Operating under such an environment brings several challenges, especially for…

We propose a method for MIMO decoding when channel state information (CSI) is unknown to both the transmitter and receiver. The proposed method requires some structure in the transmitted signal for the decoding to be effective, in…

Sharing radar spectrum with communication systems is an emerging area of research. Deploying commercial wireless communication services in radar bands give wireless operators the much needed additional spectrum to meet the growing bandwidth…

The recovery of block-sparse signals with unknown structural patterns remains a fundamental challenge in structured sparse signal reconstruction. By proposing a variance transformation framework, this paper unifies existing pattern-based…

This paper focuses on the analysis and optimization of a class of linear one-bit precoding schemes for a downlink massive MIMO system under Rayleigh fading channels. The considered class of linear one-bit precoding is fairly general,…

This paper considers the joint impact of non-linear hardware impairments at the base station (BS) and user equipments (UEs) on the uplink performance of single-cell massive MIMO (multiple-input multiple-output) in practical Rician fading…

Learning with Noisy Labels (LNL) aims to improve the model generalization when facing data with noisy labels, and existing methods generally assume that noisy labels come from known classes, called closed-set noise. However, in real-world…

The fast adoption of Massive MIMO for high-throughput communications was enabled by many research contributions mostly relying on infinite-blocklength information-theoretic bounds. This makes it hard to assess the suitability of Massive…

We consider the problem of estimating a signal subspace in the presence of interference that contaminates some proportion of the received observations. Our emphasis is on detecting the contaminated observations so that the signal subspace…

This work analyzes the performance of an underlay cognitive radio based decode-and-forward mixed multiple-input multiple-output (MIMO) radio frequency/free space optical (RF/FSO) cooperative relay system with multiple mobile secondary and…

Link-adaptation (LA) is one of the most important aspects of wireless communications where the modulation and coding scheme (MCS) used by the transmitter is adapted to the channel conditions in order to meet a certain target error-rate. In…