相关论文: DNN-Enabled Multi-User Beamforming for Throughput …

This paper addresses coordinated downlink beamforming optimization in multicell time-division duplex (TDD) systems where a small number of parameters are exchanged between cells but with no data sharing. With the goal to reach the point on…

The exponential growth of wireless devices and stringent reliability requirements of emerging applications demand fundamental improvements in distributed channel access mechanisms for unlicensed bands. Current Wi-Fi systems, which rely on…

In this thesis, we study the downlink multiuser scheduling and power allocation problem for systems with simultaneous wireless information and power transfer (SWIPT). In the first part of the thesis, we focus on multiuser scheduling. We…

We consider the problem of optimal link scheduling in large-scale wireless ad hoc networks. We specifically aim for the maximum long-term average performance, subject to a minimum transmission requirement for each link to ensure fairness.…

In this paper, we revisit the widely known performance anomaly that results in severe network utility degradation in WiFi networks when nodes use diverse modulation and coding schemes. The proportional-fair allocation was shown to mitigate…

We study the beamforming design for multiuser systems with simultaneous wireless information and power transfer (SWIPT). Employing a practical non-linear energy harvesting (EH) model, the design is formulated as a non-convex optimization…

In this paper, wireless video transmission to multiple users under total transmission power and minimum required video quality constraints is studied. In order to provide the desired performance levels to the end-users in real-time video…

Weighted sum rate maximization (WSRM) for precoder optimization effectively balances performance and fairness among users. Recent studies have demonstrated the potential of deep learning in precoder optimization for sum rate maximization.…

In this paper, we propose a state-of-the-art downlink communication transceiver design for transmissive reconfigurable metasurface (RMS)-enabled simultaneous wireless information and power transfer (SWIPT) networks. Specifically, a feed…

The advantages of graph neural networks (GNNs) in leveraging the graph topology of wireless networks have drawn increasing attentions. This paper studies the GNN-based learning approach for the sum-rate maximization in multiple-user…

In this paper, we design a deep learning based resource allocation framework, in the form of an auction, for simultaneous information and power transfer from a hybrid access point (AP) to information devices and energy harvesting devices,…

Transmit beamforming is a versatile technique for signal transmission from an array of $N$ antennas to one or multiple users [1]. In wireless communications, the goal is to increase the signal power at the intended user and reduce…

We propose a novel data-driven approach to allocate transmit power for federated learning (FL) over interference-limited wireless networks. The proposed method is useful in challenging scenarios where the wireless channel is changing during…

This is the first treatise on multi-user (MU) beamforming designed for achieving long-term rate-fairness in fulldimensional MU massive multi-input multi-output (m-MIMO) systems. Explicitly, based on the channel covariances, which can be…

MIMO interference network optimization is important for increasingly crowded wireless communication networks. We provide a new algorithm, named Dual Link algorithm, for the classic problem of weighted sum-rate maximization for MIMO…

In this paper, we examine the fundamental trade-off between radiated power and achieved throughput in wireless multi-carrier, multiple-input and multiple-output (MIMO) systems that vary with time in an unpredictable fashion (e.g. due to…

A two-user downlink network aided by a reconfigurable intelligent surface is considered. The weighted sum signal to interference plus noise ratio maximization and the sum rate maximization models are presented, where the precoding vectors…

The persistent challenge of bias in machine learning models necessitates robust solutions to ensure parity and equal treatment across diverse groups, particularly in classification tasks. Current methods for mitigating bias often result in…

It is well-known that the problem of finding the optimal beamformers in massive multiple-input multiple-output (MIMO) networks is challenging because of its non-convexity, and conventional optimization based algorithms suffer from high…

Wireless Power Transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things, Radio Frequency identification (RFID) networks, etc. Although there has been some progress…