Related papers: Message Passing Algorithm for Distributed Downlink…
Low-density parity-check codes are attractive for high throughput applications because of their low decoding complexity per bit, but also because all the codeword bits can be decoded in parallel. However, achieving this in a circuit…
This paper considers two base stations (BSs) powered by renewable energy serving two users cooperatively. With different BS energy arrival rates, a fractional joint transmission (JT) strategy is proposed, which divides each transmission…
This paper presents an energy-efficient downlink precoding scheme with the objective of maximizing system energy efficiency in a multi-cell massive MIMO system. The proposed precoding design jointly considers the issues of power control,…
In this paper, a practical precoding method for the downlink of filter bank multicarrier-based (FBMC-based) massive multiple-input multiple-output (MIMO) is developed. The proposed method includes a two-stage precoder consisting of a…
We consider distributed optimization problems in which a group of agents are to collaboratively seek the global optimum through peer-to-peer communication networks. The problem arises in various application areas, such as resource…
This study proposes an adaptive experimental design framework for a channel-simulation-based base station (BS) design that supports the joint optimization of transmission power and placement. We consider a system in which multiple…
This study proposes an orthogonal frequency division multiplexing (OFDM) based scheme to achieve interference-free backscatter communications (BC) in a symbiotic radio system. In specific, we propose three frequency shift keying (FSK) based…
This paper considers the problem of downlink localization and user equipments (UEs) tracking with an adaptive procedure for a range of distances. We provide the base station (BS) with two signaling schemes and the UEs with two localization…
Networked low Earth orbit (LEO) satellite constellations enabled by inter-satellite links offer a promising path toward ubiquitous broadband non-terrestrial services. However, fast orbital motion induces frequent scheduling updates and…
Semantic communication (SemCom) is emerging as a key technology for future sixth-generation (6G) systems. Unlike traditional bit-level communication (BitCom), SemCom directly optimizes performance at the semantic level, leading to superior…
Coordinated multipoint (CoMP) communications are considered for the fifth-generation (5G) small-cell networks as a tool to improve the high data rates and the cell-edge throughput. The average achievable rates of the small-cell base…
We propose a new iterative optimization method for the {\bf Data-Fitting} (DF) problem in Machine Learning, e.g. Neural Network (NN) training. The approach relies on {\bf Graphical Model} (GM) representation of the DF problem, where…
Matrix-parametrized models, including multiclass logistic regression and sparse coding, are used in machine learning (ML) applications ranging from computer vision to computational biology. When these models are applied to large-scale ML…
Matrix-parametrized models, including multiclass logistic regression and sparse coding, are used in machine learning (ML) applications ranging from computer vision to computational biology. When these models are applied to large-scale ML…
Matrix factorization is a very common machine learning technique in recommender systems. Bayesian Matrix Factorization (BMF) algorithms would be attractive because of their ability to quantify uncertainty in their predictions and avoid…
Federated Learning is a machine learning setting where the goal is to train a high-quality centralized model while training data remains distributed over a large number of clients each with unreliable and relatively slow network…
In this paper, we study power allocation for secure communication in a multiuser multiple-input single-output (MISO) downlink system with simultaneous wireless information and power transfer. The receivers are able to harvest energy from…
The main challenges in designing downlink coordinated multicast beamforming in massive multiple-input multiple output (MIMO) cellular networks are the complex computational solutions and significant fronthaul overhead for centralized…
This paper studies the ergodic rate performance of regularized zero-forcing (RZF) precoding in the downlink of a multi-user multiple-input single-output (MISO) system, where the channel between the base station (BS) and each user is modeled…
Many compression techniques have been proposed to reduce the communication overhead of Federated Learning training procedures. However, these are typically designed for compressing model updates, which are expected to decay throughout…