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Related papers: Cooperative MIMO Precoding with Distributed CSI: A…

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Efficient uplink processing in distributed massive multiple-input multiple-output (D-mMIMO) systems requires both effective local combining and scalable decoding to significantly mitigate inter-user interference. Recent zero-forcing…

Networking and Internet Architecture · Computer Science 2026-03-17 Mohd Saif Ali Khan , Karthik RM , Samar Agnihotri

Base station (BS) cooperation can turn unwanted interference to useful signal energy for enhancing system performance. In the cooperative downlink, zero-forcing beamforming (ZFBF) with a simple scheduler is well known to obtain nearly the…

Information Theory · Computer Science 2013-03-27 Chao-Kai Wen , Jung-Chieh Chen , Kai-Kit Wong , Pangan Ting

We consider the "coded cooperative data exchange problem" for general graphs. In this problem, given a graph G=(V,E) representing clients in a broadcast network, each of which initially hold a (not necessarily disjoint) set of information…

Information Theory · Computer Science 2012-02-10 Mira Gonen , Michael Langberg

Massive multi-input multiple-out (MIMO) is a key ingredient in improving the spectral efficiencies for next-generation cellular systems. Thanks to the channel reciprocity, in time-division-duplexing mode, each base station (BS) can acquire…

Signal Processing · Electrical Eng. & Systems 2021-07-30 Deokhwan Han , Namyoon Lee

The performance of centralized and distributed massive MIMO deployments are analyzed for indoor office scenarios. The distributed deployments use one of the following precoding methods: (1) local precoding with local channel state…

Information Theory · Computer Science 2018-01-11 Stefan Dierks , Gerhard Kramer , Berthold Panzner , Wolfgang Zirwas

Federated learning protects users' data privacy through sharing users' local model parameters (instead of raw data) with a server. However, when massive users train a large machine learning model through federated learning, the dynamically…

Networking and Internet Architecture · Computer Science 2023-10-02 Ningning Ding , Lin Gao , Jianwei Huang

Federated Learning (FL) is an increasingly popular machine learning paradigm in which multiple nodes try to collaboratively learn under privacy, communication and multiple heterogeneity constraints. A persistent problem in federated…

Machine Learning · Computer Science 2022-02-24 Elnur Gasanov , Ahmed Khaled , Samuel Horváth , Peter Richtárik

This paper considers the implementation of Tomlinson-Harashima (TH) precoding for multiuser MIMO systems based on quantized channel state information (CSI) at the transmitter side. Compared with the results in [1], our scheme applies to…

Information Theory · Computer Science 2014-08-05 Liang Sun , Ming Lei

Microgrids are autonomous clusters of generators, storage units and loads. Special requirements arise in interconnected operation: control schemes that do not require individual microgrids to disclose information about their internal…

Optimization and Control · Mathematics 2024-07-04 T. Alissa Schenck , Christian A. Hans

This paper addresses the problem of exploiting interference among simultaneous multiuser transmissions in the downlink of multiple-antenna systems. Using symbol-level precoding, a new approach towards addressing the multiuser interference…

Information Theory · Computer Science 2016-11-17 Maha Alodeh , Symeon Chatzinotas , Bjorn Ottersten

We present sufficient conditions for multicasting a set of correlated sources over cooperative networks. We propose joint source-Wyner-Ziv encoding/sliding-window decoding scheme, in which each receiver considers an ordered partition of…

Information Theory · Computer Science 2009-01-16 Mohammad Hossein Yassaee , Mohammad Reza Aref

Caching of popular content during off-peak hours is a strategy to reduce network loads during peak hours. Recent work has shown significant benefits of designing such caching strategies not only to deliver part of the content locally, but…

Information Theory · Computer Science 2016-06-14 Nikhil Karamchandani , Urs Niesen , Mohammad Ali Maddah-Ali , Suhas Diggavi

Linear precoding is a relatively simple method of MIMO signaling that can also be optimal in certain special cases. This paper is dedicated to high-SNR analysis of MIMO linear precoding. The Diversity-Multiplexing Tradeoff (DMT) of a number…

Information Theory · Computer Science 2012-02-27 Ahmed Hesham Mehana , Aria Nosratinia

This paper quantifies the benefits and limitations of cooperative communications by providing a statistical analysis of the downlink in network multiple-input multiple-output (MIMO) systems. We consider an idealized model where the…

Information Theory · Computer Science 2016-08-24 Kianoush Hosseini , Wei Yu , Raviraj S. Adve

Extremely large-scale multiple-input multiple-output (XL-MIMO) promises to provide ultrahigh data rates in millimeter-wave (mmWave) and Terahertz (THz) spectrum. However, the spherical-wavefront wireless transmission caused by large…

Information Theory · Computer Science 2023-08-16 Xu Shi , Jintao Wang , Zhi Sun , Jian Song

Cell-free (CF) multiuser multiple-input multiple-output (MU-MIMO) systems are an emerging technology that provides service simultaneously to multiple users but suffers from multiuser interference (MUI). In this work, we propose a robust…

Information Theory · Computer Science 2025-02-27 A. Flores , R. de Lamare

This paper studies the problem of linear precoding for multiple-input multiple-output (MIMO) communication channels employing finite-alphabet signaling. Existing solutions typically suffer from high computational complexity due to costly…

Information Theory · Computer Science 2021-11-08 Maksym A. Girnyk

In this paper we examine a number of deployment issues which arise from practical considerations in massive multiple-input-multiple-output (MIMO) systems. We show both spatial correlation and line-of-sight (LOS) introduce an interference…

Information Theory · Computer Science 2015-03-04 Callum T. Neil , Mansoor Shafi , Peter J. Smith , Pawel A. Dmochowski

We study cost-effective communication strategies that can be used to improve the performance of distributed learning systems in resource-constrained environments. For distributed learning in sequential decision making, we propose a new…

Machine Learning · Computer Science 2020-04-15 Udari Madhushani , Naomi Ehrich Leonard

Network based on distributed caching of content is a new architecture to alleviate the ongoing explosive demands for rate of multi-media traffic. In caching networks, coded caching is a recently proposed technique that achieves significant…

Information Theory · Computer Science 2017-10-16 Qifa Yan , Xiaohu Tang , Qingchun Chen