no code implementations • 30 Nov 2023 • Eunsun Kim, Ian P. Roberts, Jeffrey G. Andrews
We carefully model and study the potential downlink interference between the two systems and investigate how strategic satellite selection may be used by Kuiper to serve its ground users while also protecting Starlink ground users.
no code implementations • 23 Jan 2023 • Manan Gupta, Sandeep Chinchali, Paul Varkey, Jeffrey G. Andrews
Cellular networks are becoming increasingly heterogeneous with higher base station (BS) densities and ever more frequency bands, making BS selection and band assignment key decisions in terms of rate and coverage.
no code implementations • 27 Oct 2022 • Ezgi Tekgul, Thomas Novlan, Salam Akoum, Jeffrey G. Andrews
We propose a novel framework for optimizing antenna parameter settings in a heterogeneous cellular network.
no code implementations • 14 Oct 2022 • Ian P. Roberts, Aditya Chopra, Thomas Novlan, Sriram Vishwanath, Jeffrey G. Andrews
Characterizing self-interference is essential to the design and evaluation of in-band full-duplex communication systems.
no code implementations • 15 Jul 2022 • Ian P. Roberts, Aditya Chopra, Thomas Novlan, Sriram Vishwanath, Jeffrey G. Andrews
Modern millimeter wave (mmWave) communication systems rely on beam alignment to deliver sufficient beamforming gain to close the link between devices.
no code implementations • 14 Jul 2022 • Eunsun Kim, Ian P. Roberts, Jeffrey G. Andrews
The extension of wide area wireless connectivity to low-earth orbit (LEO) satellite communication systems demands a fresh look at the effects of in-orbit base stations, sky-to-ground propagation, and cell planning.
no code implementations • 22 Jun 2022 • Ian P. Roberts, Sriram Vishwanath, Jeffrey G. Andrews
This work develops LoneSTAR, a novel enabler of full-duplex millimeter wave (mmWave) communication systems through the design of analog beamforming codebooks.
no code implementations • 15 Jun 2022 • Ian P. Roberts, Aditya Chopra, Thomas Novlan, Sriram Vishwanath, Jeffrey G. Andrews
We present measurements and analysis of self-interference in multi-panel millimeter wave (mmWave) full-duplex communication systems at 28 GHz.
1 code implementation • 25 May 2022 • Akash Doshi, Manan Gupta, Jeffrey G. Andrews
More importantly, our proposed framework has the potential to be trained online using real noisy pilot measurements, is not restricted to a specific channel model and can even be utilized for a federated OTA design of a dataset generator from noisy data.
no code implementations • 5 Mar 2022 • Aditya Chopra, Ian P. Roberts, Thomas Novlan, Jeffrey G. Andrews
We present measurements of the 28 GHz self-interference channel for full-duplex sectorized multi-panel millimeter wave (mmWave) systems, such as integrated access and backhaul.
no code implementations • 10 Dec 2021 • Manan Gupta, Ian P. Roberts, Jeffrey G. Andrews
We use this to characterize the network-level improvements seen when upgrading from conventional HD IAB nodes to FD ones by deriving closed-form expressions for (i) latency gain of FD-IAB over HD-IAB and (ii) the maximum number of hops that a HD- and FD-IAB network can support while satisfying latency and throughput targets.
no code implementations • 7 Oct 2021 • Akash Doshi, Jeffrey G. Andrews
The increasing number of wireless devices operating in unlicensed spectrum motivates the development of intelligent adaptive approaches to spectrum access that go beyond traditional carrier sensing.
no code implementations • 5 Oct 2021 • Akash Doshi, Srinivas Yerramalli, Lorenzo Ferrari, Taesang Yoo, Jeffrey G. Andrews
The increasing number of wireless devices operating in unlicensed spectrum motivates the development of intelligent adaptive approaches to spectrum access.
no code implementations • 24 Sep 2021 • Akash Doshi, Jeffrey G. Andrews
The use of unlicensed spectrum for cellular systems to mitigate spectrum scarcity has led to the development of intelligent adaptive approaches to spectrum access that improve upon traditional carrier sensing and listen-before-talk methods.
no code implementations • 29 Jul 2021 • Eunsun Kim, Ian P. Roberts, Peter A. Iannucci, Jeffrey G. Andrews
The coming extension of cellular technology to base-stations in low-earth orbit (LEO) requires a fresh look at terrestrial 3GPP channel models.
no code implementations • 28 Jul 2021 • Yuqiang Heng, Jianhua Mo, Jeffrey G. Andrews
Beam alignment - the process of finding an optimal directional beam pair - is a challenging procedure crucial to millimeter wave (mmWave) communication systems.
no code implementations • 27 May 2021 • Ian P. Roberts, Hardik B. Jain, Sriram Vishwanath, Jeffrey G. Andrews
This paper develops a novel methodology for designing analog beamforming codebooks for full-duplex millimeter wave (mmWave) transceivers, the first such codebooks to the best of our knowledge.
no code implementations • 22 Dec 2020 • Eren Balevi, Jeffrey G. Andrews
Communication at high carrier frequencies such as millimeter wave (mmWave) and terahertz (THz) requires channel estimation for very large bandwidths at low SNR.
no code implementations • 21 Dec 2020 • Ian P. Roberts, Jeffrey G. Andrews, Sriram Vishwanath
To prevent self-interference from saturating the receiver of a full-duplex device having limited dynamic range, our design addresses saturation on a per-antenna and per-RF chain basis.
no code implementations • 19 Oct 2020 • Yi Zhang, Akash Doshi, Rob Liston, Wai-tian Tan, Xiaoqing Zhu, Jeffrey G. Andrews, Robert W. Heath
In this work, we develop DeepWiPHY, a deep learning-based architecture to replace the channel estimation, common phase error (CPE) correction, sampling rate offset (SRO) correction, and equalization modules of IEEE 802. 11ax based orthogonal frequency division multiplexing (OFDM) receivers.
no code implementations • 13 Sep 2020 • Ian P. Roberts, Jeffrey G. Andrews, Hardik B. Jain, Sriram Vishwanath
Equipping millimeter wave (mmWave) systems with full-duplex capability would accelerate and transform next-generation wireless applications and forge a path for new ones.
no code implementations • 24 Jun 2020 • Eren Balevi, Akash Doshi, Ajil Jalal, Alexandros Dimakis, Jeffrey G. Andrews
This paper presents a novel compressed sensing (CS) approach to high dimensional wireless channel estimation by optimizing the input to a deep generative network.
1 code implementation • 2 Oct 2019 • Faris B. Mismar, Ahmad AlAmmouri, Ahmed Alkhateeb, Jeffrey G. Andrews, Brian L. Evans
Our proposed classifier-based band switching policy instead exploits spatial and spectral correlation between radio frequency signals in different bands based on knowledge of the UE location.
no code implementations • 24 Sep 2019 • Eren Balevi, Jeffrey G. Andrews
It is empirically shown that this design gives nearly the same performance as to the hypothetically perfectly trained autoencoder, and we also provide a theoretical proof of why that is so.
no code implementations • 15 Mar 2019 • Eren Balevi, Jeffrey G. Andrews
Our results illustrate that the proposed algorithm approaches the performance of the multi-agent RL, which requires millions of trials, with hundreds of online trials, assuming relatively low environmental dynamics, and performs much better than a single agent RL.
1 code implementation • 5 Dec 2018 • Chiranjib Saha, Harpreet S. Dhillon, Naoto Miyoshi, Jeffrey G. Andrews
Owing to its flexibility in modeling real-world spatial configurations of users and base stations (BSs), the Poisson cluster process (PCP) has recently emerged as an appealing way to model and analyze heterogeneous cellular networks (HetNets).
Information Theory Networking and Internet Architecture Information Theory
no code implementations • 2 Nov 2018 • Eren Balevi, Jeffrey G. Andrews
For channel estimation (using pilots), we design a novel generative supervised deep neural network (DNN) that can be trained with a reasonable number of pilots.