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Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks
TLDR
We show that much better scaling than multihop can be achieved in dense networks, as well as in extended networks with low attenuation. Expand
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Advances and Open Problems in Federated Learning
TLDR
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server, while keeping the training data decentralized. Expand
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Universally near-optimal online power control for energy harvesting nodes
  • Dor Shaviv, Ayfer Özgür
  • Computer Science, Mathematics
  • IEEE International Conference on Communications…
  • 2 November 2015
TLDR
We consider online power control for an energy harvesting system with random i.i.d. energy arrivals and a finite size battery and prove that it is universally near-optimal for all parameter values. Expand
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Hierarchical Cooperation Achieves Linear Capacity Scaling in Ad Hoc Networks
TLDR
In this paper, we show that the capacity of ad hoc wireless networks with n nodes in a fixed area actually scales linearly with n. Expand
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Phase Retrieval via Incremental Truncated Wirtinger Flow
TLDR
We present an algorithm to solve a nonconvex formulation of the phase retrieval problem, that we call $\textit{Incremental Truncated Wirtinger Flow}$. Expand
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Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication
TLDR
We consider an energy-harvesting communication system where a transmitter powered by an exogenous energy arrival process and equipped with a finite battery of size Bmax communicates over a discrete-time AWGN channel. Expand
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Information theoretic operating regimes of large wireless networks
TLDR
We propose a new scaling law formulation for wireless networks that allows us to develop a theory that is analogous to the point-to-point case; the network capacity is both power- and bandwidth-limited. Expand
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Approximately achieving Gaussian relay network capacity with lattice codes
TLDR
We show that the same approximation result can be established by using lattices for transmission and quantization along with structured mappings at the relays. Expand
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Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints
TLDR
We consider parameter estimation in distributed networks, where each sensor in the network observes an independent sample from an underlying distribution and has $k$ bits to communicate its sample to a centralized processor which computes an estimate of a desired parameter. Expand
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Capacity of the AWGN channel with random battery recharges
TLDR
We consider communication over the AWGN channel with a transmitter whose battery is recharged with RF energy transfer at random times known to the receiver. Expand
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