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20102023
most citedConvexity Conditions for 802.11 WLANs

6 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SI2023

Backward and Forward Inference in Interacting Independent-Cascade Processes: A Scalable and Convergent Message-Passing Approach

Nouman Khan, Kangle Mu, Mehrdad Moharrami +1

We study the problems of estimating the past and future evolutions of two diffusion processes that spread concurrently on a network. Specifically, given a known network $G=(V, \ove…

math.OC20232 cited

Cooperative Multi-Agent Constrained POMDPs: Strong Duality and Primal-Dual Reinforcement Learning with Approximate Information States

Nouman Khan, Vijay Subramanian

We study the problem of decentralized constrained POMDPs in a team-setting where the multiple non-strategic agents have asymmetric information. Strong duality is established for th…

math.OC2023

Nonlinear Consensus for Distributed Optimization

Hsu Kao, Vijay Subramanian

Distributed optimization algorithms have been studied extensively in the literature; however, underlying most algorithms is a linear consensus scheme, i.e. averaging variables from…

cs.IT2017

The Impact of Small-Cell Bandwidth Requirements on Strategic Operators

Cheng Chen, Randall A. Berry, Michael L. Honig +1

Small-cell deployment in licensed and unlicensed spectrum is considered to be one of the key approaches to cope with the ongoing wireless data demand explosion. Compared to traditi…

cs.NI20126 cited

Convexity Conditions for 802.11 WLANs

Vijay G. Subramanian, Douglas J. Leith

In this paper we characterise the maximal convex subsets of the (non-convex) rate region in 802.11 WLANs. In addition to being of intrinsic interest as a fundamental property of 80…

cs.NI20102 cited

Max-min Fairness in 802.11 Mesh Networks

Douglas J. Leith, Qizhi Cao, Vijay G. Subramanian

In this paper we build upon the recent observation that the 802.11 rate region is log-convex and, for the first time, characterise max-min fair rate allocations for a large class o…