activity
20052020
most citedCombining Reinforcement Learning with Model Predictive Control for On-Ramp Merging

4 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2020★ 4 cited

Combining Reinforcement Learning with Model Predictive Control for On-Ramp Merging

Joseph Lubars, Harsh Gupta, Sandeep Chinchali +4

We consider the problem of designing an algorithm to allow a car to autonomously merge on to a highway from an on-ramp. Two broad classes of techniques have been proposed to solve…

cs.IT2016★ 1 cited

Secure Content Distribution in Vehicular Networks

Viet T. Nguyen, Jubin Jose, Xinzhou Wu +1

Dedicated short range communication (DSRC) relies on secure distribution to vehicles of a certificate revocation list (CRL) for enabling security protocols. CRL distribution utiliz…

cs.NI2015★ 1 cited

Inter-Vehicle Range Estimation from Periodic Broadcasts

Urs Niesen, Venkatesan N. Ekambaram, Jubin Jose +1

Dedicated short-range communication (DSRC) enables vehicular communication using periodic broadcast messages. We propose to use these periodic broadcasts to perform inter-vehicle r…

eess.SY2015★ 1 cited

Distributed Rate and Power Control in Vehicular Networks

Jubin Jose, Chong Li, Xinzhou Wu +2

The focus of this paper is on the rate and power control algorithms in Dedicated Short Range Communication (DSRC) for vehicular networks. We first propose a utility maximization fr…

cs.NI2011

Distributed Power Control and Coding-Modulation Adaptation in Wireless Networks using Annealed Gibbs Sampling

Shan Zhou, Xinzhou Wu, Lei Ying

In wireless networks, the transmission rate of a link is determined by received signal strength, interference from simultaneous transmissions, and available coding-modulation schem…

cs.IT2005

Asymptotic Behavior of Error Exponents in the Wideband Regime

X. Wu, R. Srikant

In this paper, we complement Verdú's work on spectral efficiency in the wideband regime by investigating the fundamental tradeoff between rate and bandwidth when a constraint is im…