Lower Bounds for Noisy Wireless Networks using Sampling Algorithms

2008 49th Annual IEEE Symposium on Foundations of Computer Science ◽

10.1109/focs.2008.72 ◽

2008 ◽

Cited By ~ 1

Author(s):

Chinmoy Dutta ◽

Jaikumar Radhakrishnan

Keyword(s):

Wireless Networks ◽

Lower Bounds ◽

Sampling Algorithms

Download Full-text

Cramer-Rao lower bounds for nonhybrid and hybrid localisation techniques in wireless networks

European Transactions on Telecommunications ◽

10.1002/ett.1530 ◽

2011 ◽

pp. n/a-n/a ◽

Cited By ~ 2

Author(s):

Mohamed Laaraiedh ◽

Stéphane Avrillon ◽

Bernard Uguen

Keyword(s):

Wireless Networks ◽

Lower Bounds

Download Full-text

Sequential Sampling Algorithms: Unified Analysis and Lower Bounds

Stochastic Algorithms: Foundations and Applications - Lecture Notes in Computer Science ◽

10.1007/3-540-45322-9_12 ◽

2001 ◽

pp. 173-188 ◽

Cited By ~ 2

Author(s):

Ricard Gavaldà ◽

Osamu Watanabe

Keyword(s):

Lower Bounds ◽

Sequential Sampling ◽

Sampling Algorithms

Download Full-text

Theoretical Estimators and Lower-Bounds for Receiver-to-Receiver Time Synchronization in Multi-Hop Wireless Networks

IET International Conference on Wireless Communications and Applications (ICWCA 2012) ◽

10.1049/cp.2012.2084 ◽

2012 ◽

Author(s):

D. Djenouri

Keyword(s):

Wireless Networks ◽

Lower Bounds ◽

Time Synchronization

Download Full-text

On lower bounds for MAC layer contention in CSMA/CA-based wireless networks

Proceedings of the 2005 joint workshop on Foundations of mobile computing - DIALM-POMC '05 ◽

10.1145/1080810.1080814 ◽

2005 ◽

Cited By ~ 5

Author(s):

Frank A. Zdarsky ◽

Ivan Martinovic ◽

Jens B. Schmitt

Keyword(s):

Wireless Networks ◽

Lower Bounds ◽

Mac Layer

Download Full-text

Lower bounds for sampling algorithms for estimating the average

Information Processing Letters ◽

10.1016/0020-0190(94)00171-t ◽

1995 ◽

Vol 53 (1) ◽

pp. 17-25 ◽

Cited By ~ 31

Author(s):

Ran Canetti ◽

Guy Even ◽

Oded Goldreich

Keyword(s):

Lower Bounds ◽

Sampling Algorithms

Download Full-text

Capacity Scaling of Wireless Networks with Inhomogeneous Node Density: Lower Bounds

IEEE INFOCOM 2009 - The 28th Conference on Computer Communications ◽

10.1109/infcom.2009.5062110 ◽

2009 ◽

Cited By ~ 21

Author(s):

G. Alfano ◽

M. Garetto ◽

E. Leonardi

Keyword(s):

Wireless Networks ◽

Lower Bounds ◽

Node Density ◽

Capacity Scaling

Download Full-text

Large deviation principles for connectable receivers in wireless networks

Advances in Applied Probability ◽

10.1017/apr.2016.65 ◽

2016 ◽

Vol 48 (4) ◽

pp. 1061-1094 ◽

Cited By ~ 2

Author(s):

Christian Hirsch ◽

Benedikt Jahnel ◽

Paul Keeler ◽

Robert I. A. Patterson

Keyword(s):

Wireless Networks ◽

Importance Sampling ◽

Point Processes ◽

Large Deviation Principle ◽

Large Deviation ◽

Empirical Measure ◽

Deviation Principle ◽

Large Deviation Principles ◽

Sampling Algorithms ◽

Connectivity Threshold

AbstractWe study large deviation principles for a model of wireless networks consisting of Poisson point processes of transmitters and receivers. To each transmitter we associate a family of connectable receivers whose signal-to-interference-and-noise ratio is larger than a certain connectivity threshold. First, we show a large deviation principle for the empirical measure of connectable receivers associated with transmitters in large boxes. Second, making use of the observation that the receivers connectable to the origin form a Cox point process, we derive a large deviation principle for the rescaled process of these receivers as the connection threshold tends to 0. Finally, we show how these results can be used to develop importance sampling algorithms that substantially reduce the variance for the estimation of probabilities of certain rare events such as users being unable to connect.

Download Full-text