An Extremal Inequality Motivated by Multiterminal Information-Theoretic Problems

Li, Shipeng; Viswanath, Pramod

doi:10.1109/tit.2007.894680

Cited by 197 publications

(252 citation statements)

References 19 publications

Supporting

Mentioning

247

Contrasting

Order By: Relevance

“…Therefore, we do not need the extremal inequality [13] to prove Theorem 2. Remark 9: The sum-rate capacity for a Z-IC with a = 0, 0 < b < 1 is a special case of Theorem 2 since (15) is satisfied.…”

Section: Sum-rate Capacity For Noisy Interferencementioning

confidence: 99%

See 1 more Smart Citation

Outer bound and noisy-interference sum-rate capacity for symmetric Gaussian interference channels

Shang

Kramer²,

Chen

2008

2008 42nd Annual Conference on Information Sciences and Systems

View full text Add to dashboard Cite

A new outer bound on the capacity region of Gaussian interference channels is developed. The bound combines and improves existing genie-aided methods and is shown to give the sum-rate capacity for Gaussian interference channel with noisy interference as defined in this paper. Specifically, it is shown that if the channel coefficients and power constraints satisfy a simple condition then single-user detection at each receiver is sum-rate optimal, i.e., treating the interference as noise incurs no loss in performance. Finally, we generalize the noisy interference sum-rate capacity to m-user interference channels.

show abstract

Section: Sum-rate Capacity For Noisy Interferencementioning

confidence: 99%

“…The bound generalizes to asymmetric channels which will be treated in a subsequent paper. The new bounds are based on a genieaided approach and a recently proposed extremal inequality [13]. Unlike the genie-aided method used in [10, Theorem 1], neither receiver is required to decode the messages from the other transmitter.…”

Section: Introductionmentioning

confidence: 99%

Outer bound and noisy-interference sum-rate capacity for symmetric Gaussian interference channels

Shang

Kramer²,

Chen

2008

2008 42nd Annual Conference on Information Sciences and Systems

View full text Add to dashboard Cite

show abstract

“…It should be noted that the optimality conditions (6)-(9) are different from the outer-bound derivation by Liu and Viswanath [8]. Actually the outer bound in [8] only deals with the case that B *…”

Section: Theorem 31 For the Vector Gaussian One-helper Problem With mentioning

confidence: 96%

“…Another argument is that our optimality conditions can always be constructed for scalar Gaussian sources while the outer bound in [8] is not always tight in this case (which depends on µ).…”

Section: Theorem 31 For the Vector Gaussian One-helper Problem With mentioning

confidence: 99%

“…Later on, this technique was recognized to be useful in solving multi-terminal vector Gaussian source and channel coding problems. For the vector Gaussian one-helper DSC problem, Liu and Viswanath used the channel enhancement technique and derived an outer bound to the rate region [8]. In [9], Rahman and Wagner also used the channel enhancement technique and determined a portion of the boundary of the rate region.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the Rate Region of the Vector Gaussian One-Helper Distributed Source-Coding Problem

Zhang

2011

2011 Data Compression Conference

View full text Add to dashboard Cite

In this paper we consider the rate region of the vector Gaussian one-helper distributed source coding problem. In particular, we derive optimality conditions under which a weighted sum rate is minimum by using a contradiction-based argument. When the sources are specified to be scalar, the optimality conditions can always be constructed for any weighted sum rate. In the derivation of the optimality conditions, we introduce a new concept of "source enhancement", which can be viewed as a dual to the wellknown "channel enhancement" technique. In particular, source enhancement refers to the operation of increasing the covariance matrix of a Gaussian source in a partial ordering sense. This new technique makes the derivation of the optimality conditions straightforward.

show abstract

Physical layer security in broadcast networks

Liang

Poor

Shamai

2009

Security Comm Networks

View full text Add to dashboard Cite

This paper reviews the information theoretic characterization of security in broadcast channels, in which a transmitter has both public and confidential messages intended for multiple receivers. All messages must be successfully received by their intended receivers, and the confidential messages must be kept as secret as possible from non-intended recipients. Various scenarios are considered in the context of two-user broadcast channels, for which known results on the secrecy capacity region are reviewed and corresponding coding schemes for achieving rates in these regions are described.Security issues arise naturally in broadcast channels due to the open nature of such communication. Each receiver is able to receive signals that contain all information flows from the transmitter, although sometimes with weak signal strength. Hence, some receivers may decode information flows that are not intended for them. However, confidential information flows should be kept as secret as possible from non-intended receivers. This requires that the transmitter employ techniques to guarantee such security constraints. Information theoretic approaches have been developed to achieve secure communication, initially over broadcast channels in References [1,2] and later on over other communication channels

show abstract

An Extremal Inequality Motivated by Multiterminal Information-Theoretic Problems

Cited by 197 publications

References 19 publications

Outer bound and noisy-interference sum-rate capacity for symmetric Gaussian interference channels

Outer bound and noisy-interference sum-rate capacity for symmetric Gaussian interference channels

On the Rate Region of the Vector Gaussian One-Helper Distributed Source-Coding Problem

Physical layer security in broadcast networks

Contact Info

Product

Resources

About