On the Capacity of Gaussian Weak Interference Channels with Degraded Message sets

Wu, Wei; Vishwanath, Sriram; Arapostathis, Ari

doi:10.1109/ciss.2006.286410

Cited by 42 publications

(75 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, the cognitive radio channel shown in Figure 3.9 lets the source nodes cooperate by having one of the nodes aware of the message of the other node. The capacity region of this channel is known in some cases [89,189]. The best cooperative schemes use both superposition coding and a sophisticated coding method known as dirty paper coding.…”

Section: Other Models and Methodsmentioning

confidence: 99%

Cooperative Communications

Kramer¹,

2006

View full text Add to dashboard Cite

This article reviews progress in cooperative communication networks. Our survey is by no means exhaustive. Instead, we assemble a representative sample of recent results to serve as a roadmap for the area. Our emphasis is on wireless networks, but many of the results apply to cooperation in wireline networks and mixed wireless/wireline networks. We intend our presentation to be a tutorial for the reader who is familiar with information theory concepts but has not actively followed the field. For the active researcher, this contribution should serve as a useful digest of significant results. This article is meant to encourage readers to find new ways to apply the ideas of network cooperation and should make the area sufficiently accessible to network designers to contribute to the advancement of networking practice. Overview IntroductionThe classic representation of a communication network is a graph, as in Figure 1.1, with a set of nodes and edges. The nodes usually represent devices such as a router, a wireless access point, or a mobile telephone. The edges usually represent communication links or channels, for example a fiber-optic cable or a wireless link. Both the devices and the channels may have constraints on their operation. For example, a router might have limited processing power, or perhaps it can accept data from only a few of its ports simultaneously. A fiber-optic link has a limited bandwidth (which can be quite large!). A wireless phone, on the other hand, has limited battery resources and likely wishes to conserve energy. A wireless link can have rapid time variations arising from mobility and multipath propagation of signals. Some of these properties are collected in Table 1.1 and are described in more detail in this text.The purpose of a communication network is to enable the exchange of messages between its nodes. These messages, as generated by an application, are organized into data packets. In the traditional model of a network, the nodes operate as store-and-forward packet routers that transmit packets over point-to-point links. However, this model is unnecessarily restrictive as it ignores two important possibilities:• Node Coding: Nodes can combine, or encode, any of their received information and symbol streams.• Broadcasting: Nodes overhear the transmissions of other nodes from which they are not required to receive messages.Node coding is possible in any network, while the ability to overhear transmissions is a property of the physical communication channel. In particular, wireless devices inherently broadcast information in that a signal to a particular receiving node can be overheard by other nodes. Typically, the wireless nodes treat these overheard signals as interference and the system provides mechanisms to mitigate this interference. For example, many second generation cellular phones employ code division multiple access (CDMA) to permit signal decoding in 274 Overview the presence of interference [185]. As a second example, 802.11× wireless LANs employ a media access...

show abstract

Section: Other Models and Methodsmentioning

confidence: 99%

Cooperative Communications

Kramer¹,

2006

View full text Add to dashboard Cite

show abstract

“…By careful encoding, the channel with interference noncausally known to the transmitter, but not the receiver, may be made equivalent to an interference-free channel, at no power penalty. When using an encoding strategy that properly exploits this asymmetric message knowledge at the transmitters, the region (d) of Figure 1 is achievable and in certain cases corresponds to the capacity region of this channel [17], [18]. The encoding strategy used assumes both transmitters use random Gaussian codebooks.…”

Section: Cognitive Transmission (Using Asymmetric Transmitter Side Inmentioning

confidence: 99%

Cognitive radio networks

Devroye

Vu²,

Tarokh

2008

IEEE Signal Process. Mag.

231

113

View full text Add to dashboard Cite

show abstract

“…Such a model generically characterizes some realistic communication scenarios taking place in cognitive radio channels [1], [2] or in wireless sensor networks over a correlated field [3], [4], which we illustrate in Figs. 1(a) and 1(b).…”

Section: Introductionmentioning

confidence: 99%

“…It has been also shown in [1,Corollary 2] that, an improved achievable rate region can be attained by time-sharing between the early derived rate region and a so called fully-cooperative rate point achieved by letting sender 2 use all its power to transmit sender 1' messages. A different coding scheme was adopted in [2] and [3], in which neither of the senders splits its message into two sub-messages, and receiver 2 does not decode any transmitted information from sender 1. Since sender 2 knows what sender 1 wishes to transmit, sender 2 is allowed to: 1) apply the Gel'fand-Pinsker coding to encode its own message; and 2) partially cooperate with sender 1 using superposition coding.…”

Section: Introductionmentioning

confidence: 99%

On the Achievable Rate Regions for Interference Channels With Degraded Message Sets

Jiang

Yan

2008

IEEE Trans. Inform. Theory

View full text Add to dashboard Cite

The interference channel with degraded message sets (IC-DMS) refers to a communication model in which two senders attempt to communicate with their respective receivers simultaneously through a common medium, and one of the senders has complete and a priori (non-causal) knowledge about the message being transmitted by the other. A coding scheme that collectively has advantages of cooperative coding, collaborative coding, and dirty paper coding, is developed for such a channel. With resorting to this coding scheme, achievable rate regions of the IC-DMS in both discrete memoryless and Gaussian cases are derived, which, in general, include several previously known rate regions. Numerical examples for the Gaussian case demonstrate that in the high-interference-gain regime, the derived achievable rate regions offer considerable improvements over these existing results.

show abstract

On the Capacity of Gaussian Weak Interference Channels with Degraded Message sets

Cited by 42 publications

References 17 publications

Cooperative Communications

Cooperative Communications

Cognitive radio networks

On the Achievable Rate Regions for Interference Channels With Degraded Message Sets

Contact Info

Product

Resources

About