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179
Fading Channels: InformationTheoretic And Communications Aspects
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... In this paper we review the most peculiar and interesting informationtheoretic and communications features of fading channels. We first describe the statistical models of fading channels which are frequently used in the analysis and design of communication systems. Next, we focus on the information ..."
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Cited by 416 (3 self)
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In this paper we review the most peculiar and interesting informationtheoretic and communications features of fading channels. We first describe the statistical models of fading channels which are frequently used in the analysis and design of communication systems. Next, we focus on the information theory of fading channels, by emphasizing capacity as the most important performance measure. Both singleuser and multiuser transmission are examined. Further, we describe how the structure of fading channels impacts code design, and finally overview equalization of fading multipath channels.
A Network Information Theory for Wireless Communication: Scaling Laws and Optimal Operation
 IEEE Transactions on Information Theory
, 2002
"... How much information can be carried over a wireless network with a multiplicity of nodes? What are the optimal strategies for information transmission and cooperation among the nodes? We obtain sharp information theoretic scaling laws under some conditions. ..."
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Cited by 369 (18 self)
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How much information can be carried over a wireless network with a multiplicity of nodes? What are the optimal strategies for information transmission and cooperation among the nodes? We obtain sharp information theoretic scaling laws under some conditions.
Breaking Spectrum Gridlock with Cognitive Radios: An Information Theoretic Perspective
, 2008
"... Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified b ..."
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Cited by 244 (3 self)
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Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well as a priori rules about spectrum usage, cognitive radio systems seek to underlay, overlay or interweave the cognitive radios ’ signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today’s crowded spectrum.
On coding for reliable communication over packet networks
, 2008
"... We consider the use of random linear network coding in lossy packet networks. In particular, we consider the following simple strategy: nodes store the packets that they receive and, whenever they have a transmission opportunity, they send out coded packets formed from random linear combinations of ..."
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Cited by 223 (37 self)
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We consider the use of random linear network coding in lossy packet networks. In particular, we consider the following simple strategy: nodes store the packets that they receive and, whenever they have a transmission opportunity, they send out coded packets formed from random linear combinations of stored packets. In such a strategy, intermediate nodes perform additional coding yet do not decode nor wait for a block of packets before sending out coded packets. Moreover, all coding and decoding operations have polynomial complexity. We show that, provided packet headers can be used to carry an amount of sideinformation that grows arbitrarily large (but independently of payload size), random linear network coding achieves packetlevel capacity for both single unicast and single multicast connections and for both wireline and wireless networks. This result holds as long as packets received on links arrive according to processes that have average rates. Thus packet losses on links may exhibit correlations in time or with losses on other links. In the special case of Poisson traffic with i.i.d. losses, we give error exponents that quantify the rate of decay of the probability of error with coding delay. Our analysis of random linear network coding shows not only that it achieves packetlevel capacity, but also that the propagation of packets carrying “innovative ” information follows the propagation of jobs through a queueing network, thus implying that fluid flow models yield good approximations.
Mathematical modelling of the Internet
"... Modern communication networks are able to respond to randomly uctuating demands and failures by adapting rates, by rerouting traffic and by reallocating resources. They are able to do this so well that, in many respects, largescale networks appear as coherent, almost intelligent, organisms. The des ..."
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Cited by 189 (0 self)
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Modern communication networks are able to respond to randomly uctuating demands and failures by adapting rates, by rerouting traffic and by reallocating resources. They are able to do this so well that, in many respects, largescale networks appear as coherent, almost intelligent, organisms. The design and control of such networks present challenges of a mathematical, engineering and economic nature. This paper outlines how mathematical models are being used to address current issues concerning the stability and fairness of rate control algorithms for the Internet.
Simultaneous Routing and Resource Allocation via Dual Decomposition
, 2004
"... In wireless data networks the optimal routing of data depends on the link capacities which, in turn, are determined by the allocation of communications resources (such as transmit powers and bandwidths) to the links. The optimal performance of the network can only be achieved by simultaneous optimi ..."
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Cited by 172 (7 self)
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In wireless data networks the optimal routing of data depends on the link capacities which, in turn, are determined by the allocation of communications resources (such as transmit powers and bandwidths) to the links. The optimal performance of the network can only be achieved by simultaneous optimization of routing and resource allocation. In this paper, we formulate the simultaneous routing and resource allocation problem and exploit problem structure to derive ef£cient solution methods. We use a capacitated multicommodity flow model to describe the data ¤ows in the network. We assume that the capacity of a wireless link is a concave and increasing function of the communications resources allocated to the link, and the communications resources for groups of links are limited. These assumptions allow us to formulate the simultaneous routing and resource allocation problem as a convex optimization problem over the network flow variables and the communications variables. These two sets of variables are coupled only through the link capacity constraints. We exploit this separable structure by dual decomposition. The resulting solution method attains the optimal coordination of data routing in the network layer and resource allocation in the radio control layer via pricing on the link capacities.
Network Information Flow with Correlated Sources
 TO APPEAR IN THE IEEE TRANSACTIONS ON INFORMATION THEORY
, 2005
"... Consider the following network communication setup, originating in a sensor networking application we refer to as the “sensor reachback ” problem. We have a directed graph G = (V, E), where V = {v0v1...vn} and E ⊆ V × V. If (vi, vj) ∈ E, then node i can send messages to node j over a discrete memor ..."
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Cited by 94 (9 self)
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Consider the following network communication setup, originating in a sensor networking application we refer to as the “sensor reachback ” problem. We have a directed graph G = (V, E), where V = {v0v1...vn} and E ⊆ V × V. If (vi, vj) ∈ E, then node i can send messages to node j over a discrete memoryless channel (Xij, pij(yx), Yij), of capacity Cij. The channels are independent. Each node vi gets to observe a source of information Ui (i = 0...M), with joint distribution p(U0U1...UM). Our goal is to solve an incast problem in G: nodes exchange messages with their neighbors, and after a finite number of communication rounds, one of the M + 1 nodes (v0 by convention) must have received enough information to reproduce the entire field of observations (U0U1...UM), with arbitrarily small probability of error. In this paper, we prove that such perfect reconstruction is possible if and only if H(USUS c) < i∈S,j∈S c for all S ⊆ {0...M}, S = ∅, 0 ∈ S c. Our main finding is that in this setup a general source/channel separation theorem holds, and that Shannon information behaves as a classical network flow, identical in nature to the flow of water in pipes. At first glance, it might seem surprising that separation holds in a
Fast Broadcasting and Gossiping in Radio Networks
, 2000
"... We establish an O(n log² n) upper bound on the time for deterministic distributed broadcasting in multihop radio networks with unknown topology. This nearly matches the known lower bound of n log n). The fastest previously known algorithm for this problem works in time O(n 3=2 ). Using our broa ..."
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Cited by 91 (7 self)
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We establish an O(n log² n) upper bound on the time for deterministic distributed broadcasting in multihop radio networks with unknown topology. This nearly matches the known lower bound of n log n). The fastest previously known algorithm for this problem works in time O(n 3=2 ). Using our broadcasting algorithm, we develop an O(n 3=2 log 2 n) algorithm for gossiping in the same network model.
A Scalable Model for Channel Access Protocols in Multihop Ad Hoc Networks
, 2004
"... A new modeling framework is introduced for the analytical study of medium access control (MAC) protocols operating in multihop ad hoc networks. The model takes into account the e#ect of physicallayer parameters on the success of transmissions, the MAC protocol on the likelihood that nodes can acces ..."
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Cited by 84 (5 self)
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A new modeling framework is introduced for the analytical study of medium access control (MAC) protocols operating in multihop ad hoc networks. The model takes into account the e#ect of physicallayer parameters on the success of transmissions, the MAC protocol on the likelihood that nodes can access the channnel, and the connectivity of nodes in the network. A key feature of the model is that nodes can be modeled individually, i.e., it allows a pernode setup of many layerspecific parameters. Moreover, no spatial probability distribution or a particular arrangement of nodes is assumed; the model allows the computation of individual (pernode) performance metrics for any given network topology and radio channel model. To show the applicability of the modeling framework, we model multihop ad hoc networks using the IEEE 802.11 distributed coordination function and validate the results from the model with discreteevent simulations in Qualnet. The results show that our model predicts results that are very close to those attained by simulations, and requires seconds to complete compared to several hours of simulation time.
Exploiting Decentralized Channel State Information for Random Access
, 2002
"... We study the use of channel state information for random access in fading channels. Traditionally, random access protocols have been designed by assuming simple models for the physical layer where all users are symmetric and there is no notion of channel state. We introduce a reception model that ta ..."
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Cited by 82 (18 self)
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We study the use of channel state information for random access in fading channels. Traditionally, random access protocols have been designed by assuming simple models for the physical layer where all users are symmetric and there is no notion of channel state. We introduce a reception model that takes into account the channel states of various users. Under the assumption that each user has access to his channel state information (CSI), we propose a variant of Slotted ALOHA protocol for medium access control, where the transmission probability is allowed to be a function of the CSL The function is called the transmission control scheme. Assuming the finite user infinite buffer model we derive expressions for the maximum stable throughput of the system. We introduce the notion of asymptotic stable throughput (AST) that is the maximum stable throughput as the number of users goes to infinity. We consider two types of transmission control namely population independent transmission control (PITC) where the transmission control is not a function of the size of the network and population dependent transmission control where the transmission control is a function of the size of the network. We obtain expressions for the AST achievable with PITC. For population dependent transmission control, we introduce a particular transmission control that can potentially lead to significant gains in AST. For both PITC and PDTC, we show that the effect of transmission control is equivalent to changing the probability distribution of the channel state. The theory is then applied to CDMA networks with Linear Minimum Mean Square Error (LMMSE) receivers and Matched Filters (MF) to illustrate the effectiveness of utilizing channel state. It is shown that through the use of channel state, with an...