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Interference alignment and the degrees of freedom for the Kuser interference channel
 IEEE Transactions on Information Theory
, 2008
"... Abstract—For the fully connected K user wireless interference channel where the channel coefficients are timevarying and are drawn from a continuous distribution, the sum capacity is characterized as C(SNR) = K 2 log(SNR) +o(log(SNR)). Thus, the K user timevarying interference channel almost sure ..."
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Cited by 425 (17 self)
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Abstract—For the fully connected K user wireless interference channel where the channel coefficients are timevarying and are drawn from a continuous distribution, the sum capacity is characterized as C(SNR) = K 2 log(SNR) +o(log(SNR)). Thus, the K user timevarying interference channel almost surely has K=2 degrees of freedom. Achievability is based on the idea of interference alignment. Examples are also provided of fully connected K user interference channels with constant (not timevarying) coefficients where the capacity is exactly achieved by interference alignment at all SNR values. Index Terms—Capacity, degrees of freedom, interference alignment, interference channel, multipleinput–multipleoutput (MIMO), multiplexing. I.
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.
Cognitive Radio: An InformationTheoretic Perspective”, http://arxiv.org/abs/cs/0604107 32 A. Lapidoth, “Nearestneighbor decoding for additive nonGaussian noise channels
 IEEE Transactions on Information Theory
, 1996
"... We consider a communication scenario in which the primary and the cognitive radios wish to communicate to different receivers, subject to mutual interference. In the model that we use, the cognitive radio has noncausal knowledge of the primary radio’s codeword. We characterize the largest rate at w ..."
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Cited by 177 (1 self)
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We consider a communication scenario in which the primary and the cognitive radios wish to communicate to different receivers, subject to mutual interference. In the model that we use, the cognitive radio has noncausal knowledge of the primary radio’s codeword. We characterize the largest rate at which the cognitive radio can reliably communicate under the constraint that (i) no rate degradation is created for the primary user, and (ii) the primary receiver uses a singleuser decoder just as it would in the absence of the cognitive radio. The result holds in a “low interference ” regime in which the cognitive radio is closer to its receiver than to the primary receiver. In this regime, our results are subsumed by the results derived in a concurrent and independent work [24]. We also demonstrate that, in a “high interference ” regime, multiuser decoding at the primary receiver is optimal from the standpoint of maximal jointly achievable rates for the primary and cognitive users. Index Terms — Cognitive radio, Costa precoding, dirtypaper coding, interference channel, spectral reuse, wireless networks.
Discrete memoryless interference and broadcast channels with confidential messages: secrecy rate regions
 IEEE Transactions on Information Theory
, 2008
"... Abstract — Discrete memoryless interference and broadcast channels in which independent confidential messages are sent to two receivers are considered. Confidential messages are transmitted to each receiver with perfect secrecy, as measured by the equivocation at the other receiver. In this paper, w ..."
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Cited by 161 (12 self)
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Abstract — Discrete memoryless interference and broadcast channels in which independent confidential messages are sent to two receivers are considered. Confidential messages are transmitted to each receiver with perfect secrecy, as measured by the equivocation at the other receiver. In this paper, we derive inner and outer bounds for the achievable rate regions for these two communication systems. I.
Gaussian interference network: Sum capacity . . .
, 2008
"... Establishing the capacity region of a Gaussian interference network is an open problem in information theory. Recent progress on this problem has led to the characterization of the capacity region of a general two user Gaussian interference channel within one bit. In this paper, we develop new, impr ..."
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Cited by 133 (5 self)
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Establishing the capacity region of a Gaussian interference network is an open problem in information theory. Recent progress on this problem has led to the characterization of the capacity region of a general two user Gaussian interference channel within one bit. In this paper, we develop new, improved outer bounds on the capacity region. Using these bounds, we show that treating interference as noise achieves the sum capacity of the two user Gaussian interference channel in a low interference regime, where the interference parameters are below certain thresholds. We then generalize our techniques and results to Gaussian interference networks with more than two users. In particular, we demonstrate that the total interference threshold, below which treating interference as noise achieves the sum capacity, increases with the number of users.
The Gaussian Multiple Access Wiretap Channel
 IEEE TRANSACTION ON INFORMATION THEORY
, 2008
"... We consider the Gaussian multiple access wiretap channel (GMACWT). In this scenario, multiple users communicate with an intended receiver in the presence of an intelligent and informed wiretapper who receives a degraded version of the signal at the receiver. We define suitable security measures ..."
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Cited by 110 (12 self)
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We consider the Gaussian multiple access wiretap channel (GMACWT). In this scenario, multiple users communicate with an intended receiver in the presence of an intelligent and informed wiretapper who receives a degraded version of the signal at the receiver. We define suitable security measures for this multiaccess environment. Using codebooks generated randomly according to a Gaussian distribution, achievable secrecy rate regions are identified using superposition coding and timedivision multiple access (TDMA) coding schemes. An upper bound for the secrecy sumrate is derived, and our coding schemes are shown to achieve the sum capacity. Numerical results are presented showing the new rate region and comparing it with the capacity region of the Gaussian multipleaccess channel (GMAC) with no secrecy constraints, which quantifies the price paid for secrecy.
Capacity of interference channels with partial transmitter cooperation
 IEEE Transactions on Information Theory
"... Abstract—Capacity regions are established for several twosender, tworeceiver channels with partial transmitter cooperation. First, the capacity regions are determined for compound multipleaccess channels (MACs) with common information and compound MACs with conferencing. Next, two interference chan ..."
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Cited by 101 (10 self)
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Abstract—Capacity regions are established for several twosender, tworeceiver channels with partial transmitter cooperation. First, the capacity regions are determined for compound multipleaccess channels (MACs) with common information and compound MACs with conferencing. Next, two interference channel models are considered: an interference channel with common information (ICCI) and an interference channel with unidirectional cooperation (ICUC) in which the message sent by one of the encoders is known to the other encoder. The capacity regions of both of these channels are determined when there is strong interference, i.e., the interference is such that both receivers can decode all messages with no rate penalty. The resulting capacity regions coincide with the capacity region of the compound MAC with common information. Index Terms—Capacity region, cooperation, strong interference. I.
On the HanKobayashi region for the interference channel,” Submitted to the
 IEEE Trans. on Inf
, 2006
"... In this correspondence, a simplified description of the HanKobayashi rate region for the general interference channel is derived. Using this result, we establish the equivalence between the HanKobayashi and ChongMotaniGarg recently discovered region. Moreover, a tighter bound for the cardinality ..."
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Cited by 98 (2 self)
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In this correspondence, a simplified description of the HanKobayashi rate region for the general interference channel is derived. Using this result, we establish the equivalence between the HanKobayashi and ChongMotaniGarg recently discovered region. Moreover, a tighter bound for the cardinality of the timesharing auxiliary random variable emerges from our simplified description. I. BACKGROUND The interference channel (IC) models the situation where M unrelated senders try to communicate their separate messages to M different receivers via a common channel as shown in Fig. 1. In this model, there is no cooperation between any of the senders or receivers, and hence, the transmission of from each sender to its corresponding receiver is viewed as interference by the other senderreceiver pairs. In this paper, we limit ourselves to the twouser IC. The study of the IC was first initiated by Shannon [1], and was further studied by Ahlswede [2]. In [3], Carleial determined an improved achievable rate region for the IC. Later, Han and Kobayashi established the best achievable rate region to date for the general IC [4]. Except for the Gaussian IC under strong interference [4]–[6], a class of discrete additive degraded IC [7], a class of deterministic IC [8] and the discrete memoryless IC with strong interference
Ergodic interference alignment
 in Proceedings of the International Symposium on Information Theory (ISIT 2009), (Seoul, South Korea
, 2009
"... Abstract—Consider a Kuser interference channel with timevarying fading. At any particular time, each receiver will see a signal from most transmitters. The standard approach to such a scenario results in each transmitterreceiver pair achieving a rate proportional to 1 the single user rate. However ..."
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Cited by 96 (24 self)
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Abstract—Consider a Kuser interference channel with timevarying fading. At any particular time, each receiver will see a signal from most transmitters. The standard approach to such a scenario results in each transmitterreceiver pair achieving a rate proportional to 1 the single user rate. However, given two K well chosen time indices, the channel coefficients from interfering users can be made to exactly cancel. By adding up these two signals, the receiver can see an interferencefree version of the desired transmission. We show that this technique allows each user to achieve at least half its interferencefree ergodic capacity at any SNR. Prior work was only able to show that half the interferencefree rate was achievable as the SNR tended to infinity. We examine a finite field channel model and a Gaussian channel model. In both cases, the achievable rate region has a simple description and, in the finite field case, we prove it is the ergodic capacity region. I.
Complete Characterization of the Pareto Boundary for the MISO
 Interference Channel,” IEEE Trans. Signal Process
, 2008
"... ” c©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in oth ..."
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Cited by 90 (19 self)
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” c©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”