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236
Gaussian interference channel capacity to within one bit
 5534–5562, 2008. EURASIP Journal on Advances in Signal Processing
"... Abstract—The capacity of the twouser Gaussian interference channel has been open for 30 years. The understanding on this problem has been limited. The best known achievable region is due to Han and Kobayashi but its characterization is very complicated. It is also not known how tight the existing o ..."
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Cited by 451 (28 self)
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Abstract—The capacity of the twouser Gaussian interference channel has been open for 30 years. The understanding on this problem has been limited. The best known achievable region is due to Han and Kobayashi but its characterization is very complicated. It is also not known how tight the existing outer bounds are. In this work, we show that the existing outer bounds can in fact be arbitrarily loose in some parameter ranges, and by deriving new outer bounds, we show that a very simple and explicit Han–Kobayashi type scheme can achieve to within a single bit per second per hertz (bit/s/Hz) of the capacity for all values of the channel parameters. We also show that the scheme is asymptotically optimal at certain high signaltonoise ratio (SNR) regimes. Using our results, we provide a natural generalization of the pointtopoint classical notion of degrees of freedom to interferencelimited scenarios. Index Terms—Capacity region, Gaussian interference channel, generalized degrees of freedom.
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.
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.
Distributed Multiuser Power Control for Digital Subscriber Lines
, 2002
"... This paper considers the multiuser power control problem in a frequencyselective interference channel. The interference channel is modeled as a noncooperative game, and the existence and uniqueness of a Nash equilibrium are established for a twoplayer version of the game. An iterative waterfillin ..."
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Cited by 271 (23 self)
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This paper considers the multiuser power control problem in a frequencyselective interference channel. The interference channel is modeled as a noncooperative game, and the existence and uniqueness of a Nash equilibrium are established for a twoplayer version of the game. An iterative waterfilling algorithm is proposed to efficiently reach the Nash equilibrium. The iterative waterfilling algorithm can be implemented distributively without the need for centralized control. It implicitly takes into account the loop transfer functions and cross couplings, and it reaches a competitively optimal power allocation by offering an opportunity for loops to negotiate the best use of power and frequency with each other. When applied to the upstream power backoff problem in veryhigh bitrate digital subscriber lines and the downstream spectral compatibility problem in asymmetric digital subscriber lines, the new power control algorithm is found to give a significant performance improvement when compared with existing methods.
Achievable Rates in Cognitive Radio Channels
 IEEE Trans. Inf. Theory
, 2006
"... Cognitive radio promises a low cost, highly flexible alternative to the classic single frequency band, single protocol wireless device. By sensing and adapting to its environment, such a device is able to fill voids in the wireless spectrum and dramatically increase spectral efficiency. In this pape ..."
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Cited by 265 (46 self)
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Cognitive radio promises a low cost, highly flexible alternative to the classic single frequency band, single protocol wireless device. By sensing and adapting to its environment, such a device is able to fill voids in the wireless spectrum and dramatically increase spectral efficiency. In this paper, the cognitive radio channel is defined as an ntransmitter, mreceiver interference channel in which sender i obtains the messages senders 1 through i − 1 plan to transmit. The two sender, two receiver case is considered. In this scenario, one user, a cognitive radio, obtains (genie assisted, or causally) knowledge of the data to be transmitted by the other user. The cognitive radio may then simultaneously transmit over the same channel, as opposed to waiting for an idle channel as in a traditional cognitive radio channel protocol. Dirtypaper coding and ideas from achievable region constructions for the interference channel are used, and an achievable region for the cognitive radio channel is computed. It is shown that in the Gaussian case, the described achievable region approaches the upper bounds provided by the 2×2 Gaussian MIMO broadcast channel, and an interferencefree channel. Results are extended to the case in which the message is causally obtained.
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.
Capacity bounds for the Gaussian interference channel
 IEEE TRANS. INFORM. THEORY
"... The capacity region of the twouser Gaussian Interference Channel (IC) is studied. Three classes of channels are considered: weak, onesided, and mixed Gaussian ICs. For the weak Gaussian IC, a new outer bound on the capacity region is obtained that outperforms previously known outer bounds. The cha ..."
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Cited by 158 (6 self)
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The capacity region of the twouser Gaussian Interference Channel (IC) is studied. Three classes of channels are considered: weak, onesided, and mixed Gaussian ICs. For the weak Gaussian IC, a new outer bound on the capacity region is obtained that outperforms previously known outer bounds. The channel sum capacity for some certain range of the channel parameters is derived. It is shown that when Gaussian codebooks are used, the full HanKobayashi achievable rate region can be obtained by using the naive HanKobayashi achievable scheme over three frequency bands (equivalently, three subspaces). For the onesided Gaussian IC, a new proof for Sato’s outer bound is presented. We derive the full HanKobayashi achievable rate region when Gaussian code books are utilized. For the mixed Gaussian IC, a new outer bound is obtained that again outperforms previously known outer bounds. For this case, the channel sum capacity for all ranges of parameters is derived. It is proved that the full HanKobayashi achievable rate region using Gaussian codebooks is equivalent to that of the onesided Gaussian IC for a particular range of the channel gains.
The approximate capacity of the manytoone and onetomany Gaussian interference channels
 in Proc. Allerton Conf. Commun. Control Comput
, 2007
"... region of the twouser Gaussian interference channel to within 1 bit/s/Hz. A natural goal is to apply this approach to the Gaussian interference channel with an arbitrary number of users. We make progress towards this goal by finding the capacity region of the manytoone and onetomany Gaussian in ..."
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Cited by 137 (9 self)
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region of the twouser Gaussian interference channel to within 1 bit/s/Hz. A natural goal is to apply this approach to the Gaussian interference channel with an arbitrary number of users. We make progress towards this goal by finding the capacity region of the manytoone and onetomany Gaussian interference channels to within a constant number of bits. The result makes use of a deterministic model to provide insight into the Gaussian channel. The deterministic model makes explicit the dimension of signal level. A central theme emerges: the use of lattice codes for alignment of interfering signals on the signal level. Index Terms—Capacity, interference alignment, interference channel, lattice codes, multiuser channels. 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.
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.