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74
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 245 (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.
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 98 (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.
The general Gaussian multiple access and twoway wiretap channels: Achievable rates and cooperative jamming
 IEEE Trans. Inf. Theory
, 2008
"... We consider the General Gaussian Multiple Access WireTap Channel (GGMACWT) and the Gaussian TwoWay WireTap Channel (GTWWT) which are commonly found in multiuser wireless communication scenarios and serve as building blocks for adhoc networks. In the GGMACWT, multiple users communicate with a ..."
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Cited by 89 (31 self)
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We consider the General Gaussian Multiple Access WireTap Channel (GGMACWT) and the Gaussian TwoWay WireTap Channel (GTWWT) which are commonly found in multiuser wireless communication scenarios and serve as building blocks for adhoc networks. In the GGMACWT, multiple users communicate with an intended receiver in the presence of an intelligent and informed eavesdropper who receives their signals through another GMAC. In the GTWWT, two users communicate with each other with an eavesdropper listening through a GMAC. We consider a secrecy measure that is suitable for this multiterminal environment, and identify achievable such secrecy regions for both channels using Gaussian codebooks. In the special case where the GGMACWT is degraded, we show that Gaussian codewords achieve the strong secret key sumcapacity. For both GGMACWT and GTWWT, we find the power allocations that maximize the achievable secrecy sumrate, and find that the optimum policy may prevent some terminals from transmission in order to preserve the secrecy of the system. Inspired by this construct, we next propose a new scheme which we call cooperative jamming, where users who are not transmitting according to the sumrate maximizing power allocation can help the remaining users by “jamming ” the eavesdropper. This scheme is shown to increase the achievable secrecy sumrate, and in some cases allow a previously nontransmitting terminal to be able to transmit with secrecy. Overall,
The General Gaussian MultipleAccess and TwoWay Wiretap Channels: Achievable Rates and Cooperative Jamming
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 2008
"... The general Gaussian multipleaccess wiretap channel (GGMACWT) and the Gaussian twoway wiretap channel (GTWWT) are considered. In the GGMACWT, multiple users communicate with an intended receiver in the presence of an eavesdropper who receives their signals through another GMAC. In the GTWWT, ..."
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Cited by 85 (1 self)
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The general Gaussian multipleaccess wiretap channel (GGMACWT) and the Gaussian twoway wiretap channel (GTWWT) are considered. In the GGMACWT, multiple users communicate with an intended receiver in the presence of an eavesdropper who receives their signals through another GMAC. In the GTWWT, two users communicate with each other over a common Gaussian channel, with an eavesdropper listening through a GMAC. A secrecy measure that is suitable for this multiterminal environment is defined, and achievable secrecy rate regions are found for both channels. For both cases, the power allocations maximizing the achievable secrecy sum rate are determined. It is seen that the optimum policy may prevent some terminals from transmission in order to preserve the secrecy of the system. Inspired by this construct, a new scheme cooperative jamming is proposed, where users who are prevented from transmitting according to the secrecy sum rate maximizing power allocation policy “jam ” the eavesdropper, thereby helping the remaining users. This scheme is shown to increase the achievable secrecy sum rate. Overall, our results show that in multipleaccess scenarios, users can help each other to collectively achieve positive secrecy rates. In other words, cooperation among users can be invaluable for achieving secrecy for the system.
On the DegreesofFreedom of the KUser Gaussian Interference Channel
 IEEE Transactions on Information Theory
, 2008
"... The degreesoffreedom of a Kuser Gaussian interference channel (GIFC) has been defined to be the multiple of (1/2)log 2 P at which the maximum sum of achievable rates grows with increasing P. In this paper, we establish that the degreesoffreedom of three or more user, real, scalar GIFCs, viewed ..."
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Cited by 78 (0 self)
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The degreesoffreedom of a Kuser Gaussian interference channel (GIFC) has been defined to be the multiple of (1/2)log 2 P at which the maximum sum of achievable rates grows with increasing P. In this paper, we establish that the degreesoffreedom of three or more user, real, scalar GIFCs, viewed as a function of the channel coefficients, is discontinuous at points where all of the coefficients are nonzero rational numbers. More specifically, for all K> 2, we find a class of Kuser GIFCs that is dense in the GIFC parameter space for which K/2 degreesoffreedom are exactly achievable, and we show that the degreesoffreedom for any GIFC with nonzero rational coefficients is strictly smaller than K/2. These results are proved using new connections with number theory and additive combinatorics. 1
Capacity of a Class of Cognitive Radio Channels: Interference Channels with Degraded Message Sets
"... This paper is motivated by two different scenarios. The first is a cognitive radio system where a cognitive radio knows a “dumb ” radio’s message and the second is a sensor network in a correlated field where sensors possessing a nested message structure assist one another’s in information transmis ..."
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Cited by 68 (3 self)
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This paper is motivated by two different scenarios. The first is a cognitive radio system where a cognitive radio knows a “dumb ” radio’s message and the second is a sensor network in a correlated field where sensors possessing a nested message structure assist one another’s in information transmission. Both scenarios are modeled using the framework of discrete memoryless interference channels with degraded message sets (IFCDMS), a setting where one of the two transmitters in an interference channel knows both the messages to be conveyed to the receivers. Both inner and outer bounds are provided in this paper for a class of IFCDMS channels. The case of the Gaussian interference channels with degraded message sets is also investigated. In this case, achievability and converse arguments are presented for a class of “weak” interference channels, resulting in a characterization of this class’ capacity region.
On the capacity of interference channels with one cooperating transmitter
 EUROP. TRANS. TELECOMMUN. (SPECIAL ISSUE: NEW DIRECTIONS IN INFORMATION THEORY
, 2007
"... Inner and outer bounds are established on the capacity region of twosender, tworeceiver interference channels where one transmitter knows both messages. The transmitter with extra knowledge is referred to as being cognitive. The inner bound is based on strategies that generalize prior work, and i ..."
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Cited by 51 (3 self)
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Inner and outer bounds are established on the capacity region of twosender, tworeceiver interference channels where one transmitter knows both messages. The transmitter with extra knowledge is referred to as being cognitive. The inner bound is based on strategies that generalize prior work, and include ratesplitting, Gel’fandPinsker coding and cooperative transmission. A general outer bound is based on the NairEl Gamal outer bound for broadcast channels. A simpler bound is presented for the case in which one of the decoders can decode both messages. The bounds are evaluated and compared for Gaussian channels.
On the Capacity of Vector Gaussian Interference Channels
 IEEE ITW,2004
"... Abstract — The capacity of a vector Gaussian interference channel is investigated. Outer bounds, and where possible, capacity regions of a class of interference channels is characterized. The analysis of single transmit multiple receive antenna (SIMO) Gaussian interference channels with strong int ..."
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Cited by 45 (6 self)
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Abstract — The capacity of a vector Gaussian interference channel is investigated. Outer bounds, and where possible, capacity regions of a class of interference channels is characterized. The analysis of single transmit multiple receive antenna (SIMO) Gaussian interference channels with strong interference can be easily seen to be exactly analogous to that of a single transmit single receive antenna system. This paper demonstrates that, in contrast, multiple transmit single receive antenna (MISO) Gaussian interference channels are much harder to characterize. In this paper, the capacity region for a class of MISO interference channels with very strong interference is characterized. Also, the rank of the optimal transmit policy in a MISO Gaussian interference channel is shown to be bounded by the number of users in the system. Finally, outer bounds on the capacity region of the general multiple transmit and receive antenna (MIMO) Gaussian Interference Channels are derived. A new outer bound is obtained, which combines and improves previously known strategies for bounding the capacity of interference channels. I.
On the Capacity of the Interference Channel with a Relay
"... Abstract—Capacity gains due to relaying in wireless networks with multiple sourcedestination pairs are analyzed. A twosource, tworeceiver network with the relay is considered. The focus is on the scenario in which, due to channel conditions, the relay can observe the signal from only one source. T ..."
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Cited by 40 (7 self)
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Abstract—Capacity gains due to relaying in wireless networks with multiple sourcedestination pairs are analyzed. A twosource, tworeceiver network with the relay is considered. The focus is on the scenario in which, due to channel conditions, the relay can observe the signal from only one source. The relay can thus help the intended receiver of this message, via message forwarding, to decode it. In addition, the relay can simultaneously help the unintended receiver subtract the interference associated with this message. We call the latter strategy interference forwarding. An achievable rate region employing decodeandforward (that simultaneously does message and interference forwarding) at the relay is derived and analyzed. This strategy is shown to achieve the capacity region under certain conditions. Our results demonstrate that the relay can help both receivers, despite the fact that it forwards only the message intended for one of them. This applies in general to communications in the presence of an interferer transmitting at any arbitrary rate. Interference forwarding improves reception of interfering signals at the receivers. This facilitates decoding of the unwanted messages and eliminating the resulting interference. Therefore, in networks with multiple sourcedestination pairs, in addition to relaying messages, interference forwarding may also be employed to help in combating interference. I.
Degrees of Freedom of the K User M × N MIMO Interference Channel
, 809
"... We provide innerbound and outerbound for the total number of degrees of freedom of the K user multiple input multiple output (MIMO) Gaussian interference channel with M antennas at each transmitter and N antennas at each receiver if the channel coefficients are timevarying and drawn from a continuo ..."
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Cited by 32 (4 self)
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We provide innerbound and outerbound for the total number of degrees of freedom of the K user multiple input multiple output (MIMO) Gaussian interference channel with M antennas at each transmitter and N antennas at each receiver if the channel coefficients are timevarying and drawn from a continuous distribution. The bounds are tight when the ratio max(M,N) min(M,N) = R is equal to an integer. For this case, we show that the total number of degrees of freedom is equal to min(M, N)K if K ≤ R and min(M, N) R R+1K if K> R. Achievability is based on interference alignment. We also provide examples where using interference alignment combined with zero forcing can achieve more degrees of freedom than merely zero forcing for some MIMO interference channels with constant channel coefficients. 2 I.