Approximate Sum-Capacity of K-user Cognitive Interference Channels with Cumulative Message Sharing

Maamari, Diana; Tuninetti, Daniela; Devroye, Natasha

doi:10.1109/jsac.2014.140325

Cited by 13 publications

(18 citation statements)

References 21 publications

(35 reference statements)

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“…By considering the union over all possible choices of parameters for the mixed inputs we obtain the region in (34), which is contained within the achievable region in (5) and hence forms a lower bound to the capacity region.…”

Section: Proposition 5: For the G-ic The Tinnots Region In (5) Contaimentioning

confidence: 99%

“…The main result of this paper is as follows Theorem 7: For the symmetric G-IC, as defined in (2), the TINnoTS achievable region in (34), with the parameters for the mixed inputs chosen as indicated in Table I, and the outer bound in (36) are to within a gap of:…”

Section: Symmetric Capacity Region To Within a Gapmentioning

confidence: 99%

“…The sum-rate bounds in (36c) and (36d) were originally derived for the classical two-user IC in Gaussian noise in [29] and then extended to any memoryless two-user IC with source cooperation/generalized feedback in [31], and then to any memoryless cooperative two-user IC (where each node can have an input and an output to the channel) in [32] -see also K -user extensions in [33] and [34]. In [32] it was noted that surprisingly these bounds hold for a broad class of twouser IC-type channels, which includes for example cognitive ICs and certain ICs with cooperation.…”

Section: Symmetric Capacity Region To Within a Gapmentioning

confidence: 99%

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Interference as Noise: Friend or Foe?

Dytso

Tuninetti

Devroye

2016

IEEE Trans. Inform. Theory

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This paper shows that for the two-user Gaussian interference channel (G-IC) treating interference as noise without time sharing (TINnoTS) achieves the closure of the capacity region to within either a constant gap, or to within a gap of the order O(log(ln(min(S, I))/γ )) up to a set of Lebesgue measure γ ∈ (0, 1], where S is the largest signal to noise ratio on the direct links and I is the largest interference to noise ratio on the cross links. As a consequence, TINnoTS is optimal from a generalized degrees of freedom (gDoF) perspective for all channel gains except for a subset of zero measure. TINnoTS with Gaussian inputs is known to be optimal within 1/2 bit for a subset of the weak interference regime. Rather surprisingly, this paper shows that TINnoTS is gDoF optimal in all parameter regimes, even in the strong and very strong interference regimes where joint decoding of Gaussian inputs is optimal. For approximate optimality of TINnoTS in all parameter regimes, it is critical to use non-Gaussian inputs. This paper thus proposes to use mixed inputs as channel inputs for the G-IC, where a mixed input is the sum of a discrete and a Gaussian random variable. Interestingly, with reference to the Han-Kobayashi achievable scheme, the discrete part of a mixed input is shown to effectively behave as a common message in the sense that, although treated as noise, its effect on the achievable rate region is as if it were jointly decoded together with the desired messages at a non-intended receiver. The practical implication is that a discrete interfering input is a friend, while an Gaussian interfering input is in general a foe. This paper also discusses other practical implications of the proposed TINnoTS scheme with mixed inputs. Since TINnoTS requires neither explicit joint decoding nor time sharing, the results of this paper are applicable to a variety of oblivious or asynchronous channels, such as the block asynchronous G-IC (which is not an information stable channel) and the G-IC with partial codebook knowledge at one or more receivers.Index Terms-Treating interference as noise, interference channel, discrete inputs.

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Section: Proposition 5: For the G-ic The Tinnots Region In (5) Contaimentioning

confidence: 99%

Section: Symmetric Capacity Region To Within a Gapmentioning

confidence: 99%

Section: Symmetric Capacity Region To Within a Gapmentioning

confidence: 99%

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Interference as Noise: Friend or Foe?

Dytso

Tuninetti

Devroye

2016

IEEE Trans. Inform. Theory

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“…However, they restrict the channel so that the cognitive users do not cause interference to one another but only to the primary receiver and are interfered only by the primary transmitter; for this channel model the capacity in the very strong interference regime (i.e., INR > SNR 2 in the symmetric case) is obtained by using lattice codes. 5 In [13], we further considered the K-CIFC-CMS. A sumcapacity upper bound was derived by giving nested genie sideinformation to receivers.…”

Section: The K-user Cognitive Interference Channel (K-cifc)mentioning

confidence: 99%

Multi-user Cognitive Interference Channels: A Survey and New Capacity Results

Maamari¹,

Tuninetti²,

Devroye³

2015

IEEE Trans. Cogn. Commun. Netw.

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This paper provides a survey of the state-of-the-art information theoretic analysis for overlay multi-user (more than two pairs) cognitive networks and reports new capacity results. In an overlay scenario, cognitive / secondary users share the same frequency band with licensed / primary users to efficiently exploit the spectrum. They do so without degrading the performance of the incumbent users, and may possibly even aid in transmitting their messages as cognitive users are assumed to possess the message(s) of primary user(s) and possibly other cognitive user(s). The survey begins with a short overview of the two-user overlay cognitive interference channel. The evolution from two-user to three-user overlay cognitive interference channels is described next, followed by generalizations to multi-user (arbitrary number of users) cognitive networks. The rest of the paper considers K-user cognitive interference channels with different message knowledge structures at the transmitters.Novel capacity inner and outer bounds are proposed. Channel conditions under which the bounds meet, thus characterizing the information theoretic capacity of the channel, for both Linear Deterministic and Gaussian channel models, are derived.The results show that for certain channel conditions distributed cognition, or having a cumulative message knowledge structure at the nodes, may not be worth the overhead as (approximately) the same capacity can be achieved by having only one global cognitive user whose role is to manage all the interference in the network. The paper concludes with future research directions.In this paper, we survey the fundamental limits of communication for a multi-user overlay cognitive networks with an arbitrary number of secondary / cognitive user(s) having non-causal message knowledge of primary user(s). The users transmit in the same frequency band and thus in general interfere with one another. The performance metric considered is the information theoretic notion of channel capacity. In other words, we are interested in the maximum rate of communication for which arbitrarily small probability of error can be achieved by every user, which may be seen as a benchmark when building practical systems. We will focus on results for general memoryless and practically relevant additive white Gaussian noise (AWGN) [2] channel models, as well as high signal to noise ratio (SNR) approximations of Gaussian is currently an Associate Editor for the IEEE Transactions on Cognitive Communications and Networking. Her research focuses on multi-user information theory and applications to cognitive and software-defined radio, radar, relay and two-way communication networks.

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“…Proof: For the symmetric LDC K-CIFC-CMS the sumcapacity in was shown to be upper bounded by [6], [12]:…”

Section: Theorem 1 the Capacity Region Of A General Memoryless K-cifmentioning

confidence: 99%

On the K-user cognitive interference channel with cumulative message sharing sum-capacity

Maamari

Tuninetti

Devroye

2013

2013 IEEE International Symposium on Information Theory

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This paper considers the K-user cognitive interference channel with one primary and K − 1 secondary/cognitive transmitters with a cumulative message sharing structure, i.e., cognitive transmitter i, i ∈ [2 : K], non-causally knows all messages of the users with index less than i. We first propose a computable outer bound valid for any memoryless channel and show the sum-rate to be achievable for the symmetric Kuser Linear Deterministic Channel. Interestingly, for the Kuser channel having only the K-th transmitter know all other messages is sufficient to achieve the sum-capacity, i.e., cognition at transmitters 2 to K−1 is not needed. Next, the sum-capacity of the symmetric Gaussian noise channel is characterized to within a constant additive and multiplicative gap, which depend on K. As opposed to other interference channel models, a single scheme suffices for both the weak and strong interference regimes. Moreover it is only required for transmitters 2 to K − 1 to have, in addition to their own message, non-causal message knowledge of the transmitter 1's message.

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Approximate Sum-Capacity of K-user Cognitive Interference Channels with Cumulative Message Sharing

Cited by 13 publications

References 21 publications

Interference as Noise: Friend or Foe?

Interference as Noise: Friend or Foe?

Multi-user Cognitive Interference Channels: A Survey and New Capacity Results

On the K-user cognitive interference channel with cumulative message sharing sum-capacity

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