arXiv subjects

Stefano Rini

Publications and source records attributed to Stefano Rini.

87 records · Page 5Linked to original sources

arXiv2012

Practical Coding Schemes for Cognitive Overlay Radios

We develop practical coding schemes for the cognitive overlay radios as modeled by the cognitive interference channel, a variation of the classical two user interference channel where one of the transmitters has knowledge of both messages. Inspired by information theoretical results, we develop a coding strategy for each of the three parameter regimes where capacity is known. A key feature of the capacity achieving schemes in these regimes is the joint decoding of both users' codewords, which we accomplish by performing a posteriori probability calculation over a combined trellis. The schemes are shown to perform close to the capacity limit with low error rate.

cs.IT↗

arXiv2012

Improving the Entropy Estimate of Neuronal Firings of Modeled Cochlear Nucleus Neurons

In this correspondence information theoretical tools are used to investigate the statistical properties of modeled cochlear nucleus globular bushy cell spike trains. The firing patterns are obtained from a simulation software that generates sample spike trains from any auditory input. Here we analyze for the first time the responses of globular bushy cells to voiced and unvoiced speech sounds. Classical entropy estimates, such as the direct method, are improved upon by considering a time-varying and time-dependent entropy estimate. With this method we investigated the relationship between the predictability of the neuronal response and the frequency content in the auditory signals. The analysis quantifies the temporal precision of the neuronal coding and the memory in the neuronal response.

q-bio.NC↗

arXiv2012

Primary Rate-Splitting Achieves Capacity for the Gaussian Cognitive Interference Channel

The cognitive interference channel models cognitive overlay radio systems, where cognitive radios overhear the transmission of neighboring nodes. Capacity for this channel is not known in general. For the Gaussian case capacity is known in three regimes, usually denoted as the "weak interference", "very strong interference" and "primary decodes cognitive". This paper provides a new capacity result, based on rate-splitting of the primary user's message into a public and private part and that generalizes the capacity results in the "very strong interference" and "primary decodes cognitive" regimes. This result indicates that capacity of the cognitive interference channel not only depends on channel conditions but also the level of cooperation with the primary user.

cs.IT↗

arXiv2012

A New Random Coding Technique that Generalizes Superposition Coding and Binning

Proving capacity for networks without feedback or cooperation usually involves two fundamental random coding techniques: superposition coding and binning. Although conceptually very different, these two techniques often achieve the same performance, suggesting an underlying similarity. In this correspondence we propose a new random coding technique that generalizes superposition coding and binning and provides new insight on relationship among the two With this new theoretical tool, we derive new achievable regions for three classical information theoretical models: multi-access channel, broadcast channel, the interference channel, and show that, unfortunately, it does not improve over the largest known achievable regions for these cases.

cs.IT↗

arXiv2012

On the Capacity of a General Multiple-Access Channel and of a Cognitive Network in the Very Strong Interference Regime

The capacity of the multiple-access channel with any distribution of messages among the transmitting nodes was determined by Han in 1979 and the expression of the capacity region contains a number of rate bounds and that grows exponentially with the number of messages. We derive a more compact expression for the capacity region of this channel in which the number of rate bounds depends on the distribution of the messages at the encoders. Using this expression we prove capacity for a class of general cognitive network that we denote as "very strong interference" regime. In this regime there is no rate loss in having all the receivers decode all the messages and the capacity region reduces to the capacity of the compound multiple-access channel. This result generalizes the "very strong interference" capacity results for the interference channel, the cognitive interference channel, the interference channel with a cognitive relay and many others.

cs.IT↗

arXiv2012

The Capacity of the Semi-Deterministic Cognitive Interference Channel with a Common Cognitive Message and Approximate Capacity for the Gaussian Case

In this paper the study of the cognitive interference channel with a common message, a variation of the classical cognitive interference channel in which the cognitive message is decoded at both receivers. We derive the capacity for the semideterministic channel in which the output at the cognitive decoder is a deterministic function of the channel inputs. We also show capacity to within a constant gap and a constant factor for the Gaussian channel in which the outputs are linear combinations of the channel inputs plus an additive Gaussian noise term. Most of these results are shown using an interesting transmission scheme in which the cognitive message, decoded at both receivers, is also pre-coded against the interference experienced at the cognitive decoder. The pre-coding of the cognitive message does not allow the primary decoder to reconstruct the interfering signal. The cognitive message acts instead as a side information at the primary receiver when decoding its intended message.

cs.IT↗

arXiv2011

On the Capacity of the Interference Channel with a Cognitive Relay

The InterFerence Channel with a Cognitive Relay (IFC-CR) consists of the classical interference channel with two independent source-destination pairs whose communication is aided by an additional node, referred to as the cognitive relay, that has a priori knowledge of both sources' messages. This a priori message knowledge is termed cognition and idealizes the relay learning the messages of the two sources from their transmissions over a wireless channel. This paper presents new inner and outer bounds for the capacity region of the general memoryless IFC-CR that are shown to be tight for a certain class of channels. The new outer bound follows from arguments originally devised for broadcast channels among which Sato's observation that the capacity region of channels with non-cooperative receivers only depends on the channel output conditional marginal distributions. The new inner bound is shown to include all previously proposed coding schemes and it is thus the largest known achievable rate region to date. The new inner and outer bounds coincide for a subset of channel satisfying a strong interference condition. For these channels there is no loss in optimality if both destinations decode both messages. This result parallels analogous results for the classical IFC and for the cognitive IFC and is the first known capacity result for the general IFC-CR. Numerical evaluations of the proposed inner and outer bounds are presented for the Gaussian noise case.

cs.IT↗

arXiv2011

Capacity to within 3 bits for a class of Gaussian Interference Channels with a Cognitive Relay

The InterFerence Channel with a Cognitive Relay (IFC-CR) consists of a classical two-user interference channel in which the two independent messages are also non-causally known at a cognitive relay node. In this work a special class of IFC-CRs in which the sources do not create interference at the non-intended destinations is analyzed. This special model results in a channel with two non-interfering point-to-point channels whose transmission is aided by an in-band cognitive relay, which is thus referred to as the Parallel Channel with a Cognitive Relay (PC-CR). We determine the capacity of the PC-CR channel to within 3 bits/s/Hz for all channel parameters. In particular, we present several new outer bounds which we achieve to within a constant gap by proper selection of Gaussian input distributions in a simple rate-splitting and superposition coding-based inner bound. The inner and outer bounds are numerically evaluated to show that the actual gap can be far less than 3 bits/s/Hz.

cs.IT↗

arXiv2011

A New Capacity Result for the Z-Gaussian Cognitive Interference Channel

This work proposes a novel outer bound for the Gaussian cognitive interference channel in strong interference at the primary receiver based on the capacity of a multi-antenna broadcast channel with degraded message set. It then shows that for the Z-channel, i.e., when the secondary receiver experiences no interference and the primary receiver experiences strong interference, the proposed outer bound not only is the tightest among known bounds but is actually achievable for sufficiently strong interference. The latter is a novel capacity result that from numerical evaluations appears to be generalizable to a larger (i.e., non-Z) class of Gaussian channels.

cs.IT↗

arXiv2010

Inner and Outer Bounds for the Gaussian Cognitive Interference Channel and New Capacity Results

The capacity of the Gaussian cognitive interference channel, a variation of the classical two-user interference channel where one of the transmitters (referred to as cognitive) has knowledge of both messages, is known in several parameter regimes but remains unknown in general. In this paper we provide a comparative overview of this channel model as we proceed through our contributions: we present a new outer bound based on the idea of a broadcast channel with degraded message sets, and another series of outer bounds obtained by transforming the cognitive channel into channels with known capacity. We specialize the largest known inner bound derived for the discrete memoryless channel to the Gaussian noise channel and present several simplified schemes evaluated for Gaussian inputs in closed form which we use to prove a number of results. These include a new set of capacity results for the a) "primary decodes cognitive" regime, a subset of the "strong interference" regime that is not included in the "very strong interference" regime for which capacity was known, and for the b) "S-channel" in which the primary transmitter does not interfere with the cognitive receiver. Next, for a general Gaussian cognitive interference channel, we determine the capacity to within one bit/s/Hz and to within a factor two regardless of channel parameters, thus establishing rate performance guarantees at high and low SNR, respectively. We also show how different simplified transmission schemes achieve a constant gap between inner and outer bound for specific channels. Finally, we numerically evaluate and compare the various simplified achievable rate regions and outer bounds in parameter regimes where capacity is unknown, leading to further insight on the capacity region of the Gaussian cognitive interference channel.

cs.IT↗

arXiv2010

The Capacity of the Semi-Deterministic Cognitive Interference Channel and its Application to Constant Gap Results for the Gaussian Channel

The cognitive interference channel (C-IFC) consists of a classical two-user interference channel in which the message of one user (the "primary" user) is non-causally available at the transmitter of the other user (the "cognitive" user). We obtain the capacity of the semi-deterministic C-IFC: a discrete memoryless C-IFC in which the cognitive receiver output is a noise-less deterministic function of the channel inputs. We then use the insights obtained from the capacity-achieving scheme for the semi-deterministic model to derive new, unified and tighter constant gap results for the complex-valued Gaussian C-IFC. We prove: (1) a constant additive gap (difference between inner and outer bounds) of half a bit/sec/Hz per real dimension, of relevance at high SNRs, and (b) a constant multiplicative gap (ratio between outer and inner bounds) of a factor two, of relevance at low SNRs

cs.IT↗

arXiv2010

New Results on the Capacity of the Gaussian Cognitive Interference Channel

The capacity of the two-user Gaussian cognitive interference channel, a variation of the classical interference channel where one of the transmitters has knowledge of both messages, is known in several parameter regimes but remains unknown in general. In this paper, we consider the following achievable scheme: the cognitive transmitter pre-codes its message against the interference created at its intended receiver by the primary user, and the cognitive receiver only decodes its intended message, similar to the optimal scheme for "weak interference"; the primary decoder decodes both messages, similar to the optimal scheme for "very strong interference". Although the cognitive message is pre-coded against the primary message, by decoding it, the primary receiver obtains information about its own message, thereby improving its rate. We show: (1) that this proposed scheme achieves capacity in what we term the "primary decodes cognitive" regime, i.e., a subset of the "strong interference" regime that is not included in the "very strong interference" regime for which capacity was known; (2) that this scheme is within one bit/s/Hz, or a factor two, of capacity for a much larger set of parameters, thus improving the best known constant gap result; (3) we provide insights into the trade-off between interference pre-coding at the cognitive encoder and interference decoding at the primary receiver based on the analysis of the approximate capacity results.

cs.IT↗

arXiv2010

Outer Bounds for the Interference Channel with a Cognitive Relay

In this paper, we first present an outer bound for a general interference channel with a cognitive relay, i.e., a relay that has non-causal knowledge of both independent messages transmitted in the interference channel. This outer bound reduces to the capacity region of the deterministic broadcast channel and of the deterministic cognitive interference channel through nulling of certain channel inputs. It does not, however, reduce to that of certain deterministic interference channels for which capacity is known. As such, we subsequently tighten the bound for channels whose outputs satisfy an "invertibility" condition. This second outer bound now reduces to the capacity of this special class of deterministic interference channels. The second outer bound is further tightened for the high SNR deterministic approximation of the Gaussian interference channel with a cognitive relay by exploiting the special structure of the interference. We provide an example that suggests that this third bound is tight in at least some parameter regimes for the high SNR deterministic approximation of the Gaussian channel. Another example shows that the third bound is capacity in the special case where there are no direct links between the non-cognitive transmitters.

cs.IT↗

arXiv2010

New inner and outer bounds for the discrete memoryless cognitive interference channel and some capacity results

The cognitive interference channel is an interference channel in which one transmitter is non-causally provided with the message of the other transmitter. This channel model has been extensively studied in the past years and capacity results for certain classes of channels have been proved. In this paper we present new inner and outer bounds for the capacity region of the cognitive interference channel as well as new capacity results. Previously proposed outer bounds are expressed in terms of auxiliary random variables for which no cardinality constraint is known. Consequently it is not possible to evaluate such outer bounds explicitly for a given channel model. The outer bound we derive is based on an idea originally devised by Sato for the broadcast channel and does not contain auxiliary random variables, allowing it to be more easily evaluated. The inner bound we derive is the largest known to date and is explicitly shown to include all previously proposed achievable rate regions. This comparison highlights which features of the transmission scheme - which includes rate-splitting, superposition coding, a broadcast channel-like binning scheme, and Gel'fand Pinsker coding - are most effective in approaching capacity. We next present new capacity results for a class of discrete memoryless channels that we term the "better cognitive decoding regime" which includes all previously known regimes in which capacity results have been derived as special cases. Finally, we determine the capacity region of the semi-deterministic cognitive interference channel, in which the signal at the cognitive receiver is a deterministic function of the channel inputs.

cs.IT↗

arXiv2010

State of the cognitive interference channel: a new unified inner bound

The capacity region of the interference channel in which one transmitter non-causally knows the message of the other, termed the cognitive interference channel, has remained open since its inception in 2005. A number of subtly differing achievable rate regions and outer bounds have been derived, some of which are tight under specific conditions. In this work we present a new unified inner bound for the discrete memoryless cognitive interference channel. We show explicitly how it encompasses all known discrete memoryless achievable rate regions as special cases. The presented achievable region was recently used in deriving the capacity region of the general deterministic cognitive interference channel, and thus also the linear high-SNR deterministic approximation of the Gaussian cognitive interference channel. The high-SNR deterministic approximation was then used to obtain the capacity of the Gaussian cognitive interference channel to within 1.87 bits.

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