Daniela Tuninetti

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. This paper provides a comparative overview of this channel model as it proceeds through the following contributions. First, several outer bounds are presented: (a) a new outer bound based on the idea of a broadcast channel with degraded message sets, and (b) an outer bound obtained by transforming the channel into channels with known capacity. Next, a compact Fourier-Motzkin eliminated version of the largest known inner bound derived for the discrete memoryless cognitive interference channel is presented and specialized to the Gaussian noise case, where several simplified schemes with jointly Gaussian input are evaluated in closed form and later used to prove a number of results. These include a new set of capacity results for: (a) the “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 (b) the “S-channel in strong interference” in which the primary transmitter does not interfere with the cognitive receiver and the primary receiver experiences strong interference. Next, for a general Gaussian channel the capacity is determined to within one bit/s/Hz and to within a factor two regardless of the channel parameters, thus establishing rate performance guarantees at high and low SNR, respectively. The paper concludes with numerical evaluations and comparisons of the various simplified achievable rate regions and outer bounds in parameter regimes where capacity is unknown, leading to further insight on the capacity region.

On InterFerence Channel with Generalized Feedback (IFC-GF)

This work studies cooperative communication strategies for Interference Channels with Generalized Feedback (IFC-GF). IFC-GF models wireless peer-to-peer networks where several source-destination pairs share the same channel and, because of the broadcast nature of the wireless channel, each transmission can be overheard by the other users. In this model, the interference due to simultaneous communications furnishes the basis for cooperation among otherwise uncoordinated users. For the case of two source-destination pairs, we propose a coding strategy that combines the ideas of (i) information splitting (introduced by Han and Kobayashi for IFC without feedback), (ii) block Markov superposition coding (introduced by Cover and Leung for multiaccess channels with perfect feedback), and (iii) backward decoding (introduced by Willems in the context of multiaccess channels with cribbing encoders). We show that by exploiting the overheard information with the proposed scheme, users achieves collectively higher data rates than the case where the overheard information is neglected. We conclude by showing how our model reduces to well studied multiuser channels.

Pathological tremor prediction using surface electromyogram and acceleration: potential use in 'ON-OFF' demand driven deep brain stimulator design.

OBJECTIVE We present a proof of concept for a novel method of predicting the onset of pathological tremor using non-invasively measured surface electromyogram (sEMG) and acceleration from tremor-affected extremities of patients with Parkinsons disease (PD) and essential tremor (ET). APPROACH The tremor prediction algorithm uses a set of spectral (Fourier and wavelet) and nonlinear time series (entropy and recurrence rate) parameters extracted from the non-invasively recorded sEMG and acceleration signals. MAIN RESULTS The resulting algorithm is shown to successfully predict tremor onset for all 91 trials recorded in 4 PD patients and for all 91 trials recorded in 4 ET patients. The predictor achieves a 100% sensitivity for all trials considered, along with an overall accuracy of 85.7% for all ET trials and 80.2% for all PD trials. By using a Pearsons chi-square test, the prediction results are shown to significantly differ from a random prediction outcome. SIGNIFICANCE The tremor prediction algorithm can be potentially used for designing the next generation of non-invasive closed-loop predictive ON-OFF controllers for deep brain stimulation (DBS), used for suppressing pathological tremor in such patients. Such a system is based on alternating ON and OFF DBS periods, an incoming tremor being predicted during the time intervals when DBS is OFF, so as to turn DBS back ON. The prediction should be a few seconds before tremor re-appears so that the patient is tremor-free for the entire DBS ON-OFF cycle and the tremor-free DBS OFF interval should be maximized in order to minimize the current injected in the brain and battery usage.

Interference Channel With Generalized Feedback (a.k.a. With Source Cooperation): Part I: Achievable Region

An Interference Channel with Generalized Feedback (IFC-GF) models a wireless network where the sources can sense the channel activity. The signal overheard from the channel provides information about the activity of the other sources and thus furnishes the basis for cooperation. This two-part paper studies achievable strategies (Part I) and outer bounds (Part II) for the general discrete memoryless IFC-GF with two source-destination pairs. In Part I, the generalized feedback is used to gain knowledge about the message sent by the other source and then exploited in two ways: a) to relay the messages that can be decoded at both destinations, thus realizing the gains of beam-forming of a distributed multiantenna system, and b) to hide the messages that can not be decoded at the nonintended destination, thus leveraging the interference “precancellation” property of dirty-paper coding. We show that our achievable region generalizes several known achievable regions for the IFC-GF and that it reduces to known achievable regions for the channels subsumed by the IFC-GF model. For the Gaussian channel, it is shown that source cooperation enlarges the achievable rate region of the corresponding IFC without generalized feedback/cooperation.

On the Benefits of Partial Channel State Information for Repetition Protocols in Block Fading Channels

This paper studies the throughput performance of hybrid automatic repeat request (HARQ) protocols over block fading Gaussian channels. It proposes new protocols that use the available feedback bit(s) not only to request a retransmission, but also to inform the transmitter about the instantaneous channel quality. An explicit protocol construction is given for any number of retransmissions and any number of feedback bits. The novel protocol is shown to simultaneously realize the gains of HARQ and of power control with partial channel state information. Remarkable throughput improvements are shown, especially at low and moderate signal-to-noise ratio (SNR), with respect to protocols that use the feedback bits for retransmission request only. In particular, for the case of a single retransmission and a single feedback bit, it is shown that the repetition is not needed at low SNR where the throughput improvement is due to power control only. On the other hand, at high SNR, the repetition is useful and the performance gain comes from a combination of power control and ability to make up for deep fades.

An outer bound region for Interference Channels with Generalized Feedback

Interference Channels with Generalized Feedback (IFC-GF) are a model for wireless communication systems with source cooperation. GF enables to enlarge the achievable rate region with respect to the non-cooperative IFC without requiring an increase in system resources. This paper develops an outer bound region on the capacity of general IFC-GF and then tighten it further for a class of semi-deterministic IFC-GF that include the “high SNR approximation” of the Gaussian channel and the Gaussian channel as special cases.

Gaussian fading interference channels: Power control

In this paper we consider power allocation policies for 2-user Gaussian interference channels (IFC) with ergodic fading, perfectly known at all terminals. Based on recently found outer bounds on the capacity region of unfaded IFCs, we determine the power allocation that maximizes a sum-rate outer bound. With this power allocation both users are simultaneously active when the power of the interfering signals is small relative to the power of the intended signals. Otherwise, only the user with the largest fading gain is active, similar to multi-access and broadcast channels. By considering a simplified version of the Han-Kobayashi region, we derive the power allocation that maximizes a sum-rate inner bound. Numerical results for iid Rayleigh fading show that the inner and our bounds are very close to one another. The structure of the determined power allocation policies suggests that practical power allocations can be designed based on only a bit of channel state information.

Coverage in mmWave Cellular Networks With Base Station Co-Operation

Signal outage, due to shadowing and blockage, is expected to be the main bottleneck in millimeter wave (mmWave) networks. Moreover, the anticipated dense deployment of base stations in mmWave networks is expected to increase the interference from strong line-of-sight base stations too, thus further increasing the probability of outage. To address the issue of reducing outage, this paper explores the possibility of base station co-operation in the downlink of mmWave heterogenous networks. The main focus of this work is showing that, in a stochastic geometry framework that incorporates blockage, co-operation from randomly located base stations decreases the probability of outage/increases the coverage probability. Coverage probabilities are derived accounting for: blockage, different fading distributions on the direct links (but always Rayleigh fading on the interference links), antenna directionality, and different tiers. Numerical results suggest that coverage with base station co-operation in dense mmWave systems (i.e., with high average number of base stations per square meter), without small scale fading on the direct communications links, and with any probability of signal blockage, considerably exceeds coverage without co-operation. In contrast, a small increase in coverage is reported when mmWave networks are less dense, have a high probability of signal blockage and the direct communications links are affected by Rayleigh fading.

Variable-rate coding for slowly fading Gaussian multiple-access channels

We consider a nonergodic multiple-access Gaussian block-fading channel where a fixed number of independent and identically distributed (i.i.d.) fading coefficients affect each codeword. Variable-rate coding with input power constraint enforced on a per-codeword basis is examined. A centralized power and rate allocation policy is determined as a function of the previous and present fading coefficients. The power control policy that optimizes the expected rates is obtained through dynamic programming and the average capacity region and the average capacity region per unit energy are characterized. Moreover, we study the slope of spectral efficiency curve versus E/sub b//N/sub 0/ (dB), and we quantify the penalty incurred by time-division multiple access (TDMA) over superposition coding in the low-power regime.

Adaptively controlling deep brain stimulation in essential tremor patient via surface electromyography

Abstract Objectives: We present patient test outcomes to show that on–off control of deep brain stimulation sequences in essential tremor patients is achievable in a self-adaptive manner via non-invasive surface-electromyography, to prevent tremors in these patients. Method: In our study, an essential tremor patient, who underwent bilateral deep brain stimulation implantation 8 years earlier, was subjected to deep brain stimulation at 130 pulses/second, with a 90-microsecond pulse-width, in packets of durations from 20 to 73 seconds and was monitored with surface-electromyography. Results: At the end of these stimulation packets, tremor-free intervals followed, averaging over 20 seconds, before tremor reappeared. Wavelet analysis of the eletromyographic signals allowed predicting onset of tremors at the end of the tremor-free intervals and was successful in all test cycles. Furthermore, once stimulation was restarted, the tremors disappeared within 0.5 seconds on average. When restarting stimulation approximately 2 seconds ahead of the end of tremor-free post-simulation intervals as predicted by visual inspection of unprocessed electromyograms, no tremors occurred during three successive cycles of stimulation-on and stimulation-off. Maximal ratio of tremor-free duration to stimulation duration was computed, to determine a best DBS (deep brain stimulation) duration range (20–35 seconds). Conclusions: We show existence of a tremor-free interval averaging over 20 seconds that follows applying stimulation packets of 20–35 seconds and that surface electomyogram allows predicting onset of tremor to facilitate activation of a next stimulation packet before tremor reappears. This establishes the feasibility of electromyographic-based predictive on–off control of deep brain stimulation in certain essential tremor patients. Best tremor-free duration to stimulation duration ratio may differ over the progression of the disorder and from patient to patient.