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Conference paperRosas De Andraca F, Manolakis K, Oberli C, et al., 2018,
Impact of the interference correlation on the decoding error statistics
, 51th Asilomar Conference on Signals, Systems, and Computers, Publisher: IEEE, ISSN: 2576-2303Scenarios where interference is correlated with useful signals are often met in communications systems. Interestingly, even though uncorrelated interference mitigation has been extensively studied by the literature, there is still lack of insight into how correlation can affects information transfer processes. In this paper we formally address this issue and show how a positive correlation between the interference and useful signal power introduces a non-intuitive increase in the diversity gain, improving the error statistics with respect to the uncorrelated case. In contrast, the diversity gain decreases under negative correlation, degrading the system performance. These findings are confirmed by simulations for scenarios of practical relevance.
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Conference paperRosas De Andraca F, Azari MM, Murillo Y, et al., 2018,
Coverage maximization for a poisson field of drone cells
, 28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE PIMRC 2017), Publisher: IEEE, ISSN: 2166-9589The use of drone base stations to provide wireless connectivity for ground terminals is becoming a promising part of future technologies. The design of such aerial networks is however different compared to cellular 2D networks, as antennas from the drones are looking down, and the channel model becomes height-dependent. In this paper, we study the effect of antenna patterns and height-dependent shadowing. We consider a random network topology to capture the effect of dynamic changes of the flying base stations. First we characterize the aggregate interference imposed by the co-channel neighboring drones. Then we derive the link coverage probability between a ground user and its associated drone base station. The result is used to obtain the optimum system parameters in terms of drones antenna beamwidth, density and altitude. We also derive the average LoS probability of the associated drone and show that it is a good approximation and simplification of the coverage probability in low altitudes up to 500 m according to the required signal-to-interference-plus-noise ratio (SINR).
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Conference paperAzari MM, Rosas F, Chiumento A, et al., 2018,
Coexistence of terrestrial and aerial users in cellular networks
, 2017 IEEE Globecom Workshops (GC Wkshps), Publisher: Institute of Electrical and Electronics EngineersEnabling the integration of aerial mobile users into existing cellular networks would make possible a number of promising applications. However, current cellular networks have not been designed to serve aerial users, and hence an exploration of design parameters is required in order to allow network providers to modify their current infrastructure. As a first step in this direction, this paper provides an in-depth analysis of the coverage probability of the downlink of a cellular network that serves both aerial and ground users. We present an exact mathematical characterization of the coverage probability, which includes the effect of base stations (BSs) height, antenna pattern and drone altitude for various types of urban environments. Interestingly, our results show that the favorable propagation conditions that aerial users enjoy due to their altitude is also their strongest limiting factor, as it leaves them vulnerable to interference. This negative effect can be substantially reduced by optimizing the flying altitude, the base station height and antenna down-tilt angle. Moreover, lowering the base station height and increasing down-tilt angle are in general beneficial for both terrestrial and aerial users, pointing out a possible path to enable their coexistence.
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Journal articleSiddiqui M, Wedemann RS, Jensen HJ, 2018,
Avalanches and generalized memory associativity in a network model for conscious and unconscious mental functioning
, Physica A: Statistical Mechanics and its Applications, Vol: 490, Pages: 127-138, ISSN: 0378-4371We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud’s ideas regarding the neuroses and that consciousness is related with symbolic and linguistic memory activity in the brain. It incorporates the Stariolo–Tsallis generalization of the Boltzmann Machine in order to model memory retrieval and associativity. In the present work, we define and measure avalanche size distributions during memory retrieval, in order to gain insight regarding basic aspects of the functioning of these complex networks. The avalanche sizes defined for our model should be related to the time consumed and also to the size of the neuronal region which is activated, during memory retrieval. This allows the qualitative comparison of the behaviour of the distribution of cluster sizes, obtained during fMRI measurements of the propagation of signals in the brain, with the distribution of avalanche sizes obtained in our simulation experiments. This comparison corroborates the indication that the Nonextensive Statistical Mechanics formalism may indeed be more well suited to model the complex networks which constitute brain and mental structure.
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Journal articleNesbitt D, Pruessner G, Lee C, 2017,
Edge instability in incompressible planar active fluids
, Physical Review E, Vol: 96, ISSN: 1539-3755Interfacial instability is highly relevant to many important biological processes. A key example arises in wound healing experiments, which observe that an epithelial layer with an initially straight edge does not heal uniformly. We consider the phenomenon in the context of active fluids. Improving upon the approximation used by Zimmermann, Basan, and Levine [Eur. Phys. J.: Spec. Top. 223, 1259 (2014)], we perform a linear stability analysis on a two-dimensional incompressible hydrodynamic model of an active fluid with an open interface. We categorize the stability of the model and find that for experimentally relevant parameters, fingering instability is always absent in this minimal model. Our results point to the crucial role of density variation in the fingering instability in tissue regeneration.
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Conference paperRosas De Andraca F, Chen K-C, 2017,
Social learning against data falsification in sensor networks
, Conference on Complex Networks 2017, Publisher: Springer Verlag, Pages: 704-716, ISSN: 1860-949XSensor networks generate large amounts of geographically-distributed data. The conventional approach to exploit this data is to first gather it in a special node that then performs processing and inference. However, what happens if this node is destroyed, or even worst, if it is hijacked? To explore this problem, in this work we consider a smart attacker who can take control of critical nodes within the network and use them to inject false information. In order to face this critical security thread, we propose a novel scheme that enables data aggregation and decision-making over networks based on social learning, where the sensor nodes act resembling how agents make decisions in social networks. Our results suggest that social learning enables high network resilience, even when a significant portion of the nodes have been compromised by the attacker.
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Journal articleWillis G, Pruessner G, 2017,
Spatio-temporal correlations in the Manna model in one, three and five dimensions
, International Journal of Modern Physics B, Vol: 32, ISSN: 0217-9792Although the paradigm of criticality is centered around spatial correlations and their anomalous scaling, not many studies of self-organized criticality (SOC) focus on spatial correlations. Often, integrated observables, such as avalanche size and duration, are used, not least as to avoid complications due to the unavoidable lack of translational invariance. The present work is a survey of spatio-temporal correlation functions in the Manna Model of SOC, measured numerically in detail in d
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Journal articleFallesen T, Roostalu J, Duellberg C, et al., 2017,
Ensembles of Bidirectional Kinesin Cin8 Produce Additive Forces in Both Directions of Movement
, Biophysical Journal, Vol: 113, Pages: 2055-2067, ISSN: 0006-3495Most kinesin motors move in only one direction along microtubules. Members of the kinesin-5 subfamily were initially described as unidirectional plus-end-directed motors and shown to produce piconewton forces. However, some fungal kinesin-5 motors are bidirectional. The force production of a bidirectional kinesin-5 has not yet been measured. Therefore, it remains unknown whether the mechanism of the unconventional minus-end-directed motility differs fundamentally from that of plus-end-directed stepping. Using force spectroscopy, we have measured here the forces that ensembles of purified budding yeast kinesin-5 Cin8 produce in microtubule gliding assays in both plus- and minus-end direction. Correlation analysis of pause forces demonstrated that individual Cin8 molecules produce additive forces in both directions of movement. In ensembles, Cin8 motors were able to produce single-motor forces up to a magnitude of ∼1.5 pN. Hence, these properties appear to be conserved within the kinesin-5 subfamily. Force production was largely independent of the directionality of movement, indicating similarities between the motility mechanisms for both directions. These results provide constraints for the development of models for the bidirectional motility mechanism of fission yeast kinesin-5 and provide insight into the function of this mitotic motor.
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Journal articleClough JR, Evans TS, 2017,
Embedding graphs in Lorentzian spacetime
, PLOS ONE, Vol: 12, ISSN: 1932-6203Geometric approaches to network analysis combine simply defined models with great descriptive power. In this work we provide a method for embedding directed acyclic graphs (DAG) into Minkowski spacetime using Multidimensional scaling (MDS). First we generalise the classical MDS algorithm, defined only for metrics with a Riemannian signature, to manifolds of any metric signature. We then use this general method to develop an algorithm which exploits the causal structure of a DAG to assign space and time coordinates in a Minkowski spacetime to each vertex. As in the causal set approach to quantum gravity, causal connections in the discrete graph correspond to timelike separation in the continuous spacetime. The method is demonstrated by calculating embeddings for simple models of causal sets and random DAGs, as well as real citation networks. We find that the citation networks we test yield significantly more accurate embeddings that random DAGs of the same size. Finally we suggest a number of applications in citation analysis such as paper recommendation, identifying missing citations and fitting citation models to data using this geometric approach.
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Journal articleRochester C, Sartor A, Pruessner G, et al., 2017,
"One dimensional" double layer. The effect of size asymmetry of cations and anions on charge-storage in ultranarrow nanopores-an Ising model theory
, RUSSIAN JOURNAL OF ELECTROCHEMISTRY, Vol: 53, Pages: 1165-1170, ISSN: 1023-1935We develop a statistical mechanical theory of charge storage in quasi-single-file ionophilic nanopores with pure room temperature ionic liquid cations and anions of different size. The theory is mapped to an extension of the Ising model exploited earlier for the case of cations and anions of the same size. We calculate the differential capacitance and the stored energy density per unit surface area of the pore. Both show asymmetry in the dependence on electrode potential with respect to the potential of zero charge, related to the difference in the size of the ions, which will be interesting to investigate experimentally. It also approves the increase of charge storage capacity via obstructed charging, which in these systems emerges for charging nanopores with smaller ions.
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