12,525 research outputs found
Towards real-world complexity: an introduction to multiplex networks
Many real-world complex systems are best modeled by multiplex networks of
interacting network layers. The multiplex network study is one of the newest
and hottest themes in the statistical physics of complex networks. Pioneering
studies have proven that the multiplexity has broad impact on the system's
structure and function. In this Colloquium paper, we present an organized
review of the growing body of current literature on multiplex networks by
categorizing existing studies broadly according to the type of layer coupling
in the problem. Major recent advances in the field are surveyed and some
outstanding open challenges and future perspectives will be proposed.Comment: 20 pages, 10 figure
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
Retrieval behavior and thermodynamic properties of symmetrically diluted Q-Ising neural networks
The retrieval behavior and thermodynamic properties of symmetrically diluted
Q-Ising neural networks are derived and studied in replica-symmetric mean-field
theory generalizing earlier works on either the fully connected or the
symmetrical extremely diluted network. Capacity-gain parameter phase diagrams
are obtained for the Q=3, Q=4 and state networks with uniformly
distributed patterns of low activity in order to search for the effects of a
gradual dilution of the synapses. It is shown that enlarged regions of
continuous changeover into a region of optimal performance are obtained for
finite stochastic noise and small but finite connectivity. The de
Almeida-Thouless lines of stability are obtained for arbitrary connectivity,
and the resulting phase diagrams are used to draw conclusions on the behavior
of symmetrically diluted networks with other pattern distributions of either
high or low activity.Comment: 21 pages, revte
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