PhysComNet 2015 - Workshop PhysComNet : Physics-inspired paradigms in wireless communication and networks

Current wireless networks are reaching a level of complexity in which conventional models and design tools are no longer valid, and fail to provide the ever-growing performance requirements in terms of peak rates and mobility that users demand nowadays. Delay constraints, scaling laws, parameter estimation (e.g., in massive MIMO networks), interference management and modeling techniques, and distributed implementations are some of the challenging aspects to be researched for next-generation wireless networks. This calls for creative cross-disciplinary methods to analyze, model, understand, and design algorithms for future wireless networks, which will be characterized by denser and heterogeneous deployments.
Recently, there have been several fruitful insights and approaches inspired from the areas of physics and mathematics, including statistical mechanics, elementary particle physics, algebraic and stochastic geometry, machine learning, electrostatics, game theory, and random matrix theory, among others. This interdisciplinary workshop aims to bring together active researchers with different backgrounds interested in research on future wireless communications and networks.
Domains of interest include, but are not limited to:
Statistical mechanics methods for the derivation of performance bounds and the development of iterative algorithms
Design of distributed and diffusion-based algorithms
Parametric and nonparametric methods in machine learning
Algebraic-geometric methods for code, signal, and receiver design
Compressed sensing aspects
Networks with feedback and/or delay constraints
Applications of random matrix theory methods to large systems
Network optimization using game theory
Graph theory concepts for analyzing connectivity, scalability, and routing issues
Interference management techniques
Statistical tools for interference modeling