5,290 research outputs found
Capacity of Molecular Channels with Imperfect Particle-Intensity Modulation and Detection
This work introduces the particle-intensity channel (PIC) as a model for
molecular communication systems and characterizes the properties of the optimal
input distribution and the capacity limits for this system. In the PIC, the
transmitter encodes information, in symbols of a given duration, based on the
number of particles released, and the receiver detects and decodes the message
based on the number of particles detected during the symbol interval. In this
channel, the transmitter may be unable to control precisely the number of
particles released, and the receiver may not detect all the particles that
arrive. We demonstrate that the optimal input distribution for this channel
always has mass points at zero and the maximum number of particles that can be
released. We then consider diffusive particle transport, derive the capacity
expression when the input distribution is binary, and show conditions under
which the binary input is capacity-achieving. In particular, we demonstrate
that when the transmitter cannot generate particles at a high rate, the optimal
input distribution is binary.Comment: Accepted at IEEE International Symposium on Information Theory (ISIT
Information Flow Structure in Large-Scale Product Development Organizational Networks
In recent years, understanding the structure and function of complex networks has become the foundation for explaining many different real- world complex social, information, biological and technological phenomena. Techniques from statistical physics have been successfully applied to the analysis of these networks, and have uncovered surprising statistical structural properties that have also been shown to have a major effect on their functionality, dynamics, robustness, and fragility. This paper examines, for the first time, the statistical properties of strategically important complex organizational information-based networks -- networks of people engaged in distributed product development -- and discusses the significance of these properties in providing insight into ways of improving the strategic and operational decision-making of the organization. We show that the patterns of information flows that are at the heart of large-scale product development networks have properties that are like those displayed by information, biological and technological networks. We believe that our new analysis methodology and empirical results are also relevant to other organizational information-based human or nonhuman networks.Large-scale product development, socio-technical systems, information systems, social networks, Innovation, complex engineering systems, distributed problem solving
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