35,860 research outputs found
Single Bit and Reduced Dimension Diffusion Strategies Over Distributed Networks
We introduce novel diffusion based adaptive estimation strategies for
distributed networks that have significantly less communication load and
achieve comparable performance to the full information exchange configurations.
After local estimates of the desired data is produced in each node, a single
bit of information (or a reduced dimensional data vector) is generated using
certain random projections of the local estimates. This newly generated data is
diffused and then used in neighboring nodes to recover the original full
information. We provide the complete state-space description and the mean
stability analysis of our algorithms.Comment: Submitted to the IEEE Signal Processing Letter
Compressive Diffusion Strategies Over Distributed Networks for Reduced Communication Load
We study the compressive diffusion strategies over distributed networks based
on the diffusion implementation and adaptive extraction of the information from
the compressed diffusion data. We demonstrate that one can achieve a comparable
performance with the full information exchange configurations, even if the
diffused information is compressed into a scalar or a single bit. To this end,
we provide a complete performance analysis for the compressive diffusion
strategies. We analyze the transient, steady-state and tracking performance of
the configurations in which the diffused data is compressed into a scalar or a
single-bit. We propose a new adaptive combination method improving the
convergence performance of the compressive diffusion strategies further. In the
new method, we introduce one more freedom-of-dimension in the combination
matrix and adapt it by using the conventional mixture approach in order to
enhance the convergence performance for any possible combination rule used for
the full diffusion configuration. We demonstrate that our theoretical analysis
closely follow the ensemble averaged results in our simulations. We provide
numerical examples showing the improved convergence performance with the new
adaptive combination method.Comment: Submitted to IEEE Transactions on Signal Processin
Improving Diffusion-Based Molecular Communication with Unanchored Enzymes
In this paper, we propose adding enzymes to the propagation environment of a
diffusive molecular communication system as a strategy for mitigating
intersymbol interference. The enzymes form reaction intermediates with
information molecules and then degrade them so that they have a smaller chance
of interfering with future transmissions. We present the reaction-diffusion
dynamics of this proposed system and derive a lower bound expression for the
expected number of molecules observed at the receiver. We justify a
particle-based simulation framework, and present simulation results that show
both the accuracy of our expression and the potential for enzymes to improve
communication performance.Comment: 15 pages, 4 figures, presented at the 7th International Conference on
Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS
2012) in Lugano, Switzerlan
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