papr reduction
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Transcript of papr reduction
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A Diffusion-Based Binary
Digital Communication System
Gyan DeepMT15097
Published in :- Communications (ICC), 2012 IEEE International Conference on. IEEE, 2012.
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Abstract
• Design of a binary digital communication system is proposed based on particle diffusion. Stochastic signaling through On-Off Keying (OOK) for random particle emission and a diffusion channel with memory is considered.
• The optimal decision threshold for the receiver detection is derived through mutual information maximization.
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• Four different communication mechanisms for nanomachines have been considered and proposed so far, i.e., mechanical, acoustic, electromagnetic, and molecular communications
• Molecular communication is the transfer of information using particles as message carriers, is considered one of the most promising among the four.
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• The particles can either follow a specific path or be guided by a fluidic mediumto reach the destination.
• Diffusion-based communication refers to the situation where molecules reach the destination relying solely on the laws of particle diffusion.
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Model
• A time-slotted system with signaling intervalTs.
• Assume perfect synchronization betweenthe transmitter and the receiver.
• With a priori probability p1, a random number of molecules is emitted in an instantaneous fashion by the transmitter at the beginning of each signaling interval to signify 1; no molecule is emitted to signify 0.
• Once released into the propagation medium, the molecules are assumed to diffusefreely, and the dynamics is described by the Brownian motion.
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Diffusion channel as a binary hypothesis testing Channel
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Xi and Yi denote the input and output random variables of the ith signaling interval
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Model
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Detection with Perfect apriori Information
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Detection with Perfect apriori Information
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Detection with Perfect apriori Information
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Detection with Perfect apriori Information
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Detection with Perfect apriori Information
The simplified test statistic of z is put here
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Detection with Perfect apriori Information
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Detection with Perfect apriori Information
• Nita here is optimal threshold• In case , receiver has control over apriori
probability
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Detection without apriori Information
• The decision threshold η∗(p1) thus maximizes the integrated information amount independent of the actual a priori probability
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Results
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Results
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Results
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Results
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Conclusion
• Numerical results indicate that in the case of diffusion in one or two dimensions, the information of a priori probability plays a key role in optimizing the system performance, whileit does not when considering the diffusion in three dimensions.
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Thank You