August 14, 2017

Probabilistic Shaping via Non-Binary Codes

  • Jardel F.
  • Joseph J. Boutros
  • Measson C.

Shaping refers to engineering methods that adapt the signal distribution to a communication channel for increased efficiency. Recently, shaping methods have regained interest especially in optical communications where current technologies operate close the fundamental limits of the linear fiber channel model. Probabilistic amplitude shaping (PAS) has been proposed in [1] as a rather simple and efficient way to shape binarylabeled QAM constellations. In this paper, we show how this method can be generalized to non-binary alphabets. Information data is assumed to be shaped via look-up-tables and modern coding schemes to be used. We first present a scheme based on time sharing over prime fields. Second we design p2 circular constellations which are a natural modulation scheme for nonbinary PAS.

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Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...