March 27, 2017

Dielectric powder loaded coaxial-cavity filters

  • Bulja S.
  • Doumanis E.
  • Pivit F.

In this paper we demonstrate the use of low-loss powders in the design and fabrication of RF filters. Initially, several different powders are tested for their RF performance - in particular their relative dielectric permittivity and loss tangent. Then, based on the information obtained in this way, the best performance powder is used to design a 5 pole Chebyshev filter operating at a centre frequency of 779 MHz, with a bandwidth of 17 MHz. Upon fabrication of the filter housing, the filter cavities are filled with the powder. Compaction of the powders is achieved in a systematic way and has resulted in stable performance.

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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 ...