May 17, 2017

5G Radio Access Protocols with Multi-User Detection for URLLC

  • Marco Centenaro
  • Saur S.

In this paper we present both collision-free and contention-based radio access protocols for sporadic small data packet transmissions in the uplink of 5G. We compare them by computer simulations with respect to throughput and a joint latency plus reliability metric. Based on that we analyze the tradeoff between number of transmission attempts and advanced collision resolution. In a second study we investigate the impact of multi-user detection on the performance. The key outcome of our study is that contention-based radio access combined with multi-user detection is well suited for URLLC applications with required error rates down to 10-5 in a low traffic load scenario.

View Original Article

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 ...