Enhanced Control Signal and Data Detection for 5G Multicarrier Low-Power Communications

  • Chen Y.
  • Doll M.

As being a complementary technique for Machine Type Communications (MTC) in future 5th Generation (5G) wireless communications, the control mechanism and control signaling should preferably be able to operate at possibly low Signal-to-Noise Ratio (SNR) without interfering the existing cellular network. In this paper, we propose an enhanced mechanism for the control signaling, targeting to low-power communications. It enables the detection of sporadically transmitted data packet of a user at relatively low SNR. Further, we focus on the low-power channel estimation and data detection as an additional proof-of-concept within a multicarrier system. The superimposed pilots are exploited 2-dimensionally in time and frequency to jointly detect the data and estimate the channel.

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 ...