MIMO Equalization for Multi-Gbit/s Communication Under Channel Variability

  • D. Vande Ginste
  • Guenach M.
  • Jacobs L.
  • Jelle Bailleul
  • Marc Moeneclae
  • P. Manfredi

Multiple-input multiple-output (MIMO) equalization at the transmitter and/or receiver has been shown to enable multi-Gbit/s communication over lowcost electrical interconnects. Because of the high operating frequencies, however, the interconnects become susceptible to manufacturing tolerances and the equalization filters must be adjusted to the specific channel realization to achieve optimal performance. To reduce the implementation complexity, we propose a MIMO transceiver scheme where (part of) the equalization filters depend on the channel statistics rather than the actual channel. More specifically, we consider fixed MIMO linear pre-equalization, which avoids the need for a feedback channel with the channel state information, combined with MIMO decision feedback equalization (DFE) at the receiver. Depending on the level of channel variability, the DFE filters can be either fixed or adjustable.

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 ...