Low-Cost Superimposed Pilots Based Receiver for Massive MIMO in Multicarrier System

  • Chen Y.

In this paper, we present a low-cost receive algorithm for massive Multiple-Input Multiple-Output (MIMO) system, which exploits 2-dimensional superimposed pilots in time and frequency domain. By introducing the well designed superimposed pilots, the pilot contamination can be systematically suppressed. Even within a small time-frequency allocation, transforming the 2-dimensional superimposed pilots to an equivalent one-dimensional orthogonal pattern, the provided processing gain can be adequate to achieve precise channel estimation on the basis of linear operations. In this paper, we provide the proof-of-concept with link layer simulation for multicarrier system. Additionally, the 2-dimensional trellis-based channel estimation, as a high-cost solution, will be compared to the proposed solution, in order to quantify the reasonability of the trade-off.

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 ...