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Multicell Downlink Capacity with Coordinated Processing

  • Sheng Jing
  • David N.C. Tse
  • Joseph B. Soriaga
  • Jilei Hou
  • John E. Smee
  • Roberto Padovani
Open Access
Research Article
Part of the following topical collections:
  1. Theory and Applications in Multiuser/Multiterminal Communications

Abstract

We study the potential benefits of base-station (BS) cooperation for downlink transmission in multicell networks. Based on a modified Wyner-type model with users clustered at the cell-edges, we analyze the dirty-paper-coding (DPC) precoder and several linear precoding schemes, including cophasing, zero-forcing (ZF), and MMSE precoders. For the nonfading scenario with random phases, we obtain analytical performance expressions for each scheme. In particular, we characterize the high signal-to-noise ratio (SNR) performance gap between the DPC and ZF precoders in large networks, which indicates a singularity problem in certain network settings. Moreover, we demonstrate that the MMSE precoder does not completely resolve the singularity problem. However, by incorporating path gain fading, we numerically show that the singularity problem can be eased by linear precoding techniques aided with multiuser selection. By extending our network model to include cell-interior users, we determine the capacity regions of the two classes of users for various cooperative strategies. In addition to an outer bound and a baseline scheme, we also consider several locally cooperative transmission approaches. The resulting capacity regions show the tradeoff between the performance improvement and the requirement for BS cooperation, signal processing complexity, and channel state information at the transmitter (CSIT).

Keywords

Channel State Information Capacity Region Singularity Problem Cooperative Transmission Downlink Transmission 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Sheng Jing et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • Sheng Jing
    • 1
  • David N.C. Tse
    • 2
  • Joseph B. Soriaga
    • 3
  • Jilei Hou
    • 3
  • John E. Smee
    • 3
  • Roberto Padovani
    • 3
  1. 1.Laboratory for Information and Decision Systems (LIDS)Massachusetts Institute of Technology (MIT)CambridgeUSA
  2. 2.Electrical Engineering and Computer Science DepartmentUniversity of CaliforniaBerkeleyUSA
  3. 3.Corporate R & D DivisionQualcomm IncorporatedSan DiegoUSA

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