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Robust transceiver optimization for downlink coordinated base station systems: Distributed algorithm

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Title: Robust transceiver optimization for downlink coordinated base station systems: Distributed algorithm
Authors: Bogale, Tadilo Endeshaw, Vandendorpe, Luc, Chalise, B.K.
Contributors: UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique, Villanova State University - EE dpt
Source: IEEE Transactions on Signal Processing, Vol. 60, no. 1, p. 337-350 (2012)
Publication Year: 2012
Collection: DIAL@USL-B (Université Saint-Louis, Bruxelles)
Subject Terms: Distributed optimization and convex optimization, Multiuser multiple-input multiple-output (MIMO), Joint transceiver design, Lagrangian dual, Matrix, Minimum mean-square-error, Mobile station, Multi user multiple input single outputs, Multi-user, Power constraints, Precoders, Robust designs, Robust transceiver, Total power, Transceiver optimization, Weighted Sum, Antennas, Base stations, Channel state information, Computer simulation, Convex optimization, Design, MIMO systems, Antenna correlation, Optimization, Transceivers, Algorithms, Centralized algorithms, Channel estimation errors, Computationally efficient
Description: This paper considers the joint transceiver design for downlink multiuser multiple-input single-output (MISO) systems with coordinated base stations (BSs) where imperfect channel state information (CSI) is available at the BSs and mobile stations (MSs). By incorporating antenna correlation at the BSs and taking channel estimation errors into account, we solve two robust design problems: 1) minimizing the weighted sum of mean-square-error (MSE) with per BS antenna power constraint, and 2) minimizing the total power of all BSs with per user MSE target and per BS antenna power constraints. These problems are solved as follows. First, for fixed receivers, we propose centralized and novel computationally efficient distributed algorithms to jointly optimize the precoders of all users. Our centralized algorithms employ the second-order-cone programming (SOCP) approach, whereas, our novel distributed algorithms use the Lagrangian dual decomposition, modified matrix fractional minimization and an iterative method. Second, for fixed BS precoders, the receivers are updated by the minimum mean-square-error (MMSE) criterion. These two steps are repeated until convergence is achieved. In all of our simulation results, we have observed that the proposed distributed algorithms achieve the same performance as that of the centralized algorithms. Moreover, computer simulations verify the robustness of the proposed robust designs compared to the nonrobust/naive designs. © 2006 IEEE.
Document Type: article in journal/newspaper
Language: English
Relation: boreal:107492; http://hdl.handle.net/2078.1/107492
DOI: 10.1109/TSP.2011.2170167
Availability: http://hdl.handle.net/2078.1/107492
https://doi.org/10.1109/TSP.2011.2170167
Rights: info:eu-repo/semantics/restrictedAccess
Accession Number: edsbas.6CBA52B0
Database: BASE
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  Data: Robust transceiver optimization for downlink coordinated base station systems: Distributed algorithm
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  Data: <searchLink fieldCode="AR" term="%22Bogale%2C+Tadilo+Endeshaw%22">Bogale, Tadilo Endeshaw</searchLink><br /><searchLink fieldCode="AR" term="%22Vandendorpe%2C+Luc%22">Vandendorpe, Luc</searchLink><br /><searchLink fieldCode="AR" term="%22Chalise%2C+B%2EK%2E%22">Chalise, B.K.</searchLink>
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  Data: UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique<br />Villanova State University - EE dpt
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  Data: IEEE Transactions on Signal Processing, Vol. 60, no. 1, p. 337-350 (2012)
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  Data: 2012
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  Data: DIAL@USL-B (Université Saint-Louis, Bruxelles)
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  Data: <searchLink fieldCode="DE" term="%22Distributed+optimization+and+convex+optimization%22">Distributed optimization and convex optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Multiuser+multiple-input+multiple-output+%28MIMO%29%22">Multiuser multiple-input multiple-output (MIMO)</searchLink><br /><searchLink fieldCode="DE" term="%22Joint+transceiver+design%22">Joint transceiver design</searchLink><br /><searchLink fieldCode="DE" term="%22Lagrangian+dual%22">Lagrangian dual</searchLink><br /><searchLink fieldCode="DE" term="%22Matrix%22">Matrix</searchLink><br /><searchLink fieldCode="DE" term="%22Minimum+mean-square-error%22">Minimum mean-square-error</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+station%22">Mobile station</searchLink><br /><searchLink fieldCode="DE" term="%22Multi+user+multiple+input+single+outputs%22">Multi user multiple input single outputs</searchLink><br /><searchLink fieldCode="DE" term="%22Multi-user%22">Multi-user</searchLink><br /><searchLink fieldCode="DE" term="%22Power+constraints%22">Power constraints</searchLink><br /><searchLink fieldCode="DE" term="%22Precoders%22">Precoders</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+designs%22">Robust designs</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+transceiver%22">Robust transceiver</searchLink><br /><searchLink fieldCode="DE" term="%22Total+power%22">Total power</searchLink><br /><searchLink fieldCode="DE" term="%22Transceiver+optimization%22">Transceiver optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Weighted+Sum%22">Weighted Sum</searchLink><br /><searchLink fieldCode="DE" term="%22Antennas%22">Antennas</searchLink><br /><searchLink fieldCode="DE" term="%22Base+stations%22">Base stations</searchLink><br /><searchLink fieldCode="DE" term="%22Channel+state+information%22">Channel state information</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Convex+optimization%22">Convex optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Design%22">Design</searchLink><br /><searchLink fieldCode="DE" term="%22MIMO+systems%22">MIMO systems</searchLink><br /><searchLink fieldCode="DE" term="%22Antenna+correlation%22">Antenna correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization%22">Optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Transceivers%22">Transceivers</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Centralized+algorithms%22">Centralized algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Channel+estimation+errors%22">Channel estimation errors</searchLink><br /><searchLink fieldCode="DE" term="%22Computationally+efficient%22">Computationally efficient</searchLink>
– Name: Abstract
  Label: Description
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  Data: This paper considers the joint transceiver design for downlink multiuser multiple-input single-output (MISO) systems with coordinated base stations (BSs) where imperfect channel state information (CSI) is available at the BSs and mobile stations (MSs). By incorporating antenna correlation at the BSs and taking channel estimation errors into account, we solve two robust design problems: 1) minimizing the weighted sum of mean-square-error (MSE) with per BS antenna power constraint, and 2) minimizing the total power of all BSs with per user MSE target and per BS antenna power constraints. These problems are solved as follows. First, for fixed receivers, we propose centralized and novel computationally efficient distributed algorithms to jointly optimize the precoders of all users. Our centralized algorithms employ the second-order-cone programming (SOCP) approach, whereas, our novel distributed algorithms use the Lagrangian dual decomposition, modified matrix fractional minimization and an iterative method. Second, for fixed BS precoders, the receivers are updated by the minimum mean-square-error (MMSE) criterion. These two steps are repeated until convergence is achieved. In all of our simulation results, we have observed that the proposed distributed algorithms achieve the same performance as that of the centralized algorithms. Moreover, computer simulations verify the robustness of the proposed robust designs compared to the nonrobust/naive designs. © 2006 IEEE.
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1109/TSP.2011.2170167
    Languages:
      – Text: English
    Subjects:
      – SubjectFull: Distributed optimization and convex optimization
        Type: general
      – SubjectFull: Multiuser multiple-input multiple-output (MIMO)
        Type: general
      – SubjectFull: Joint transceiver design
        Type: general
      – SubjectFull: Lagrangian dual
        Type: general
      – SubjectFull: Matrix
        Type: general
      – SubjectFull: Minimum mean-square-error
        Type: general
      – SubjectFull: Mobile station
        Type: general
      – SubjectFull: Multi user multiple input single outputs
        Type: general
      – SubjectFull: Multi-user
        Type: general
      – SubjectFull: Power constraints
        Type: general
      – SubjectFull: Precoders
        Type: general
      – SubjectFull: Robust designs
        Type: general
      – SubjectFull: Robust transceiver
        Type: general
      – SubjectFull: Total power
        Type: general
      – SubjectFull: Transceiver optimization
        Type: general
      – SubjectFull: Weighted Sum
        Type: general
      – SubjectFull: Antennas
        Type: general
      – SubjectFull: Base stations
        Type: general
      – SubjectFull: Channel state information
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Convex optimization
        Type: general
      – SubjectFull: Design
        Type: general
      – SubjectFull: MIMO systems
        Type: general
      – SubjectFull: Antenna correlation
        Type: general
      – SubjectFull: Optimization
        Type: general
      – SubjectFull: Transceivers
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Centralized algorithms
        Type: general
      – SubjectFull: Channel estimation errors
        Type: general
      – SubjectFull: Computationally efficient
        Type: general
    Titles:
      – TitleFull: Robust transceiver optimization for downlink coordinated base station systems: Distributed algorithm
        Type: main
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            NameFull: Bogale, Tadilo Endeshaw
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            NameFull: Vandendorpe, Luc
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            NameFull: Chalise, B.K.
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            NameFull: UCL - SST/ICTM/ELEN - Pôle en ingénierie électrique
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            NameFull: Villanova State University - EE dpt
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              Type: published
              Y: 2012
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            – TitleFull: IEEE Transactions on Signal Processing, Vol. 60, no. 1, p. 337-350 (2012
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