• DocumentCode
    787113
  • Title

    Adaptive loading for OFDM/SDMA-based wireless networks

  • Author

    Thoen, Steven ; Van der Perre, Liesbet ; Engels, Marc ; De Man, Hugo

  • Author_Institution
    Resonext Commun., Leuven, Belgium
  • Volume
    50
  • Issue
    11
  • fYear
    2002
  • fDate
    11/1/2002 12:00:00 AM
  • Firstpage
    1798
  • Lastpage
    1810
  • Abstract
    The two major obstacles toward high-capacity indoor wireless networks are distortion due to the indoor channel and the limited availability of bandwidth which necessitates a high spectral efficiency. A combined orthogonal-frequency division multiplexing/spatial-diversity multiple access (OFDM/SDMA) approach can effectively tackle both obstacles. The channel distortion due to multipath propagation is easily mitigated with OFDM while the bandwidth efficiency can be increased with the use of SDMA. In order to keep the network´s cost acceptable, simplified SDMA processors are preferred over the exponentially complex optimal maximum-likelihood processors. However, these simplified processors perform significantly worse than the optimal ones in terms of average bit error rate (BER). In this paper, we show that by adapting the constellation sizes applied on the individual subcarriers to the channel conditions, the performance of OFDM/SDMA processors can be significantly enhanced. In the uplink, we derive simple closed-form equations for the optimal constellation sizes for both a simple linear minimum mean-square error (MMSE) detector and for a nonlinear MMSE decision feedback equalizer (DFE) detector. Furthermore, for each detector, we introduce a simplified loading algorithm which lowers the computational and signaling complexity substantially at a small performance penalty. In the downlink, we study the dual precoders of the uplink detectors, respectively, the linear MMSE precoder and the nonlinear Tomlinson-Harashima (TH) MMSE-based precoder. For both precoders, we derive expressions for the optimal and the simplified constellation sizes. Additionally, we show that in time-division duplexing systems, the constellation distribution of a set of dual detectors/precoders is identical for up- and downlink, which effectively halves the computational complexity of adaptive loading. In the fully loaded uplink, the proposed adaptive loading algorithm results in a gain of 9 dB for a BER=10-3 for the linear MMSE detector and a gain of 4.5 dB for the nonlinear MMSE-DFE detector. In the fully loaded downlink, a gain of 6.3 dB is achieved for the MMSE precoder and 5.5 dB for the TH-MMSE precoder.
  • Keywords
    OFDM modulation; decision feedback equalisers; error statistics; indoor radio; least mean squares methods; multipath channels; radio receivers; signal detection; space division multiple access; time division multiplexing; wireless LAN; 4.5 dB; 5.5 dB; 6.3 dB; 9 dB; BER; OFDM/SDMA-based wireless networks; TH-MMSE precoder; adaptive loading; adaptive loading algorithm; bandwidth efficiency; bit error rate; closed-form equations; combined orthogonal-frequency division multiplexing/spatial-diversity multiple access; computational complexity; constellation distribution; constellation sizes; distortion; dual detectors/precoders; dual precoders; high-capacity indoor wireless networks; indoor channel; linear MMSE detector; linear MMSE precoder; linear minimum mean-square error detector; loaded downlink; multipath propagation; nonlinear MMSE DFE detector; nonlinear MMSE decision feedback equalizer detector; nonlinear Tomlinson-Harashima MMSE-based precoder; optimal constellation sizes; signaling complexity; simplified loading algorithm; spectral efficiency; subcarriers; time-division duplexing systems; uplink detectors; Bandwidth; Bit error rate; Decision feedback equalizers; Detectors; Downlink; Gain; Multiaccess communication; Nonlinear distortion; OFDM; Wireless networks;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/TCOMM.2002.805260
  • Filename
    1097890