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Transmission power optimization of convolutional coded VBLAST system

Lookup NU author(s): Dr Charalampos Tsimenidis, Professor Bayan Sharif

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Abstract

There is a growing demand for huge capacity and high data rate transmission fuelled by a steady increase in subscriber numbers. Currently, achieving high data rate transmission reliability over multipath fading channels in multiple-input multiple-output (MIMO) systems poses a major challenge to communication system designers. Conventional Vertical-Bell Labs layered space-time (V-BLAST) based systems achieve high spectral efficiency by employing diversity; however, their performance is sensitive to the near-far problem. The Newton and Interior Point Methods (IPM), which satisfy the Lagrangian and Karush-Kuhn-Tucker (KKT) conditions are regarded as some of the most efficient algorithms for resolving optimal power allocation in MIMO channels. Turbo BLAST (TBLAST) is also a promising technique, which provides diversity by encoding each substream, in contrast to conventional VBLAST. However, system performance is limited due to error propagation and simple power allocation in conventional coded BLAST system. On the other hand, the optimal power allocation depends on Lagrangian method and strict condition, i.e. perfect estimation for KKT condition. In this paper, the proposed scheme depends on the turbo principle for MIMO-OFCDM (Orthogonal Frequency-Code Division Multiple Access) systems. Furthermore, an optimal power allocation scheme is proposed that depends on Automatic Differentiation (AD) method, which can be regarded as an alternative algorithm in cases where the KKT condition is not met The performance of the proposed system is evaluated and compared to conventional schemes by means of simulations. ©2005 IEEE.


Publication metadata

Author(s): Yin W, Tsimenidis CC, Sharif BS

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: IEEE Vehicular Technology Conference

Year of Conference: 2005

Pages: 945-948

ISSN: 9780780388871

Publisher: IEEE


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