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A VLSI 8 × 8 MIMO Near-ML Detector with Preprocessing

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Abstract

Multiple-input multiple-output (MIMO) systems are of significant interest due to their ability to increase the capacity of wireless communications systems, but for these to be useful they must also be practical for implementation in VLSI circuits. A particularly difficult part of these systems is the detector, where the optimal maximum-likelihood solution is desirable, but cannot be directly implemented due to its exponential complexity. This paper addresses this challenge and presents a digital circuit design for an 8×8 MIMO detection problem. A key feature is the integrated channel preprocessing unit, which performs the channel decomposition functions that are either omitted or performed “off-line” in other designs. The proposed device achieves near maximum likelihood bit error rate results at 57.6 Mbps. Other novelties include a high speed sorting mechanism and power saving features.

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References

  1. Garrett, D., Davis, L., ten Brink, S., Hochwald, B., & G. Knagge (2004). A 28.8 Mb/s 4×4 MIMO 3G high-speed downlink packet access receiver with normalized least mean square equalization. In IEEE international solid-state circuits conference (ISSCC) (pp. 420–421) (February).

  2. Guo, Z., & Nilsson, P. (2006). Algorithm and implementation of the k-best sphere decoding for MIMO detection. IEEE Journal on Selected Areas in Communications, 24, 491–503 (March).

    Article  Google Scholar 

  3. Davis, L. M., Garrett, D. C., Woodward, G. K., Bickerstaff, M. A., & Mullany, F. J. (2003). System architecture and ASICs for a MIMO 3GPP-HSDPA receiver. In 57th IEEE semiannual vehicular technology conference, 2003. VTC 2003-Spring (Vol. 2, pp. 818–822) (April).

  4. Hochwald, B., & ten Brink, S. (2003). Achieving near-capacity on a multiple-antenna channel. IEEE Transactions on Information Theory, 51, 389–399 (March).

    Google Scholar 

  5. Knagge, G., Woodward, G., Ninness, B., & Weller, S. (2004). An optimised parallel tree search for multiuser detection with VLSI implementation strategy. In IEEE global telecommunications conference, 2004. (GLOBECOM ’04) (pp. 2440–2444) (December).

  6. Knagge, G., Bickerstaff, M., Ninness, B., Weller, S., & Woodward, G. (2006). A VLSI 8×8 MIMO near-ML decoder engine. In IEEE workshop on signal processing systems design and implementation (SiPS06) (pp. 387–392) (October).

  7. Verdú, S. (1986). Minimum probability of error for asynchronous Gaussian multiple-access channels. IEEE Transactions on Information Theory, 32, 85–96 (January).

    Article  MATH  Google Scholar 

  8. Burg, A., Borgmann, M., Wenk, M., Zellweger, M., Fichtner, W., & Bolcskei, H. (2005). VLSI implementation of MIMO detection using the sphere decoding algorithm. IEEE Journal of Solid State Circuits, 40, 1566–1577 (July).

    Article  Google Scholar 

  9. Davis, L. M. (2003). Scaled and decoupled cholesky and QR decompositions with application to spherical MIMO detection. IEEE wireless communications & networking conference (WCNC) (pp. 326–331) (March).

  10. Knagge, G., Garrett, D. C., Venkatesan, S., & Nicol, C. (2003). Matrix datapath architecture for an iterative 4×4 MIMO noise whitening algorithm. In ACM great lakes symposium on VLSI circuits (GLSVLSI) (pp. 590–593) (April).

  11. Sharma, N. K. (1997). Modular design of a large sorting network. In Third international symposium on parallel architectures, algorithms, and networks, 1997. (I-SPAN ’97). (pp. 362–368) (December).

  12. Burg, A., Borgmann, M., Wenk, M., Studer, C., & Bolcskei, H. (2006). Advanced receiver algorithms for mimo wireless communications. In Proc. design automation and test in Europe conf. (DATE) (March).

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, New South Wales, 2308, Australia

    Geoff Knagge, Brett Ninness & Steven R. Weller

  2. National ICT Australia (NICTA), Locked Bag 9013, Alexandria, New South Wales, 1435, Australia

    Mark Bickerstaff

  3. Toshiba Research Europe Limited, 32 Queen Square, Bristol, BS1 4ND, UK

    Graeme Woodward

Authors
  1. Geoff Knagge
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  2. Mark Bickerstaff
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  3. Brett Ninness
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  4. Steven R. Weller
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  5. Graeme Woodward
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Correspondence to Geoff Knagge.

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Knagge, G., Bickerstaff, M., Ninness, B. et al. A VLSI 8 × 8 MIMO Near-ML Detector with Preprocessing. J Sign Process Syst Sign Image Video Technol 56, 229–247 (2009). https://doi.org/10.1007/s11265-008-0222-6

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  • DOI: https://doi.org/10.1007/s11265-008-0222-6

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