DOI QR코드

DOI QR Code

On the Hardware Complexity of Tree Expansion in MIMO Detection

  • Kong, Byeong Yong (Division of Electrical, Electronic, and Control Engineering, Kongju National University) ;
  • Lee, Youngjoo (Department of Electrical Engineering, Pohang University of Science and Technology) ;
  • Yoo, Hoyoung (Department of Electronics Engineering, Chungnam National University)
  • Received : 2021.08.27
  • Accepted : 2021.10.04
  • Published : 2021.12.31

Abstract

This paper analyzes the tree expansion for multiple-input multiple-output (MIMO) detection in the viewpoint of hardware implementation. The tree expansion is to calculate path metrics of child nodes performed in every visit to a node while traversing the detection tree. Accordingly, the tree-expansion unit (TEU), which is responsible for such a task, has been an essential component in a MIMO detector. Despite the paramount importance, the analyses on the TEUs in the literature are not thorough enough. Accordingly, we further investigate the hardware complexity of the TEUs to suggest a guideline for selection. In this paper, we focus on a pair of major ways to implement the TEU: 1) a full parallel realization; 2) a transformation of the formulae followed by common subexpression elimination (CSE). For a logical comparison, the numbers of multipliers and adders are first enumerated. To evaluate them in a more practical manner, the TEUs are implemented in a 65-nm CMOS process, and their propagation delays, gate counts, and power consumptions were measured explicitly. Considering the target specification of a MIMO system and the implementation results comprehensively, one can choose which architecture to adopt in realizing a detector.

Keywords

Acknowledgement

The authors would like to thank the IC Design Education Center (IDEC) of South Korea for supporting electronic design automation (EDA) tools.

References

  1. F. Rusek, D. Persson, B. K. Lau, E. G. Larsson, T. L. Marzetta, O. Edfors, and F. Tufvesson, "Scaling up MIMO: Opportunities and challenges with very large arrays," IEEE Signal Process. Mag., vol. 30, no. 1, pp. 40-60, Jan. 2013. https://doi.org/10.1109/MSP.2011.2178495
  2. R. Wang and G. B. Giannakis, "Approaching MIMO channel capacity with reduced-complexity soft sphere decoding," in Proc. IEEE Wireless Commun. Netw. Conf. (WCNC), Atlanta, GA, USA, Mar. 2004, pp. 1620-1625.
  3. J. Jalden and B. Ottersten, "Approaching MIMO channel capacity with reduced-complexity soft sphere decoding," in Proc. IEEE Wireless Commun. Netw. Conf. (WCNC), Atlanta, GA, USA, Mar. 2004, pp. 1620-1625.
  4. A. Burg, M. Borgmann, M. Wenk, M. Zellweger, W. Fichtner, and H. Bolcskei, "VLSI implementation of MIMO detection using the sphere decoding algorithm," IEEE J. Solid-State Circuits, vol. 40, no. 7, pp. 1566-1577, Jul. 2005. https://doi.org/10.1109/JSSC.2005.847505
  5. P.-Y. Tsai, W.-T. Chen, X.-C. Lin, and M.-Y. Huang, "A 4 × 4 64-QAM reduced-complexity K-best MIMO detector up to 1.5 Gbps," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), Paris, France, May 2010, pp. 3953-3956.
  6. T.-H. Kim and I.-C. Park, "Small-area and low-energy K-best MIMO detector using relaxed tree expansion and early forwarding," IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 57, no. 10, pp. 2753-2761, Oct. 2010.
  7. M. Shabany and P. G. Gulak, "A 675 Mbps, 4 × 4 64-QAM Kbest MIMO detector in 0.13 um CMOS," IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 20, no. 1, pp. 135-147, Jan. 2012. https://doi.org/10.1109/TVLSI.2010.2090367
  8. T. H. Tran, H. Ochi, and Y. Nagao, "A 2D sorter-based K-best algorithm for high order modulation MIMO systems," in Proc. IEEE Veh. Technol. Conf. (VTC), Vancouver, BC, Canada, Sep. 2014, pp. 1-5.
  9. T. H. Tran, H. Ochi, and Y. Nagao, "A 4 × 4 multiplier-dividerless K-best MIMO decoder up to 2.7 Gbps," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), Melbourne, VIC, Australia, Jun. 2014, pp. 1696-1699.
  10. C.-F. Liao, J.-Y. Wang, and Y.-H. Huang, "A 3.1 Gb/s 8 × 8 sorting reduced K-best detector with lattice reduction and QR decomposition," IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 22, no. 12, pp. 2675-2688, Dec. 2014. https://doi.org/10.1109/TVLSI.2013.2297435
  11. M. Wenk, M. Zellweger, A. Burg, N. Felber, and W. Fichtner, "K-best MIMO detection VLSI architectures achieving up to 424 Mbps," in Proc. IEEE Int. Symp. Circuits Syst. (ISCAS), Island of Kos, Greece, May 2006, pp. 1151-1154.
  12. M.-T. Shiue, S.-S. Long, C.-K. Jao, and S.-K. Lin, "Design and implementation of power-efficient K-best MIMO detector for configurable antennas," IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 22, no. 11, pp. 2418-2422, Nov. 2014. https://doi.org/10.1109/TVLSI.2013.2288574
  13. Z. Guo and P. Nilsson, "Algorithm and implementation of the K-best sphere decoding for MIMO detection," IEEE J. Sel. Areas Commun., vol. 24, no. 3, pp. 491-503, Mar. 2006. https://doi.org/10.1109/JSAC.2005.862402
  14. B. Y. Kong and I.-C. Park, "Improved sorting architecture for K-best MIMO detection," IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 64, no. 9, pp. 1042-1046, Sep. 2017. https://doi.org/10.1109/TCSII.2016.2624304
  15. W. Xu, Y. Wang, Z. Zhou, and J. Wang, "A computationally efficient exact ML sphere deocder," in Proc. Proc. IEEE Global Commun. Conf. (GLOBECOM), Dallas, TX, USA, Nov.-Dec. 2004, pp. 2594-2598.
  16. B. Y. Kong and I.-C. Park, "Fast detection for spatial modulation MIMO based on cost estimation," Electron. Lett., vol. 52, no. 8, pp. 671-673, Apr. 2016. https://doi.org/10.1049/el.2016.0170
  17. T.-H. Kim and I.-C. Park, "High-throughput and area-efficient MIMO symbol detection based on modified Dijkstra's search," IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 57, no. 7, pp. 1756-1766, Jul. 2010. https://doi.org/10.1109/TCSI.2009.2034235
  18. B. Y. Kong and I.-C. Park, "Interference cancellation architecture for pipelined parallel MIMO detectors," in Proc. IEEE Int. Conf. Electron., Circuits, Syst. (ICECS), Bordeaux, France, Dec. 2018, pp. 77-80.
  19. B. Y. Kong and I.-C. Park, "Adaptive metric calculation for improving detection capability of MIMO detectors," in Proc. IEEE Veh. Technol. Conf. (VTC), Dresden, Germany, Jun. 2013, pp. 1-5.
  20. B. Y. Kong and I.-C. Park, "Hardware-efficient tree expansion for MIMO symbol detection," Electron. Lett., vol. 49, no. 3, pp. 226-228, Jan. 2013. https://doi.org/10.1049/el.2012.1074
  21. L. Azzam and E. Ayanoglu, "Reduced complexity sphere decoding for square QAM via new lattice representation," in Proc. IEEE Global Commun. Conf. (GLOBECOM), Washington, DC, USA, Nov. 2007, pp. 4242-4246.
  22. R. I. Hartley, "Subexpression sharing in filters using canonic signed digit multipliers," IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., vol. 43, no. 10, pp. 677-688, Oct. 1996. https://doi.org/10.1109/82.539000
  23. B. Y. Kong and I.-C. Park, "FIR filter synthesis based on interleaved processing of coefficient generation and multiplierblock synthesis," IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst., vol. 31, no. 8, pp. 1169-1179, Aug. 2012. https://doi.org/10.1109/TCAD.2012.2190826