The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Efficient Power Allocation Algorithms for Adaptive Spatial Multiplexing MIMO Systems

적응 공간 다중화 MIMO 시스템을 위한 효율적인 전력 할당 알고리즘

  • 신준호 (한국항공대학교 대학원 정보통신공학과 이동통신연구실) ;
  • 김동건 (한국항공대학교 대학원 정보통신공학과 이동통신연구실) ;
  • 박형래 (한국항공대학교 대학원 정보통신공학과 이동통신연구실)
  • Received : 2010.10.11
  • Accepted : 2011.04.01
  • Published : 2011.04.30
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Abstract

While the water-filling algorithm is an efficient power allocation method that maximizes the ergodic capacity of adaptive MIMO systems, its excessive residual power causes spectrum loss in real systems employing discrete modulation indices. In this paper we propose new power allocation algorithms that improve the spectral efficiency of MIMO systems by efficiently reallocating the residual power of the water-filling algorithm. We apply the proposed algorithms to the adaptive turbo-coded MIMO system to verify their performance through computer simulation in various environments. Simulation results show that the spectral efficiency of the proposed algorithms is better than that of the water-filling algorithm by about 8.9% at SNR of 20dB in Rayleigh fading environments.

Water-filling 알고리즘은 적응 MIMO 시스템의 ergodic 용량을 최대화하는 효율적인 전력 할당 방식이지만 이산 변조 지쉬discrete modulation index)를 사용하는 실제의 시스템의 경우 과도한 잉여 전력(residual power)으로 인해 스펙트럼 효율이 감소하는 단점이 있다. 본 논문에서는 water-filling 알고리즘의 잉여 전력을 효율적으로 재할당 함으로써 적응 MIMO 시스템의 스펙트럼 효율을 향상시키는 새로운 전력 할당 알고리즘을 제안한다. 알고리즘의 성능을 검증하기 위해 터보 코드가 적용된 적응 MIMO 시스템을 구성하고 다양한 환경에서 시뮬레이션을 수행한다 시뮬레이션 결과, 레일리이 페이딩 환경에서 SNR이 20dB일 때 제안된 알고리즘의 스펙트럼 효율이 기존의 water-filling 알고리즘에 비해 대략 8.9% 향상됨을 알 수 있었다.

Keywords

References

  1. G. D. Golden, C. J. Foschini, R. A. Vanezuela, and P. W. Wolniansky, "Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture", Electron.Lett., Vol.35, No.1, pp.14-16, 1999. https://doi.org/10.1049/el:19990058
  2. A. Scaglione, P. Stoica, S. Barbarossa, G. B. Giannakis, and H. Sampath, "Optimal designs for space time linear precoders and decoders", IEEE Trans. Signal Precess., Vol.50, No.5, pp.1051-1064, 2002. https://doi.org/10.1109/78.995062
  3. D. J. Love and J. R. W. Heath, "Multimode precoding for MIMO wireless systems", IEEE Trans. Signal Process., Vol.53, No.10, pp.3674-3687, 2005. https://doi.org/10.1109/TSP.2005.855107
  4. X. Li, S. Jin, X. Gao, and K.K. Wong, "Near-optimal power allocation for MIMO channels with mean or covariance feedback", IEEE Trans. Commun., Vol.58, No.1, pp.289-300, 2010. https://doi.org/10.1109/TCOMM.2010.01.070377
  5. A. Scaglione, S. Barbarossa, and G. B. Giannakis, "Filterbank transceivers optimizing information rate in block transmissions over dispersive channels", IEEE Trans. Inf. Theory, Vol.45, No.3, pp.1019-1032, 1999. https://doi.org/10.1109/18.761338
  6. D. P. Palomar and J. R. Fonollosa,"Practical algorithms for a family of water-filling solutions", IEEE Trans. Signal Process., Vol.53, No.2, pp.686-695, 2005. https://doi.org/10.1109/TSP.2004.840816
  7. D. P. Palomar and S. Barbarossa, "Designing MIMO communication system: constellation choice and linear transceiver design", IEEE Trans. Signal Process., Vol.53, No.10, pt.1, pp.3804-3818, 2007.
  8. D. P. Palomar, M. Bengtsson, and B. Ottersten, "Minimum BER linear transceivers for MIMO channels via primal decomposition", IEEE Trans. Signal Process., Vol.53, No.8, pp.2866-2882, 2005. https://doi.org/10.1109/TSP.2005.850373
  9. R. W. Heath, A. Pauraj, and S. Sandhu, "Antenna selection for spatial multiplexing systems with linear receivers", IEEE Commun. Lett., Vol.5, pp.142-144, 2001. https://doi.org/10.1109/4234.917094
  10. R. Gowrishankar, M. F. Demirkol, and Z. Yun, "Adaptive modulation for MIMO systems and throughput evaluation with realistic channel model", Proc. Internat. Conf. Wireless Networks, Commun. and Mobile Computing, pp.851-856, 2005.
  11. Z. Zhou, B. Vucetic, M. Dohler and Y. Li, "MIMO systems with adaptive modulation", IEEE Trans. Vehicular Tech., Vol.54, No.5, pp.1828-1842, 2005. https://doi.org/10.1109/TVT.2005.853886
  12. X. Che, C. He, and D. Wang, "A simplified adaptive modulation scheme for MIMO spatial multiplexing systems", IEEE Conf. Comm., pp.503-507, 2007.
  13. Z. Zhou, and B. Vucetic, "Multiplexing gain of variable-rate MIMO system", IEEE Comm. Letter, Vol.11, No.4, pp.289-291, 2007. https://doi.org/10.1109/LCOM.2007.348277
  14. S. Vishwanath and A. Goldsmith, "Adaptive turbo-coded modulation for flat-fading channels", IEEE Trans. Comm., Vol.51, No.6, pp.964-972, 2003. https://doi.org/10.1109/TCOMM.2003.813180
  15. A. Goldsmith and S.G. Chua, "Adaptive coded modulation for fading channels", IEEE Trans. Comm., Vol.46, No.5, pp.595-602, 1998. https://doi.org/10.1109/26.668727
  16. S. Benedetto, D. Divsalar, G. Montorsi, and F. Pollara, "Serial concatenation of interleaved codes: performance analysis, design, and iterative decoding", IEEE Trans. Information Theory, Vol.44, No.3, pp.909-926, 1998. https://doi.org/10.1109/18.669119
  17. S. A. Barbulescu and S. S. Pietrobon, "Interleaver design for turbo codes", Electronic Letters, Vol.30, pp.2107-2108, 1994. https://doi.org/10.1049/el:19941434
  18. F. Daneshgaran and M. Mondin, "Design of interleavers for turbo codes based on a cost function", Int. Symp. On Turbo Codes, pp.255- 258, 1997.
  19. R. Zhang, A. Yang, G. Xie, Y. Liu and B. Tang, "Optimal robust bit and power allocation for MIMO systems", ISCIT'07 International Symposium, pp.392-396, 2007.
  20. G. Lai, J. Yin, F. Lin and H. Yu, "Performance of adaptive bit and power allocation MIMO-OFDM system based on Greedy Algorithm", IEEE Conf. Wireless Comm., Vol.1, pp.44-49, 2005.
  21. X. Jin, H. Jiang, J. Hu, Y. Yuan, C. Zhao and J. Shi, "Maximum data rate power allocation for MIMO spatial multiplexing systems with imperfect CSI", IEEE Conf. Vech. Tech., pp.1-5, 2009