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

  • 제41권1호
  • /
  • Pages.1-11
  • /
  • 2016
  • /
  • 1226-4717(pISSN)
  • /
  • 2287-3880(eISSN)
한국통신학회 (The Korean Institute of Commucations and Information Sciences)
권호 표지
DOI QR코드

DOI QR Code

OFDM 시스템에서 측정 벡터 결합을 이용한 채널 추정 방법

Sparse Channel Estimation Based on Combined Measurements in OFDM Systems

  • Min, Byeongcheon (Department of Information and Communication, Inha University) ;
  • Park, Daeyoung (Department of Information and Communication, Inha University)
  • 투고 : 2015.10.20
  • 심사 : 2016.01.05
  • 발행 : 2016.01.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 Orthogonal Frequency Division Multiplexing(OFDM) 시스템에서 압축센싱을 이용하는 채널추정기법을 연구한다. 압축센싱은 측정벡터의 크기가 성능에 영향을 주는데, OFDM에서는 channel delay spread가 큰 경우에 압축센싱 기법을 사용하는데 제약이 된다. 본 논문에서는 채널추정 오차를 줄이기 위해서 OFDM data block에 pilot information을 추가해 측정벡터의 길이를 증가시켜 성능을 향상시킨다. 제안하는 방식이 성긴 신호의 위치를 찾을 확률을 높이고 압축센싱의 신호 복원 성능을 높인다. 모의실험을 통해 제안하는 방식이 기존 방식보다 신호 복원 능력이 더 우수함을 확인한다.

We investigate compressive sensing techniques to estimate sparse channel in Orthogonal Frequency Division Multiplexing(OFDM) systems. In the case of large channel delay spread, compressive sensing may not be applicable because it is affected by length of measurement vectors. In this paper, we increase length of measurement vector adding pilot information to OFDM data block. The increased measurement vector improves probability of finding path delay set and Mean Squared Error(MSE) performance. Simulation results show that signal recovery performance of a proposed scheme is better than conventional schemes.

키워드

참고문헌

  1. Y. Gong and K. B. Letaief, "Low complexity channel estimation for space-time coded wideband OFDM systems," IEEE Trans. Wireless Commun., vol. 2, no. 5, pp. 876-882, Sept. 2003. https://doi.org/10.1109/TWC.2003.816797
  2. D. Lim, B. Kim, and K. Choi, "Interpolationbased precoding approximation algorithm for low complexity in multiuser MIMO-OFDM systems," J. KICS, vol. 35, no. 11, pp. 1027- 1037, Nov. 2010.
  3. S. Coleri, M. Ergen, A. Puri, and A. Bahai, "Channel estimation techniques based on pilot arrangement in OFDM systems," IEEE Trans. Broadcast., vol. 48, no. 3, pp. 223-229, Sept. 2002. https://doi.org/10.1109/TBC.2002.804034
  4. J. Kim, J. Jang, and H. Choi, "A lowcomplexity 2-D MMSE channel estimation for OFDM systems," J. KICS, vol. 36, no. 5, pp. 317-325, May 2011. https://doi.org/10.7840/KICS.2011.36C.5.317
  5. A. F. Molisch, "Ultra-wide-band propagation channels," in Proc. IEEE, vol. 97, no. 2, pp. 353-371, Feb. 2009. https://doi.org/10.1109/JPROC.2008.2008836
  6. N. Czink, X. Yin, H. Ozcelik, M. Herdin, E. Bonek, and B. Fleury, "Cluster characteristics in a MIMO indoor propagation environment," IEEE Trans. Wireless Commun., vol. 6, no. 4, pp. 1465-1475, Apr. 2007.
  7. W. U. Bajwa, J. Haupt, G. Raz, and R. Nowak, "Compressed channel sensing," in Proc. Annual Conf. Inf. Sci. Syst., pp. 5-10, Princeton, USA, Mar. 2008.
  8. D. L. Donoho, "Compressed sensing," IEEE Trans. Inf. Theory, vol. 52, no. 4, pp. 1289- 1306, Apr. 2006. https://doi.org/10.1109/TIT.2006.871582
  9. J. Kim, I. Kim, J. Park, H. Song, and S. Han, "Channel state information feedback scheme based on non-convex compressed sensing for massive MIMO systems," J. KICS, vol. 40, no. 04, pp. 628-636, Apr. 2015. https://doi.org/10.7840/kics.2015.40.4.628
  10. J. A. Tropp and A. C. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit," IEEE. Trans. Inf. Theory, vol. 53, no. 12, pp. 4655-4666, Dec. 2007. https://doi.org/10.1109/TIT.2007.909108
  11. D. Needell and J. A. Tropp, "CoSaMP: iterative signal recovery from incomplete and inaccurate samples," Commun. ACM, vol. 53, no. 12, pp. 93-100, Dec. 2010. https://doi.org/10.1145/1859204.1859229
  12. L. Dai, Z. Wang, and Z. Yang, "Timefrequency training OFDM with high spectral efficiency and reliable performance in high speed environments," IEEE J. Sel. Areas Commun., vol. 30, no. 4, pp. 695-707, May 2012. https://doi.org/10.1109/JSAC.2012.120504
  13. J. Fu, J. Wang, J. Song, C. Pan, and Z. Yang, "A simplified equalization method for dual PN-sequence padding TDS-OFDM systems," IEEE Trans. Broadcast., vol. 54, no. 4, pp. 825-830, Dec. 2008. https://doi.org/10.1109/TBC.2008.2001725
  14. L. Dai, Z. Wang, and Z. Yang, "Compressive sensing based time domain synchronous OFDM transmission for vehicular communications," IEEE. J. Sel. Areas Commun., vol. 31, no. 9, pp. 460-469 Sept. 2013. https://doi.org/10.1109/JSAC.2013.SUP.0513041
  15. B. Yang, K. Letaief, R. Cheng, and Z. Cao, "Channel estimation for OFDM transmission in multipath fading channels based on parametric channel modeling," IEEE Trans. Commun., vol. 49, no. 3, pp. 467-479, Mar. 2001. https://doi.org/10.1109/26.911454
  16. A. Iyer, C. Rosenberg, and A. Karnik, "What is the right model for wireless channel interference?," IEEE Trans. Wireless Commun., vol. 8, no. 5, pp. 2662-2671, May 2009. https://doi.org/10.1109/TWC.2009.080720
  17. E. Candès and M. Wakin, "An introduction to compressive sampling," IEEE Signal Process. Mag., vol. 25, no. 2, pp. 21-30, Feb. 2008. https://doi.org/10.1109/MSP.2007.914731
  18. R. Baraniuk, "Compressive sensing," IEEE Signal Processing Mag., vol. 24, no. 4, pp. 118-124, Jul. 2007. https://doi.org/10.1109/MSP.2007.4286571
  19. W. Ding, F. Yang, C. Y. Pan, L. Dai, and J. Song, "Compressive sensing based channel estimation for OFDM systems under long delay channels," IEEE Trans. Broadcast., vol. 60, no. 2, pp. 313-321, Jun. 2014. https://doi.org/10.1109/TBC.2014.2315913

피인용 문헌

  1. 사전 정보를 이용한 다중경로 정합 추구 vol.41, pp.6, 2016, https://doi.org/10.7840/kics.2016.41.6.628