최소거리탐지 알고리즘(MDSA)을 이용한 ML 탐지 MIMO 시스템 연구

Low Complexity MIMO System Using Minimum Distance Searching Algorithm (MDSA) with Linear Receiver

  • 발행 : 2007.04.30

초록

본 논문은 공간다중화 MIMO 시스템인 ML 수신기법의 연산량을 감소시키는 최소거리탐지 알고리즘 (MDSA: Minimum Distance Searching Algorithm)을 제안한다. 선형수신기의 출력값을 기준비트로 설정하여 탐색공간을 줄이고 기준비트와 수신심벌과의 최소거리를 이용하여 최종송신심벌로의 최적경로를 구함으로써 ML의 연산량을 효율적으로 감소시킨다. 제안한 기법의 연산 반복수는 송신안테나 4개, 성상차수 16일 때, ML 방식에 비해 0.21%로 감소되었다. 성능분석 시뮬레이션 결과는 16QAM에서 송신 안테나 2개, 수신안테나 3개 이상일 때 MDS 는 ML과 성능이 거의 동일하였고, QPSK에서 송신 안테나 4개, 수신안테나 6개 이상일 때 MDS의 성능은 ML에 비해 약간 열화됨을 확인 할 수 있었다.

This paper proposes Minimum Distance Searching Algorithm (MDSA) which reduces the computational complexity (CC) of the ML, the kind of Spatial Multiplexing (SM) MIMO system. The MDSA searchs candidate symbols with a starting symbol, which is called reference bits. We used the linear receiver of MIMO techniques to find a starting symbol. The MDSA searchs the shortest path to a transmitted symbol using reference bits and Minimum Distance(MD) concept. The CC of MDSA is reduced to the 0.21% to the ML as the transmit antennas is 4 in 16QAM. The simulation result shows the BER of MDSA is nearly same to the BER of ML as the transmit antennas is 2 and the receive antennas is 3 in 16QAM and slightly degraded to the BER of ML as the transmit antennas is 4 and the receive antennas is 6 in QPSK.

키워드

참고문헌

  1. H. Yang, 'A Road to Future Broadband Wireless Access: MIMO-OFDM-Based Air Interface,' IEEE Commun. Mag., Jan. 2005, pp53-60
  2. http://grouper.ieee.org/groups/802/11/
  3. S. Cui, Andrea J. Goldsmith, and A. Bahai, 'Energy-Efficiency of MIMO and Cooperative MIMO Techniques in Sensor Networks,' IEEE Journal On Selected Areas in Commun., Vol. 22, No.6, Aug. 2004, pp1089-1098 https://doi.org/10.1109/JSAC.2004.830916
  4. D. Morris and O. Kwon, 'Transporting JPEG Images over MIMO Links in Ad-Hoc Networks: an Investigation,' IEEE Sarnoff Sym., Mar. 2006
  5. G. Golden, C. Foschini, R. Valenzuela, and P. Wolniansky, 'Detection algorithm and initial laboratory results using V-BLAST space-time communication architecture,' IEE Electronics Letters, Vol. 35, No. 1, Jan. 1999, pp14-16 https://doi.org/10.1049/el:19990058
  6. E. Viterbo, and J. Boutros, 'A Universal Lattice Code Decoder for Fading Channels,' IEEE Trans. On Information Theory, Vol. 45, No. 5, July 1999, pp1639-1642 https://doi.org/10.1109/18.771234
  7. B. Hassibi, and H. Vikalo, 'On the Sphere-Decoding Algorithm I. Expected Complexity,' IEEE Trans. On Signal Processing, Vol. 53, No. 8, Aug. 2005, pp2806-2818 https://doi.org/10.1109/TSP.2005.850352
  8. T. Cui, and C. Tellambura, 'Approximate ML Detection for MIMO Systems Using Multistage Sphere Decoding,' IEEE Signal Processing Letters, Vol. 12, No. 3, Mar. 2005, pp222-225 https://doi.org/10.1109/LSP.2004.842263