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arXiv 0911.0183cs.ITmath.ACmath.IT
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快速变化移动信道下基于Gibbs采样的OFDM MAP检测算法

A Gibbs Sampling Based MAP Detection Algorithm for OFDM Over Rapidly Varying Mobile Radio Channels

Erdal Panayirci, Hakan Dogan, H. Vincent Poor

摘要:

在快速时变信道上运行的正交频分复用(OFDM)系统中,子载波之间的正交性被破坏,导致载波间干扰(ICI)并导致不可减少的错误平层。针对OFDM系统在快时变多径信道中的应用,提出了一种新的低复杂度的最大{ \em后验}概率(MAP)检测算法。检测算法利用频域信道矩阵的带状结构,频域信道矩阵的带宽是根据移动终端的速度调整的参数。基于该假设,接收信号矢量被分解为降维的子观测,使得观测矢量的对要检测的符号有贡献的所有分量都被包括在分解的观测模型中。然后,通过MAP算法借助于马尔可夫链蒙特卡罗(MCMC)技术以最佳和计算有效的方式检测数据符号。计算复杂性的研究以及仿真结果表明,该算法具有显着的性能和复杂性优于现有的次优检测和均衡算法在文献中提出的早期。

英文摘要:

In orthogonal frequency-division multiplexing (OFDM) systems operating over rapidly time-varying channels, the orthogonality between subcarriers is destroyed leading to inter-carrier interference (ICI) and resulting in an irreducible error floor. In this paper, a new and low-complexity maximum {\em a posteriori} probability (MAP) detection algorithm is proposed for OFDM systems operating over rapidly time-varying multipath channels. The detection algorithm exploits the banded structure of the frequency-domain channel matrix whose bandwidth is a parameter to be adjusted according to the speed of the mobile terminal. Based on this assumption, the received signal vector is decomposed into reduced dimensional sub-observations in such a way that all components of the observation vector contributing to the symbol to be detected are included in the decomposed observation model. The data symbols are then detected by the MAP algorithm by means of a Markov chain Monte Carlo (MCMC) technique in an optimal and computationally efficient way. Computational complexity investigation as well as simulation results indicate that this algorithm has significant performance and complexity advantages over existing suboptimal detection and equalization algorithms proposed earlier in the literature.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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