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Turbo Coded Modulation as an Alternative to Space-Time Codes: The Case of Large Number of Transmit and Receive Antennas

机译:Turbo编码调制作为时空编码的替代选择:大量发送和接收天线的情况

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In a recent paper we have shown that a simple turbo coded modulation scheme provides significatn performance improvement with respect to the properly interleaved space-time trellis codes for block Rayleigh fading channels. The turbo coded modulation scheme for the multiple antenna system is based on a simple encoding procedure which uses the encoder for a binary turbo code and maps the encoded bits to a certain constellation, and a simple decoding procedure which is based on a log-likelihood computation of the transmitted bits and the use of these log-likelihoods in a sub-optimal iterative decoding algorithm. Although the computation of log-likelihoods is not a problem for small number of transmit antennas, the comptuational complexity at the receiver is too high for the case of large number of transmit antennas. In this paper we present a practical method for handling this problem. In particular, we present a new decoding algorithm which does not suffer from the same computational complexity. Our method is similar to the array processing/group interference suppresion scheme developed for space-time trellis coding. We present examples for the case of four transmit - four receive antennas and for the case of eight rate of 10~-5 over the multi-layered space-time trellis coding with symbole interleaving. We also observe that although the current approach is computationally efficient, it results in a considerable performance degradation compared to the original (more complex) approach.
机译:在最近的论文中,我们已经表明,相对于用于块瑞利衰落信道的适当交织的时空网格码,简单的turbo编码调制方案提供了显着的性能改善。用于多天线系统的turbo编码调制方案基于一个简单的编码过程,该过程将编码器用于二进制turbo码,并将编码后的比特映射到某个星座图;一个简单的解码过程,它基于对数似然计算传输比特的数量以及在次优迭代解码算法中这些对数似然的使用。尽管对数似然率的计算对于少量发射天线而言不是问题,但对于大量发射天线而言,接收机处的计算复杂度过高。在本文中,我们提出了一种解决此问题的实用方法。特别是,我们提出了一种新的解码算法,该算法不会遭受相同的计算复杂性。我们的方法类似于为时空网格编码开发的阵列处理/组干扰抑制方案。我们给出了具有符号交织的多层空时网格编码上的四个发射-四个接收天线的情况以及八个速率为10〜-5的情况的示例。我们还观察到,尽管当前的方法在计算上是有效的,但是与原始的(更复杂的)方法相比,它导致了相当大的性能下降。

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