Parallel Concatenated Convolutional Lattice Codes With Constrained States
Parallel Concatenated Convolutional Lattice Codes With Constrained States
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DOI：
10.1109/tcomm.2015.2408317
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发表时间：
2015-04-01
影响因子：
8.3
通讯作者：
Ochiai, Hideki
中科院分区：
文献类型：
--
作者：
Mitran, Patrick;Ochiai, Hideki
卷积格码，也称为信号码，已经被提出作为一种技术来生成具有良好性能的结构化码。虽然原则上可以使用维特比算法实现最佳解码，但实际上由于Tomlinson-Harashima预编码，状态空间的大小太大，并且必须求助于次优技术，例如顺序解码。在本文中，我们采取了另一种方法。通过采用一个明智的选择抽头系数和预编码相结合，我们表明，状态空间可以被约束到一个相对较小的集合，使维特比解码是实用的。这样的代码的性能仍然表现出很大的差距，以容量，我们进一步提出了一个并行级联类似的涡轮码，从而在一个“涡轮信号码。由于相对较小的状态空间，基于BCJR算法的迭代解码现在是可能的。通过仿真发现，在块长度为8192的情况下，对于1%的误帧率的SNR与对于相同速率的码在AWGN信道上理论上可实现的最佳性能之间的差距在0.75-0.85 dB内。
Convolutional lattice codes, also known as signal codes, have been proposed as a technique to generate structured codes that have good performance. While in principle optimal decoding can be achieved using the Viterbi Algorithm, in practice due to Tomlinson-Harashima precoding, the size of the state space is too large, and one must resort to suboptimal techniques such as sequential decoding. In this paper, we take an alternate approach. By employing a judicious selection of tap coefficients and in combination with precoding, we show that the state space can be constrained to a relatively small set such that Viterbi decoding is practical. The performance of such codes still exhibits a large gap to capacity, and we further propose a parallel concatenation similar to that of turbo codes, resulting in a "turbo signal code." Due to the relatively small state space, iterative decoding based on the BCJR algorithm is now possible. The gaps between the SNR for a frame error rate of 1% and the optimal performance theoretically achievable for a code of the same rate over an AWGN channel are found by simulation to be within 0.75-0.85 dB with a block length of 8192.