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A Low-Complexity Decoding Algorithm for Coded Hierarchical Modulation in Single Frequency Networks

机译:一种单频网络中编码分层调制的低复杂度解码算法

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摘要

In this paper, the hierarchical modulation (HM) technique is adopted in a single frequency network (SFN) to provide both global and local information. In order to mitigate the interlayer interference and intercell interference, we develop a low-complexity successive interference cancellation (SIC) algorithm for the coded HM signals in the SFN. The proposed decoding algorithm can be applied to different soft-decision channel coding schemes (e.g., Turbo codes, LDPC codes) under various channel profiles. We analyzed the decoding complexity of the proposed algorithm, and evaluated the bit error rate performance. The simulations show that the new decoding algorithm can offer up to 0.7 dB carrier to noise ratio ((C/N)) gain compared with the traditional SIC approach under different channel models, while providing the comparable performance (up to 95% decoding complexity savings) with the multilayer iterative decoding approach. The performance evaluation and decoding complexity comparisons indicate that the proposed structured SIC approach offers a good performance-complexity trade-off, especially for the HM-based SFN scenarios.
机译:在本文中,在单频网络(SFN)中采用了分层调制(HM)技术来提供全局和本地信息。为了减轻层间干扰和小区间干扰,我们针对SFN中的编码HM信号开发了一种低复杂度的连续干扰消除(SIC)算法。可以将所提出的解码算法应用于在各种信道简档下的不同软判决信道编码方案(例如,Turbo码,LDPC码)。我们分析了该算法的解码复杂度,并评估了误码率性能。仿真表明,在不同的信道模型下,与传统的SIC方法相比,新的解码算法可提供高达0.7 dB的载噪比((C / N))增益,同时提供可比的性能(节省多达95%的解码复杂度) )与多层迭代解码方法。性能评估和解码复杂度比较表明,所提出的结构化SIC方法提供了良好的性能复杂度折衷,尤其是对于基于HM的SFN方案而言。

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