A Low-Complexity Decoding Algorithm for Hierarchically Modulated Signals in SFN

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 inter-layer interference (ILI) and inter-cell interference (ICI), 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 (BER) 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 multi-layer 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.