{'fraction_non_alphanumeric': 0.03534031413612566, 'fraction_numerical': 0.017015706806282723, 'mean_word_length': 4.58029197080292, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Improved 2-D Graph-Based Detectors for 2-D Interference Channels

The 2-D interference channels, which consist of intersymbol interference as well as intertrack interference (ITI), appear in high-density recording channels. A graph-based detector has received much attention since it is a real 2-D detector, which can recover data from multiple tracks or each 2-D page simultaneously. In this paper, we propose two approaches to improve the performances of graph-based detectors. For the first method (M1), which processes data on a 2-D page, the system equalizes 2-D interference channel into two 1-D targets, horizontal and vertical directions followed by two corresponding graph detectors. The second method (M2) is similar to the first one, but the 2-D channel is equalized into two 2-D targets with and without cornered ITIs, respectively, in order to better handle the effects of cornered ITIs. Compared with the full-graph detector, the method M1 offers reduced-complexity due the fewer number of edges from the factor nodes. The simulation results on the 3 × 3 channel matrix with 2% cornered ITI show that the proposed methods achieve the gains of about 1.0 and 1.7 dB, respectively, at the BER of 10-5 over the full graph detector. As the cornered ITI levels increase, the method M2 gives the larger gains over the others. When the media noise is accounted for, the method M2 still gives the best performances. Finally, the mutual information of the three graph detectors for the 2-D channels is computed and compared.