Joint Parallel Tabu Search Algorithm-Based Look-Up Table Design and Deep Learning-Based Signal Detection for OFDM-AIM

This letter first proposes a parallel Tabu Search (PTS) algorithm-based look-up table for orthogonal frequency division multiplexing with all index modulation (OFDM-AIM) called PTS-AIM. In the conventional OFDM-AIM (referred to as AIM in this letter), each subcarrier within a subblock is mapped to t...

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Veröffentlicht in:	IEEE wireless communications letters 2024-02, Vol.13 (2), p.575-579
1. Verfasser:	Yildirim, Mahmut
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Bit error rate Deep learning deep learning (DL) deep neural network (DNN) Detectors Indexes long short-term memory (LSTM) Lookup tables Machine learning Orthogonal Frequency Division Multiplexing Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM) parallel tabu search algorithm Quadrature amplitude modulation recurrent neural network (RNN) Search algorithms Signal detection Signal detectors Subcarriers Table lookup Tabu search
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