DEC-aided SM-OFDM: A Spatial Modulation System with Deep Learning based Error Correction
Article No.: 8, Pages 1 - 6
Abstract
In this work, we propose a Deep Learning (DL) based error correction system termed as DEC. It predicts the transmitted symbols at the receiver using the received soft symbols and channel state information (CSI) of the transmission link. Hence, the proposed system eliminates the need of using complex channel coding/decoding blocks in the wireless communication system. Specifically, we explore the application of proposed DEC system for Spatial Modulation-OFDM (SM-OFDM) systems. SM is a technique that avoids inter-channel interference (ICI) at receiver input, also offers a good balance between the energy and spectral efficiency. This together with DEC system can prove to be of interest for the next generation wireless system, particularly for the Internet-of-Things (IoT) devices that require optimal bit-error ratios (BER) at moderate data rates. The performance of the proposed system is compared with Trellis coded-SM (TCSM) system. The obtained simulation results successfully verify the superiority of the DEC-aided SM-OFDM system over the TCSM in terms of both BER and throughput.
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Published In
October 2022
209 pages
ISBN:9781450398473
DOI:10.1145/3564121
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Association for Computing Machinery
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Published: 16 May 2023
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AIMLSystems 2022
AIMLSystems 2022: The Second International Conference on AI-ML Systems
October 12 - 15, 2022
Bangalore, India
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