Block Deep Neural Network-Based Signal Detector for Generalized Spatial Modulation
Type
Software
KAUST Department
Communication Theory LabComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Electrical and Computer Engineering Program
Physical Science and Engineering (PSE) Division
Date
2020Permanent link to this record
http://hdl.handle.net/10754/667586Metadata
Show full item recordAbstract
This is a simulation program of Generalized Spatial Modulation (GSM) detector using DNN as the base of the signal detector. Comparing with the conventional methods, the proposed method has better performance of BER. Also, since this method based on DNN that can easily parallelize due to the availability of computation equipment, so the time complexity of the proposed method is also reliable.Citation
Albinsaid, H., Keshav Singh, Sudip Biswas, Chih-Peng Li, & Mohamed-Slim Alouini. (2020). Block Deep Neural Network-Based Signal Detector for Generalized Spatial Modulation (Version 2.0) [Computer software]. Code Ocean. https://doi.org/10.24433/CO.3589818.V2Publisher
Code OceanAdditional Links
https://codeocean.com/capsule/3375420/tree/v2Relations
Is Supplement To:- [Article]
Albinsaid, H., Singh, K., Biswas, S., Li, C.-P., & Alouini, M.-S. (2020). Block Deep Neural Network-Based Signal Detector for Generalized Spatial Modulation. IEEE Communications Letters, 1–1. doi:10.1109/lcomm.2020.3015810. DOI: 10.1109/lcomm.2020.3015810 Handle: 10754/664608