Block Deep Neural Network-Based Signal Detector for Generalized Spatial Modulation
Type
SoftwareKAUST 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/10754/667586
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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
ae974a485f413a2113503eed53cd6c53
10.24433/co.3589818.v2