Joint Channel and Information Estimation on Symbol Decomposition-Based Secure Point-to-Point Communications - Technological Innovation for Life Improvement Access content directly
Conference Papers Year : 2020

Joint Channel and Information Estimation on Symbol Decomposition-Based Secure Point-to-Point Communications

Abstract

Energy efficiency and physical layer security are important features in future wireless communication networks. A secure point to point communication is established by using a symbol decomposition method where higher order modulation symbols are decomposed into bits or smaller symbols as separate components and then transmitted to the receiver through multiple amplifiers on the same channel. One of the main challenges in symbol decomposition is accurate channel knowledge for the case of non-static transmitter and receiver position, which necessitates employing a robust and accurate channel estimation with this technique. To improve the accuracy of the channel estimate, an iterative block decision feedback equalizer (IB-DFE) is used at the receiver for joint channel and information estimation. In this paper, we study the symbol decomposition method along with the channel estimation technique and analyze the performance of the system model by using bit error rate parameter and results showcase the effectiveness of IB-DFE receiver.
Fichier principal
Vignette du fichier
496588_1_En_13_Chapter.pdf (612.53 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03741555 , version 1 (01-08-2022)

Licence

Attribution

Identifiers

Cite

Akashkumar Rajaram, David Borges, Paulo Montezuma, Rui Dinis, Dushnatha Jayakody, et al.. Joint Channel and Information Estimation on Symbol Decomposition-Based Secure Point-to-Point Communications. 11th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Jul 2020, Costa de Caparica, Portugal. pp.137-146, ⟨10.1007/978-3-030-45124-0_13⟩. ⟨hal-03741555⟩
7 View
11 Download

Altmetric

Share

Gmail Facebook X LinkedIn More