Abstract
In this article, a novel multiple-input multiple-out (MIMO) transmission scheme, called generalized polarized enhanced spatial modulation (GPESM), is proposed for dual-polarized land mobile satellite (LMS) communications. We first introduce the enhanced spatial modulation (ESM) technique for dual-polarized LMS communications, in which polarization dimension, spatial dimension and multiple signal constellations are used to transmit information and obtain substantial performance gain. Meanwhile, the theoretical upper bound for the average bit error probability (ABEP) of the proposed GPESM scheme is derived. In order to further improve the reliability of the system, we also propose two novel power allocation (PA) algorithms for GPESM system, which are the optimization-driven approximated max-min distance (AMMD)-based PA algorithm and the data-driven deep neural network (DNN)-based PA algorithm. To achieve an enhanced spatial diversity gain, we consider to apply a reconfigurable intelligent surface (RIS) to the GPESM system as a relay to assist in transmitting information. In this way, the user can receive the information transmitted by the satellite on one hand, and the information sent by the satellite via the RIS relay on the other hand. We also extend the above-mentioned two PA algorithms to the RIS-assisted GPESM systems. Our simulation results show that the RIS-assisted GPESM systems are capable of obtaining high bit error rate (BER) performance gain (up to 10 dB) compared to the standard GPESM system and two PA algorithms can further improve the performance to the systems.
Original language | English |
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Article number | 9403416 |
Pages (from-to) | 383-397 |
Number of pages | 15 |
Journal | IEEE Transactions on Cognitive Communications and Networking |
Volume | 7 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2021 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2015 IEEE.
ASJC Scopus Subject Areas
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence
Keywords
- Deep neural network
- land mobile satellite
- polarized modulation
- power allocation
- reconfigurable intelligent surfaces