Updated 23 Jul 2020
This repo is dedicated to BER Imitation Modeling of Satellite Communication System (SCS) using QPSK and OFDM Modulation in Rician Transionospheric Communication Channel with Multipath Propagation and Limited Coherence Bandwidth, that causes Frequency-Selective Fading and Intersymbol Interference of received signal.
The Imitation Model is constructed using objects and high-developed functions from MATLAB Communication and DSP Toolbox. For reducing signal impairments and for BER improvement SCS uses OFDM technique with Cyclic Prefix and Least Squares (LS) Channel Estimation, that determines Channel Frequency Response based on observing for Pilot Signals known a priori in the receiver.
The "SatCommSystem_LSModeling.mlx" is a Live Script and contains detailed code, explanations, analysis and references, and performs Imitation Modeling in Live Script Editor. The "BERTool_QPSK_RicianChannel.m" and "BERTool_QPSK_OFDM_RicianChannel_LSEstimation.m" are functions that can be used in BER Analyzer Tool.
For BER and efficiency research presented files perform Imitation Modeling for the next cases:
>> arbitrary parameters of Transionospheric Communication Channel and signal impairments:
- Rician Fading;
- Rayleigh Fading;
- Multipath Fading;
- Frequency-Selective Fading;
- Intersymbol Interference;
>> two types of SCS Transmitter-Receiver Scheme:
- only using QPSK;
- using QPSK and OFDM;
>> wide range of OFDM parameters:
- number and structure of Subcarriers in Time-Frequency Domain;
- number and location of Pilot Subcarriers;
>> arbitrary Ratio of Channel Coherence vs. Signal Bandwidth;
>> modulation type and order, initial symbol rate, etc.;
>> signal analysis and visualization.
Files in the repo will be useful for any communication engineer and MATLAB programmer, who is looking for examples of the BER Imitation Modeling of the Comm Systems.
Dmitriy Kostyuk (2021). SCS with QPSK-OFDM LSEstimation in Transionospheric Channel (https://github.com/fosfor15/SatCommSystem-QPSK-OFDM-LSEstimation-TransionosphericChannel/releases/tag/v1.0), GitHub. Retrieved .
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