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Underwater Acoustic Multi-user OFDM Bit Loading with Markov Chain based Channel State Information Prediction
- Source :
- OCEANS 2018 MTS/IEEE Charleston.
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- In underwater acoustic (UWA) adaptive OFDM system, the transmission parameters are adjusted on the basis of channel state information (CSI). Whereas in the temporal varying UWA channels, large propagation delay leads to that the actual CSI in transmission may different from the feedback CSI. In this paper, a multi-user OFDM bit loading scheme have been proposed with Markov chain based CSI prediction so as to achieve better match of channel states for efficient resources allocation. Markov chain based channel state space for each user is constructed by initial and statistical CSI, which can make full use of the sensed delayed CSI and channel statistics to predict the CSI at the moment of data transmission. And then, with the predicted CSI, optimal bit loading for multiple users can be determined for system performance improvement. The simulation results have shown that, with the proposed method, both the single and multiple users adaptive OFDM system can achieve better throughput in comparison to employing the delayed available feedback.
- Subjects :
- Markov chain
Physics::Instrumentation and Detectors
010505 oceanography
Computer science
Orthogonal frequency-division multiplexing
ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS
Markov process
020206 networking & telecommunications
Throughput
Data_CODINGANDINFORMATIONTHEORY
02 engineering and technology
01 natural sciences
symbols.namesake
Transmission (telecommunications)
Channel state information
0202 electrical engineering, electronic engineering, information engineering
symbols
Electronic engineering
Computer Science::Information Theory
0105 earth and related environmental sciences
Data transmission
Communication channel
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- OCEANS 2018 MTS/IEEE Charleston
- Accession number :
- edsair.doi...........263e72e47545e11e401e898065e10183