期刊
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 13, 期 9, 页码 5173-5182出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2014.2325028
关键词
Adaptive generative models; error models; burst error statistics; Markov models; hidden Markov models
资金
- EPSRC
- Philips Research Cambridge, U.K.
- Opening Project of the Key Laboratory of Cognitive Radio and Information Processing, Guilin University of Electronic Technology, Ministry of Education [2013KF01]
- State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University [RCS2012K003]
- National 863 project in 5G, Ministry of Science and Technology, China [2014AA01A706]
- National Natural Science Foundation of China [61222105]
- Beijing Municipal Natural Science Foundation [4112048]
- Sensor Networks and Cellular Systems Research Center, University of Tabuk
- Ministry of Higher Education in Saudi Arabia
Generative models, which can generate bursty error sequences with similar burst error statistics to those of descriptive models, have an immense impact on the wireless communications industry as they can significantly reduce the computational time of simulating wireless communication links. Adaptive generative models aim to produce any error sequences with any given signal-to-noise ratios (SNRs) by using only two reference error sequences obtained from a reference transmission system with two different SNRs. Compared with traditional generative models, this adaptive technique can further considerably reduce the computational load of generating new error sequences as there is no need to simulate the whole reference transmission system again. In this paper, reference error sequences are provided by computer simulations of a long term evolution (LTE) system. Adaptive generative models are developed from three widely used generative models, namely, the simplified Fritchman model (SFM), the Baum-Welch based hidden Markov model (BWHMM), and the deterministic process based generative model (DPBGM). It is demonstrated that the adaptive DPBGM can provide accurate burst error statistics and bit error rate (BER) performance of the LTE system, while the adaptive SFM and adaptive BWHMM fail to do so.
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