Cross-layer hybrid automatic repeat request error control with turbo processing for wireless system
The increasing demand for wireless communication system requires an efficient design in wireless communication system. One of the main challenges is to design error control mechanism in noisy wireless channel. Forward Error Correction (FEC) and Automatic Repeat reQuest (ARQ) are two main error contr...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/77664/1/HazilahMadKaidiPFKE2015.pdf |
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| Summary: | The increasing demand for wireless communication system requires an efficient design in wireless communication system. One of the main challenges is to design error control mechanism in noisy wireless channel. Forward Error Correction (FEC) and Automatic Repeat reQuest (ARQ) are two main error control mechanisms. Hybrid ARQ allows the use of either FEC or ARQ when required. The issues with existing Hybrid ARQ are reliability, complexity and inefficient design. Therefore, the design of Hybrid ARQ needs to be further improved in order to achieve performance close to the Shannon capacity. The objective of this research is to develop a Cross-Layer Design Hybrid ARQ defined as CLD_ARQ to further minimize error in wireless communication system. CLD_ARQ comprises of three main stages. First, a low complexity FEC defined as IRC_FEC for error detection and correction has been developed by using Irregular Repetition Code (IRC) with Turbo processing. The second stage is the enhancement of IRC_FEC defined as EM_IRC_FEC to improve the reliability of error detection by adopting extended mapping. The last stage is the development of efficient CLD_ARQ to include retransmission for error correction that exploits EM_IRC_FEC and ARQ. In the proposed design, serial iterative decoding and parallel iterative decoding are deployed in the error detection and correction. The performance of the CLD_ARQ is evaluated in the Additive White Gaussian Noise (AWGN) channel using EXtrinsic Information Transfer (EXIT) chart, bit error rate (BER) and throughput analysis. The results show significant Signal-to-Noise Ratio (SNR) gain from the theoretical limit at BER of 10-5. IRC_FEC outperforms Recursive Systematic Convolutional Code (RSCC) by SNR gain up to 7% due to the use of IRC as a simple channel coding code. The usage of CLD_ARQ enhances the SNR gain by 53% compared to without ARQ due to feedback for retransmission. The adoption of extended mapping in the CLD_ARQ improves the SNR gain up to 50% due to error detection enhancement. In general, the proposed CLD_ARQ can achieve low BER and close to the Shannon‘s capacity even in worse channel condition. |
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