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Reliable Wireless Networking via Soft-Source Information Combining

delete2023-03-15
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OA
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L
Lihao Zhang
S
Soung Chang Liew *
DOI:10.1109/JIOT.2022.3219980delete
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摘要

摘要

En 中文
This article puts forth a multistream networking paradigm, referred to as soft-source-information-combining (SSIC), to support wireless Internet of Things (IoT) applications with ultrareliability requirements. For SSIC networking, an SSIC dispatcher at the source dispatches duplicates of packets over multiple streams, which may be established over different physical wireless networks. If a packet on a stream cannot be decoded due to wireless interference or noise, the decoder makes available the packet's soft information. An aggregator then combines the soft information of the duplicates to boost reliability. Of importance are two challenges: 1) how to descramble the scrambled soft information from different streams to enable correct SSIC and 2) the construct of an SSIC dispatching and aggregation framework compatible with commercial network interface cards (NICs) and TCP/IP networks. To address the challenges, we put forth: 1) a soft descrambling (SD) method to minimize the bit-error rate (BER) and packet-error rate (PER) at the SSIC's output and 2) an SSIC networking architecture readily deployable over today's TCP/IP networks without specialized NICs. For concept proving and experimentation, we realized an SSIC system over two Wi-Fi's physical paths in such a way that all legacy TCP/IP applications can enjoy the reliability brought forth by SSIC without modification. Experiments over our testbed corroborate the effectiveness of SSIC in lowering the packet delivery failure rate and the possibility of SSIC in providing 99.99% reliable packet delivery for short-range communication.
Keyword:
Multistream transmission
soft information com-bining
ultrareliable communications
Wi-Fi 7
wireless networks

期刊

IEEE Internet of Things Journal 封面图
IEEE Internet of Things Journal
IF:
8.9
论文数:
1.4W
被引数:
7.8W

机构

C
Chinese University of Hong Kong
学者数:
3.4W
论文数: 3.2W
被引数: 5.6W
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