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Jingze Zheng

dblp:397/3343 · DBLP profile ↗
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4ranked-venue papers
3as first author
4since 2021 · last 2026
0009-0007-8756-3867ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 4 · 3 first-author · 4 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Physical-layer communications · 56% Cellular and mobile networks · 28% Internet of things and sensor networks · 17%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cellular and mobile networks › machine-type communication
NB-IoT
1.822026
SoftNB: Design and Implementation of an NB-IoT PHY Software-Defined Radio · IEEE Trans. Netw. 2026
SoftNB: A Fully Functional NB-IoT PHY for Various SDR Platforms · ICNP 2024
Physical-layer communications
software-defined radio
1.822026
SoftNB: Design and Implementation of an NB-IoT PHY Software-Defined Radio · IEEE Trans. Netw. 2026
SoftNB: A Fully Functional NB-IoT PHY for Various SDR Platforms · ICNP 2024
Internet of things and sensor networks
LPWAN
1.122026
SoftNB: A Fully Functional NB-IoT PHY for Various SDR Platforms · ICNP 2024
SoftNB: Design and Implementation of an NB-IoT PHY Software-Defined Radio · IEEE Trans. Netw. 2026
Physical-layer communications
physical layer
1.012026
SoftNB: Design and Implementation of an NB-IoT PHY Software-Defined Radio · IEEE Trans. Netw. 2026
Physical-layer communications
physical layer implementation
0.812024
SoftNB: A Fully Functional NB-IoT PHY for Various SDR Platforms · ICNP 2024

Methods — techniques the papers use, named apart from their topics

time/frequency/phase offset mitigation · 1.0software-defined radio · 1.0signal processing pipeline · 0.8offset mitigation · 0.8
YearPublicationVenuePosition
2026 SoftNB: Design and Implementation of an NB-IoT PHY Software-Defined Radio
abstract
In recent years, there has been a growing focus on developing Low Power Wide Area Network (LPWAN) protocols, especially within the LoRa research community. However, the research community for NB-IoT, another crucial LPWAN technology, has not experienced comparable expansion due to the absence of a functional and adaptable software-defined radio (SDR) implementation. To address this gap, we present SoftNB, the first fully functional physical layer SDR implementation for NB-IoT. SoftNB conforms to the latest 3GPP standards and features an efficient and effective signal processing pipeline to mitigate time, frequency, and phase offsets during transmission and reception. Additionally, SoftNB is compatible with various SDR platforms, including USRP, HackRF One, and RTL-SDR Dongle. Extensive evaluations of SoftNB demonstrate its superior performance. Compared to the state-of-the-art baseline, SoftNB achieves an 8× reduction in Block Error Rate (BLER) when the number of repetitions is set to 4 at a distance of 450 meters.
Jingze Zheng, Chaojie Gu, Yuanchao Shu, Xiuzhen Guo, Shibo He, Jiming Chen 0001, Guohui Shen
IEEE Trans. Netw.1
2026 Efficient Sim2Real Deep Learning for Device-Specific OFDM Frequency Offset Calibration
Chaojie Gu, Jingze Zheng, Yichuan Yang, Shibo He, Zhiguo Shi 0001
IEEE Trans. Wirel. Commun.2
2025 Sim2Real Deep Transfer for Per-Device CFO Calibration
Jingze Zheng, Zhiguo Shi 0001, Shibo He, Chaojie Gu
GLOBECOM1
2024 SoftNB: A Fully Functional NB-IoT PHY for Various SDR Platforms
abstract
The design of Low Power Wide Area Network (LPWAN) protocols has attracted increasing attention in recent years, particularly within the LoRa research community. However, NB-IoT, another critical LPWAN technology, has not seen similar growth in its research community due to the lack of a functional and flexible software-defined radio (SDR) implementation. To address this gap, we present SoftNB, the first fully functional physical layer SDR implementation for NB-IoT. SoftNB conforms to the latest 3GPP standards and features an efficient and effective signal processing pipeline to mitigate time, frequency, and phase offsets during transmission and reception. Additionally, SoftNB is compatible with various SDR platforms, including USRP, HackRF One, and RTL-SDR Dongle. Extensive evaluations of SoftNB demonstrate its superior performance. Compared to the state-of-the-art baseline, SoftNB achieves an$8\times$reduction in Block Error Rate (BLER) when the number of repetitions is set to 4 at a distance of 450 meters.
Jingze Zheng, Chaojie Gu, Yuanchao Shu, Xiuzhen Guo, Shibo He, Zhiguo Shi 0001, Jiming Chen 0001
ICNP1