Peng Li
Shaanxi Normal University
20 Papers
104 Citations
Peng Li is an academic researcher from Shaanxi Normal University. The author has contributed to research in topics: Cognitive radio & Collaborative learning. The author has an hindex of 6, co-authored 20 publications. Previous affiliations of Peng Li include Chinese Ministry of Education & Georgia State University.
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Papers
Spectrum-Availability Based Routing for Cognitive Sensor Networks
TL;DR: This work estimates the spectrum availability and spectrum quality from the view of both the global statistical spectrum usage and the local instant spectrum status, and introduces novel routing metrics to consider the estimation.
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An efficient privacy preserving data aggregation approach for mobile sensing
TL;DR: This work proposes an efficient data aggregation approach by which an untrusted aggregator in mobile sensing can collect the statistics over the data contributed by multiple mobile users, while supporting privacy preservation of each user and data integrity verification.
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User social activity-based routing for cognitive radio networks
Junling Lu,Zhipeng Cai,Xiaoming Wang,Lichen Zhang,Peng Li,Zaobo He +5 more
- 01 Jun 2018
TL;DR: This work approximate primary activity probability based on the real datasets of mobile phone usage records, then the spectrum opportunity between a pair of communication SUs is deduced based on primary activities, and a greedy routing algorithm is proposed to verify the idea.
25
Exploiting Spectrum Availability and Quality in Routing for Multi-hop Cognitive Radio Networks
Lichen Zhang,Zhipeng Cai,Peng Li,Xiaoming Wang +3 more
- 08 Aug 2016
TL;DR: Novel routing metrics that estimate both the future spectrum availability and the average transmission time are introduced and two routing algorithms for multi-hop CRNs are proposed that attempt to reduce the probability of spectrum handoff and rerouting upon PU’s arrival.
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The impact of node velocity diversity on mobile opportunistic network performance
TL;DR: This paper explores the impact of node velocity diversity on the performance of mobile opportunistic networks while keeping the average velocity of nodes consistent with each other and constructs mathematical models to analyze node contact times and link numbers.
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