Di Yuan
Uppsala University
269 Papers
2.2K Citations
Di Yuan is an academic researcher from Uppsala University. The author has contributed to research in topics: Wireless network & Scheduling (computing). The author has an hindex of 37, co-authored 268 publications. Previous affiliations of Di Yuan include University of Maryland, College Park & Linköping University.
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Papers
Optimal allocation of non-uniformly partitioned bandwidth for cognitive communications under fading conditions
Song Huang,Anthony Ephremides,Di Yuan +2 more
- 22 May 2016
TL;DR: A non-uniform scheme of bandwidth partition and traffic allocation with the aim of regularizing the primary user's (PU's) bandwidth occupancy pattern is proposed, which is able to improve the performance of the secondary user (SU).
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Routing and Scheduling of Network Flows with Deadlines and Discrete Capacity Allocation
TL;DR: In this paper, the authors address a flow routing and scheduling problem with delivery deadline, where the assignment of link capacity occurs in discrete units and derive an effective reformulation of the problem, via which a column generation algorithm is developed.
A distributed, load-aware, power and frequency bargaining protocol for LTE-based networks
Vangelis Angelakis,Muhammad Sajid,Imran Siddiqui,Di Yuan +3 more
- 10 Jun 2012
TL;DR: The proposed scheme aims to cooperatively limit the impact of Fractional Frequency Reuse on the center users' throughput compared to the Reuse 1 scheme, while providing sufficient throughput for the edge users.
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Probabilistic Cooperation of a Full-Duplex Relay in Random Access Networks
TL;DR: In this article, the authors analyzed the probabilistic cooperation of a full-duplex relay in a multiuser random access network and provided analytical expressions for the performance of the relay queue, such as arrival and service rates, stability conditions, and average queue size.
Pursuing the potential of new mechanisms for performance engineering of 5G
Nikolaos Pappas,Emmanouil Fountoulakis,Cristian Tatino,Vangelis Angelakis,Di Yuan +4 more
- 01 Jun 2017
TL;DR: The authors' modeling enables network anticipation, resulting in an estimation of the coverage probability of mmWave, including coverage with non-line-of-sight (NLOS) mmWave beams, and the use of scalable and dynamic transmission time interval (TTI) for scenarios with a mix of different traffic types.