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Yin Sun

Researcher at Auburn University

Publications -  128
Citations -  5168

Yin Sun is an academic researcher from Auburn University. The author has contributed to research in topics: Throughput & Communication channel. The author has an hindex of 31, co-authored 128 publications receiving 3705 citations. Previous affiliations of Yin Sun include Ohio State University & Rice University.

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Capacity of Compound MIMO Gaussian Channels with Additive Uncertainty

TL;DR: In this article, the authors studied the optimal transmit covariance matrix design to achieve the capacity of compound MIMO Gaussian channels, where the channel uncertainty region is characterized by the spectral norm.
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Sampling for Remote Estimation through Queues: Age of Information and Beyond

TL;DR: In this article, an interesting connection between the age of information and remote estimation error was found in a sampling problem of Wiener processes: if the sampler has no knowledge of the signal being sampled, the optimal sampling strategy is to minimize the age, however, by exploiting causal knowledge of signal values, it is possible to achieve a smaller estimation error.
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Joint Beam and Channel Tracking for Two-Dimensional Phased Antenna Arrays

TL;DR: In this paper, the authors developed a beam probing and tracking algorithm that can efficiently track fast-moving mm-wave beams in three-dimensional (3D) space, which achieves the minimum probing requirement for joint beam and channel tracking.
Patent

Trapping wave forming method of originating broadband signal with variable parameters

TL;DR: In this paper, the authors proposed a cascade trapper-based method for originating broadband signals with variable parameters, which consists of detecting the number n of useful narrow-band signals in real time and the bandwidth and frequency band distribution of each useful narrowband signal.
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Designing Low-Complexity Heavy-Traffic Delay-Optimal Load Balancing Schemes: Theory to Algorithms

Abstract: We establish a unified analytical framework for load balancing systems, which allows us to construct a general class $\Pi$ of policies that are both throughput optimal and heavy-traffic delay optimal. This general class $\Pi$ includes as special cases popular policies such as join-shortest-queue and power-of-$d$, but not the join-idle-queue (JIQ) policy. In fact, we show that JIQ, which is not in $\Pi$, is actually not heavy-traffic delay optimal. Owing to the significant flexibility offered by class $\Pi$, we are able to design a new policy called join-below-threshold (JBT-d), which maintains the simplicity of pull-based policies such as JIQ, but updates its threshold dynamically. We prove that JBT-$d$ belongs to the class $\Pi$ when the threshold is picked appropriately and thus it is heavy-traffic delay optimal. Extensive simulations show that the new policy not only has a low complexity in message rates, but also achieves excellent delay performance, comparable to the optimal join-shortest-queue in various system settings.