12 citations · 98 across the 61 of their papers we have counts for
25 papers · 1 filter
Deep Multi-Agent Reinforcement Learning Based Cooperative Edge Caching in Wireless Networks
Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
The growing demand on high-quality and low-latency multimedia services has led to much interest in edge caching techniques. Motivated by this, we in this paper consider edge cachin…
Power Control for Wireless VBR Video Streaming: From Optimization to Reinforcement Learning
Chuang Ye, M. Cenk Gursoy, Senem Velipasalar
In this paper, we investigate the problem of power control for streaming variable bit rate (VBR) videos over wireless links. A system model involving a transmitter (e.g., a base st…
Actor-Critic Deep Reinforcement Learning for Dynamic Multichannel Access
Chen Zhong, Ziyang Lu, M. Cenk Gursoy +1
We consider the dynamic multichannel access problem, which can be formulated as a partially observable Markov decision process (POMDP). We first propose a model-free actor-critic d…
Learning-Based Delay-Aware Caching in Wireless D2D Caching Networks
Yi Li, Chen Zhong, M. Cenk Gursoy +1
Recently, wireless caching techniques have been studied to satisfy lower delay requirements and offload traffic from peak periods. By storing parts of the popular files at the mobi…
A Deep Reinforcement Learning-Based Framework for Content Caching
Chen Zhong, M. Cenk Gursoy, Senem Velipasalar
Content caching at the edge nodes is a promising technique to reduce the data traffic in next-generation wireless networks. Inspired by the success of Deep Reinforcement Learning (…
Joint Mode Selection and Resource Allocation for D2D Communications via Vertex Coloring
Yi Li, M. Cenk Gursoy, Senem Velipasalar +1
Device-to-device (D2D) communication underlaid with cellular networks is a new paradigm, proposed to enhance the performance of cellular networks. By allowing a pair of D2D users t…