Title | ||
---|---|---|
Deep-Reinforcement-Learning-Based Optimization for Cache-Enabled Opportunistic Interference Alignment Wireless Networks. |
Abstract | ||
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Both caching and interference alignment (IA) are promising techniques for next-generation wireless networks. Nevertheless, most of the existing works on cache-enabled IA wireless networks assume that the channel is invariant, which is unrealistic considering the time-varying nature of practical wireless environments. In this paper, we consider realistic time-varying channels. Specifically, the cha... |
Year | DOI | Venue |
---|---|---|
2017 | 10.1109/TVT.2017.2751641 | IEEE Transactions on Vehicular Technology |
Keywords | Field | DocType |
Learning (artificial intelligence),Transmitters,Wireless networks,Interference,Receivers,Time-varying channels | Wireless network,Wireless,Cache,Computer science,Efficient energy use,Computer network,Communication channel,Interference (wave propagation),Invariant (mathematics),Reinforcement learning | Journal |
Volume | Issue | ISSN |
66 | 11 | 0018-9545 |
Citations | PageRank | References |
33 | 0.94 | 26 |
Authors | ||
7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ying He | 1 | 248 | 12.27 |
Zheng Zhang | 2 | 267 | 29.51 |
Fei Yu | 3 | 5116 | 335.58 |
Nan Zhao | 4 | 1591 | 123.85 |
Hongxi Yin | 5 | 242 | 19.35 |
Victor C. M. Leung | 6 | 9717 | 759.02 |
Yanhua Zhang | 7 | 145 | 24.84 |