5GNOW: non-orthogonal, asynchronous waveforms for future mobile applications
By Gerhard Wunder, Peter Jung, Martin Kasparick, Thorsten Wild, Frank Schaich, Yejian Chen, Stephan ten Brink, Ivan Simoes Gaspar, Nicola Michailow, Andreas Festag and 8 more. IEEE Communications Magazine, 2014
916 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/c7a0e96bf72e9b8ab5e59c829d718be5ab6fa787
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Qingqing Wu
- Rui Zhang
- Geoffrey Y. Li
- Shunqing Zhang
- Shugong Xu
- Frank Schaich
- Thorsten Wild
- Abhishek Roy
In Electrical and Electronic Engineering
- Rui Zhang
- Qingqing Wu
- Geoffrey Y. Li
- Andreas F. Molisch
- Shunqing Zhang
- Shugong Xu
- Ismail Güvenç
- Thorsten Wild
Citations in the corpus
- 5G: A Tutorial Overview of Standards, Trials, Challenges, Deployment, and Practice (2017, background): “Recent research (e.g. as part of the European projects 5GNOW [153], FANTASTIC-5G [154] and mmMAGIC [155]) has produced a plethora of waveform candidates depicted in Table III.”
- Next Generation 5G Wireless Networks: A Comprehensive Survey (2016, background): “from the human centric interactions to a M2M platform [24] equipped with 5G wireless.”
- Non-orthogonal Multiple Access (NOMA) with Successive Interference Cancellation for Future Radio Access (2015, neutral): “INVITED SURVEY PAPER”
- 5G Backhaul Challenges and Emerging Research Directions: A Survey (2016, background): “Small cells are multi radio access technologies (multi-RAT) capable and represent an essential part of UDNs, which are considered an imperative 5G solution [3]–[8].”
- Waveform contenders for 5G — OFDM vs. FBMC vs. UFMC (2014, methodology): “SMT exhibits higher spectral efficiency and is more heavily promoted (e.g. [3] [6]) than FMT and thus we concentrate on SMT in the following.”
- Machine Learning for 5G/B5G Mobile and Wireless Communications: Potential, Limitations, and Future Directions (2019, background): “These schemes can be combined with open- and closed-loop MIMO schemes [137], [138].”
- Challenges in 5G: how to empower SON with big data for enabling 5G (2014, background): “For a detailed rationale behind these projected capacity growth dimensions, the reader is referred to [2] [3] [4] [5] [6] [7] [8].”
- The Emerging Trends of Multi-Label Learning (2020, background): “Recently, the development of mobile applications has become one of the most important topics in communications [187].”
- User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions (2021, neutral): “This solution employs power domain multiplexing and SIC to support multiple users with the same time-frequency resources [191], hence boosting the capacity of the system at the expense of added interference.”
- A Survey of In-Band Full-Duplex Transmission: From the Perspective of PHY and MAC Layers (2015, background): “2403614 Orthogonal Waveforms for Asynchronous Signaling (5GNOW) [1]–[4] and Mobile and wireless communications Enablers for”
- A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions (2017, background): “Even though asynchronous mode of communication is more favorable over synchronized operation in terms of latency, it requires additional spectrum and power resources [33].”