Machine learning integration in Communication system for efficient selection of signals
Through combined antenna selecting and power management design, we examine the
effectiveness of multi-user multiple-antenna downlinks. A fraction of antennas are chosen to …
effectiveness of multi-user multiple-antenna downlinks. A fraction of antennas are chosen to …
Joint user grouping and power allocation for MISO systems: learning to schedule
In this paper, we address ajoint user scheduling and power allocation problem from a
machine-learning perspective in order to efficiently minimize data delivery time for multiple …
machine-learning perspective in order to efficiently minimize data delivery time for multiple …
Recent Trends in 5G and Machine Learning, Challenges, and Opportunities
S Kannadhasan, R Nagarajan… - … for Security Systems …, 2022 - taylorfrancis.com
Fifth-generation (5G) wireless networks must meet a number of unique criteria, including
1,000 times the system capacity of fourth-generation (4G) networks, a broader scope …
1,000 times the system capacity of fourth-generation (4G) networks, a broader scope …
Machine Learning-Based Efficient Resource Scheduling for Future Wireless Communication Networks
Y Yuan - 2022 - orbilu.uni.lu
The next-generation mobile communication system, eg, 6G communication system, is
envisioned to support unprecedented performance requirements such as exponentially …
envisioned to support unprecedented performance requirements such as exponentially …
Machine Learning-Based Node Selection for Cooperative Non-Orthogonal Multi-Access System Under Physical Layer Security
Cooperative non-orthogonal multi access communication is a promising paradigm for the
future wireless networks because of its advantages in terms of energy efficiency, wider …
future wireless networks because of its advantages in terms of energy efficiency, wider …