A Q-learning based autonomic Joint Radio Resource Management algorithm

作者：Zhang, Yong-Jing; Feng, Zhi-Yong; Zhang, Ping

来源：JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2008, 30(3): 676-680.

DOI：10.3724/sp.j.1146.2006.01357

• Joint admission control
• Q-learning
• Radio access technology (RAT)
• Resource Management

A Q-learning based Joint Radio Resource Management (JRRM) algorithm is proposed for the autonomic resource optimization in a B3G system with heterogeneous Radio Access Technologies (RAT). Through the 'trial-and-error'interactions with the radio environment, the JRRM controller learns to allocate the proper RAT and the service bandwidth for each session. A backpropagation neural network is adopted to generalize the large input state space to reduce memory requirement. Simulation results show that the proposed algorithm not only realizes the autonomy of JRRM through the online learning process, but also achieves well trade-off between the spectrum utility and the blocking probability.

• 出版日期2008-3
• 单位北京邮电大学