Abstract—This paper introduces a novel Q-value based adap-tive call admission control scheme (Q-CAC) for distributed reinforcement learning (RL) based dynamic spectrum access (DSA) in mobile cellular networks, which provides a good quality of service (QoS) without the need for spectrum sensing. A

academic behavior, and research of Williams, Grow, Freedman, Ryan, and Deci (1996), which showed that over a 23-month period, self-determined motivation positively predicted attendance at weight loss program meetings. Thus, the present findings reinforce the notion that motivation is a powerful force

/consumption, experience, and power, are the fundamental ingredients of human action -an action that ultimately produces and modi es social structure. THE NETWORK SOCIETY: AN OVERVIEW In the last two decades of the twentieth centur y a related set of social transformations has taken place around the world. While cultures

Abstract – Game theory is a promising approach for the system-level analysis of power control in wireless networks. This paper extends game-theoretic analysis to the study of link adaptation, which involves the variation of modulation parameters in addition to power control. We use the link

In recent years, game theory has emerged as a promising approach to solving the power control problem in wireless networks. This thesis extends the reach of game-theoretic analysis to embrace link adaptation, thereby constituting a generalization of the power control problem. A realistic

Abstract:- In this paper, we present an adaptive multi-agent reinforcement learning method for solving congestion control problems on high-speed networks. Traditional reactive congestion control regulates source rate in terms of queue length restricted to a predefined threshold. However

-totransmitter feedback and, for cellular networks, cell-to-cell channel state information (CSI) signaling. We give asymptotic properties pertaining to rate-maximizing power control and scheduling in multicell networks. We then present some promising leads for substantial complexity and signaling reduction via the use

centralized control commands from serving base stations. For this purpose, we develop a general non-cooperative game-theoretic framework and characterize the resulting power and rate allocation dynamics in terms of its convergence to network-wide acceptable equilibrium states under stochastic communication

This paper proposes an approach for learning call admission control (CAC) policies in a cellular network that handles several classes of traffic with different resource requirements. The performance measures in cellular networks are long term revenue, utility, call blocking rate (CBR) and handoff

Abstract:- In this paper, adaptive channel management approach fuzzy neural networks in heterogeneous wireless cellular networks (ACM-FNN) is presented to efficient resource allocation, and admission control schemes are needed to guarantee quality-of-service (QoS) for differentiated services