Artificial neural networks-based machine learning for wireless networks: A tutorial
In order to effectively provide ultra reliable low latency communications and pervasive
connectivity for Internet of Things (IoT) devices, next-generation wireless networks can …
connectivity for Internet of Things (IoT) devices, next-generation wireless networks can …
Game-theoretic methods for the smart grid: An overview of microgrid systems, demand-side management, and smart grid communications
The future smart grid is envisioned as a large scale cyberphysical system encompassing
advanced power, communications, control, and computing technologies. To accommodate …
advanced power, communications, control, and computing technologies. To accommodate …
Learning how to communicate in the Internet of Things: Finite resources and heterogeneity
For a seamless deployment of the Internet of Things (IoT), there is a need for self-organizing
solutions to overcome key IoT challenges that include data processing, resource …
solutions to overcome key IoT challenges that include data processing, resource …
A survey of game theory in unmanned aerial vehicles communications
Unmanned aerial vehicles (UAVs) can be deployed as wireless relays or aerial base
stations to improve network connectivity and coverage in cellular networks. UAVs can also …
stations to improve network connectivity and coverage in cellular networks. UAVs can also …
Self-organization in small cell networks: A reinforcement learning approach
In this paper, a decentralized and self-organizing mechanism for small cell networks (such
as micro-, femto-and picocells) is proposed. In particular, an application to the case in which …
as micro-, femto-and picocells) is proposed. In particular, an application to the case in which …
Reinforcement learning in energy trading game among smart microgrids
Reinforcement learning (RL) is essential for the computation of game equilibria and the
estimation of payoffs under incomplete information. However, it has been a challenge to …
estimation of payoffs under incomplete information. However, it has been a challenge to …
Game theory for networks: A tutorial on game-theoretic tools for emerging signal processing applications
The aim of this tutorial is to provide an overview, although necessarily incomplete, of game
theory (GT) for signal processing (SP) in networks. One of the main features of this …
theory (GT) for signal processing (SP) in networks. One of the main features of this …
An evolutionary game for distributed resource allocation in self-organizing small cells
We propose an evolutionary game theory (EGT)-based distributed resource allocation
scheme for small cells underlaying a macro cellular network. EGT is a suitable tool to …
scheme for small cells underlaying a macro cellular network. EGT is a suitable tool to …
Optimal power allocation and user scheduling in multicell networks: Base station cooperation using a game-theoretic approach
This paper proposes a novel base station (BS) coordination approach for intercell
interference mitigation in the orthogonal frequency-division multiple access based cellular …
interference mitigation in the orthogonal frequency-division multiple access based cellular …
Learning and reasoning in cognitive radio networks
L Gavrilovska, V Atanasovski… - … Surveys & Tutorials, 2013 - ieeexplore.ieee.org
Cognitive radio networks challenge the traditional wireless networking paradigm by
introducing concepts firmly stemmed into the Artificial Intelligence (AI) field, ie, learning and …
introducing concepts firmly stemmed into the Artificial Intelligence (AI) field, ie, learning and …