Training Effect on AI-based Resource Allocation in small-cell networks

2021 ◽  
Author(s):  
Alexis Anzaldo ◽  
Angel G. Andrade
Keyword(s):  
Resource Allocation ◽  
Small Cell ◽  
Training Effect ◽  
Small Cell Networks ◽  
Cell Networks

Distributed Dynamic Resource Allocation for OFDMA-Based Cognitive Small Cell Networks Using a Regret-Matching Game Approach

2015 ◽  
pp. 230-253 ◽  
Author(s):  
Wei-Sheng Lai ◽  
Tsung-Hui Chang ◽  
Ta-Sung Lee
Keyword(s):  
Resource Allocation ◽  
Small Cell ◽  
Small Cells ◽  
Allocation Strategy ◽  
Small Cell Networks ◽  
Distributed Resource Allocation ◽  
Cell Network ◽  
Resource Allocation Strategy ◽  
Matching Game ◽  
Cell Networks

Game theoretical approaches have been used to develop distributed resource allocation technologies for cognitive heterogeneous networks. In this chapter, we present a novel distributed resource allocation strategy for cognitive small cell networks based on orthogonal frequency-division multiple access. In particular, we consider a heterogeneous network consisting of macrocell networks overlaid with cognitive small cells that opportunistically access the available spectrum. We focus on a regret-matching game approach, aiming at maximizing the total throughput of the small cell network subject to cross-tier interference and quality of service (QoS) constraints. The regret-matching game approach exploits a regret procedure to learn the optimal resource allocation strategy from the regrets of the actions of cognitive users. Furthermore, the regret-matching game approach is extended to the joint resource allocation and user admission control problem. Numerical results are presented to demonstrate the effectiveness of the proposed regre-matching approaches.

Game Theory-Based Radio Resource Optimization in Heterogeneous Small Cell Networks (HSCNs)

2015 ◽  
pp. 137-183
Author(s):  
Mugen Peng ◽  
Yaohua Sun ◽  
Chengdan Sun ◽  
Manzoor Ahmed
Keyword(s):  
Game Theory ◽  
Resource Allocation ◽  
Small Cell ◽  
Base Stations ◽  
Radio Resource Allocation ◽  
Radio Resource ◽  
Small Cell Networks ◽  
The Game Theory ◽  
Simulation Results ◽  
Cell Networks

To optimize radio resource allocation, the game theory is utilized as a powerful tool because its characteristic can be adaptive to the distribution characteristics of in heterogeneous small cell networks (HSCNs). This chapter summarizes the recent achievements for the game theory based radio resource allocation in HSCNs, where macro base stations (MBSs) and dense small cell base stations (SBSs) share the same frequency spectrum and interfere with each other. Two kinds of game models are introduced to optimize the radio resource allocation, namely the non-cooperative Stackelberg and the cooperative coalition. System models, optimization problem formulation, problem solution, and simulation results for these two kinds of game models are presented. Particularly, the Stackelberg models for HSCNs are presented with the Stackelberg equilibrium and the closed-form expressions. The coalition formations for traditional HCSNs, cloud small cell networks, and heterogeneous cloud small cell networks are introduced. Simulation results are shown to demonstrate the proposed game theory based radio resource optimization strategies converged and efficient.

Sign in / Sign up

Export Citation Format

Share Document