Learning-Based Reconfigurable Multiple Access Schemes for Virtualized MTC Networks

Preface
Contents
Acronyms
1 Introduction
	1.1 Machine-type Communications
	1.2 Machine-type Applications
		1.2.1 Industrial Automation and Control
		1.2.2 Intelligent Transportation
			1.2.2.1 M2M-Assisted Driving
			1.2.2.2 Fleet Management
			1.2.2.3 e-Ticketing and Passenger Services
			1.2.2.4 Smart Parking
		1.2.3 Smart Grid
		1.2.4 Smart Environment
			1.2.4.1 Smart Homes, Offices, and Shops
			1.2.4.2 Smart Lighting
		1.2.5 Security and Public Safety
			1.2.5.1 Remote Surveillance
			1.2.5.2 Personal Tracking
			1.2.5.3 Public Infrastructure Protection
		1.2.6 e-Health
	1.3 Machine-type Communication Characteristics
	1.4 Multiple Access Schemes and their Requirements in MTC
	1.5 Book Organization
	References
2 Multiple Access Schemes for Machine-Type Communications: A Literature Review
	2.1 Multiple Access Schemes for MTC
		2.1.1 Scheduling-Based Schemes in LTE
			2.1.1.1 LTE Frame Structure
			2.1.1.2 Existing Scheduling-Based Access Schemes for MTC Over LTE
		2.1.2 Random Access Schemes in LTE
			2.1.2.1 Random Access Procedure in LTE
		2.1.3 Failure of RA Procedure and Its Inefficiency in MTC Systems
			2.1.3.1 Enhancements of the RA Procedure
		2.1.4 Random Access Schemes in WiFi
		2.1.5 Hybrid Schemes
	2.2 Machine-type Communications in LTE/WiFi Coexistence
		2.2.1 Existing Works on LTE-LAA and WiFi Coexistence
	2.3 NOMA-Enhanced Multiple Access Schemes for MTC
		2.3.1 Overview of Uplink NOMA
		2.3.2 Existing NOMA Schemes
			2.3.2.1 Grant-Based NOMA
			2.3.2.2 Grant-free NOMA
			2.3.2.3 Compressed Sensing-Based NOMA
	2.4 Massive MIMO for Massive MTC
		2.4.1 Grant-Based Random Access Schemes
		2.4.2 Grant-free Random Access Schemes
		2.4.3 Grant-free Access Relying on Compressed Sensing
	2.5 Fast Uplink Grant for MTC
		2.5.1 Existing Works
			2.5.1.1 Cellular Traffic Prediction
			2.5.1.2 Device Traffic Prediction
	2.6 Concluding Remarks
	References
3 MDP-Based Access Scheme for Virtualized M2M Networks
	3.1 Introduction
	3.2 System Model
	3.3 MDP-Based Access Scheme Design
	3.4 Heuristic Algorithm for Backoff Generation
	3.5 Numerical Results
	3.6 Concluding Remarks
	Appendix: An overview of MDP model
		Model Description
		Time Horizon and Discount Factor
		Observations, Policies and Value Function
	References
4 Reconfigurable and Traffic-Aware Access Schemes for Virtualized M2M Networks
	4.1 Introduction
	4.2 System Model
		4.2.1 Network Model and Frame Structure
		4.2.2 Traffic and Channel Models
		4.2.3 Device Operation
		4.2.4 An Analytical Model for p-persistent CSMA
	4.3 Problem Formulation
	4.4 Reconfigurable Access Scheme Scheduling with Traffic Knowledge
		4.4.1 Reconfigurable Access Scheme Scheduling via CGP
		4.4.2 Computational Complexity of the Proposed Algorithm
		4.4.3 Scalable Reconfigurable Access Scheme for Dense Networks
	4.5 Illustrative Results
		4.5.1 CGP-Based Reconfigurable Access Scheme
		4.5.2 Scalable Reconfigurable Access Scheme
	4.6 Concluding Remarks
	Appendix 1: A Brief Overview of Complementary Geometric Programming
	Appendix 2: An Overview of Difference of Convex
	References
5 Learning-Based Reconfigurable Access Schemes for Virtualized M2M Networks
	5.1 Introduction
	5.2 Related Works
		5.2.1 Overview of MAB
		5.2.2 Existing Works
	5.3 Learning-Based Reconfigurable Access Scheme via Thompson Sampling
		5.3.1 Thompson Sampling
		5.3.2 Thompson Sampling for Reconfigurable Access Scheme
		5.3.3 Thompson Sampling for Thresholding Multi-Armed Bandits
	5.4 Regret Analysis
	5.5 Illustrative Results
		5.5.1 Reconfigurable Access Scheme: Unknown Statistics
			5.5.1.1 Effect of Suboptimal Arms Statistic
			5.5.1.2 Effect of Time
	5.6 Concluding Remarks
	Appendix
		Proof of Lemma 5.3
	References
6 Efficient and Fair Access Scheme for MTC: LTE/WiFi Coexistence Case
	6.1 Introduction
	6.2 System Model
		6.2.1 Coordinated Structure for LTE/WiFi Coexistence
	6.3 Hybrid Scheduling via CGP for LTE and WiFi Coexistence
		6.3.1 Problem Formulation
		6.3.2 Computational Complexity of the Proposed Algorithm
		6.3.3 Signaling Aspect of the Proposed Structure
	6.4 Admission Control for LTE Devices
		6.4.1 Assumptions
		6.4.2 Modeling the LTE Scheduling Algorithm
		6.4.3 Delay Analysis
			6.4.3.1 Derivation of p0
			6.4.3.2 Derivation of Lf(l,n)
			6.4.3.3 Derivation of P(Ef) and P(Ec)
			6.4.3.4 Average Packet Delay
	6.5 Illustrative Results
		6.5.1 Effect of Increasing Nl
		6.5.2 Effect of Increasing Nw
		6.5.3 Homogeneous LTE Network
		6.5.4 Computational Complexity
	6.6 Concluding Remarks
	References
7 A NOMA-Enhanced Reconfigurable Access Scheme with Device Pairing for MTC
	7.1 Introduction
	7.2 System Model
		7.2.1 NOMA with Imperfect SIC
		7.2.2 NOMA-Enhanced Reconfigurable Access Scheme
	7.3 Problem Formulation
		7.3.1 Optimization Problem
	7.4 Device Pairing for NOMA
		7.4.1 Introduction to Weighted Matching Problem
		7.4.2 Proposed Device Pairing Algorithm
	7.5 Scheduling Algorithm for NERA Scheme
		7.5.1 NDFA-ODFA Scheduling Sub-problem
		7.5.2 p-Probability Derivation Sub-problem
		7.5.3 Reconfigurable Access Scheme
		7.5.4 Computational Complexity
	7.6 Performance Evaluation
	7.7 Concluding Remarks
	References
8 A Distributed Contention-Resolution Self-Organizing TDMA Scheme for MTC
	8.1 Introduction
	8.2 System Model
	8.3 Proposed Self-Organizing TDMA (SO-TDMA)
		8.3.1 Initial Access Phase
		8.3.2 Periodic Transmission Phase
			8.3.2.1 AIMD Time-Slot Adaptation Algorithm
	8.4 Convergence Analysis
		8.4.1 Convergence Time: Initial Access Phase
		8.4.2 Convergence to Fairness: Periodic Transmission Phase
	8.5 Illustrative Results
		8.5.1 Simulation Setup and Assumptions
		8.5.2 SO-TDMA Convergence
		8.5.3 Effective Capacity and Delay Outage Probability
		8.5.4 System Throughput
		8.5.5 Fairness
		8.5.6 Collision Probability
		8.5.7 Impact of Device Dynamics
	8.6 Concluding Remarks
	Appendix
		Proof of Lemma 8.1
	References
9 Conclusions and Future Works
	9.1 Summary
	9.2 Potential Future Studies
		9.2.1 Correlated Traffic
		9.2.2 Massive MIMO
		9.2.3 URLLC Use Case
		9.2.4 Machine Learning
		9.2.5 Integrating Massive MIMO, NOMA, Full Duplex
	References