This document proposes a MAC protocol design for cellular-based M2M communications that improves energy efficiency. It presents a system model where machine nodes communicate via a cellular network. The proposed MAC design uses clustering, with multi-phase CSMA for intra-cluster communication and dynamic TDMA for inter-cluster communication. Simulation results show the proposed MAC extends battery life by 500% on average by improving energy efficiency through clustering, while sacrificing some delay performance. The design aims to make efficient use of energy for massive M2M access over cellular networks.

1. KTH ROYAL INSTITUTE
OF TECHNOLOGY
Energy Efficient MAC for Cellular-Based
M2M Communications
Amin Azari and Guowang Miao
KTH Royal Institute of Technology
GlobalSIP Conference, 2014, Atlanta, USA

2. Contents:
• Introduction
• System model and problem formulation
• Proposed MAC design
• Simulation Results
• Conclusion
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3. Motivation
Future wireless access (5G)
• Key challenges
• Continued traffic growth in terms of volume
• Continued traffic growth in terms of number of devices
• Spectral & Enrgy efficient system design
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4. M2M communication
• M2M communications: Communication of smart devices
without human intervention.
• Some characteristics:
• Large number of short-lived sessions
• (usually) low-payload
• Vastly diverse characteristics (e.g. battery capacity)
• Vastly diverse QoS requirements (e.g. delay)
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5. M2M Communication Enablers
ReliabilityAvailability
Cellular-based M2M
Proprietary Cellular
Low-power WLAN
Zigbee-like
Low-power Bluetooth
• Reliability = resilience to interference, throughput and outage guarantees
Reference: GREEN NETWORK TECHNOLOGIES FOR MTC IN 5G, Jesus Alonso-Zarate,
EIT/ICT Summer school presentation
• Availability = coverage, roaming, mobility
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Coverage
Mobility & Roaming
Interference Control
Energy Efficiency ?
☑
☑
☑

6. Contents:
• Introduction
• System model and problem formulation
• Proposed MAC design
• Simulation Results
• Conclusion
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7. System model
• Single Cell
• N machine nodes
• Battery-driven nodes
• Long battery-life is desired
• Specific resource allocation for M2M (no cellular user)
• Event-driven traffic (Poisson packet arrival)
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8. Problem formulation
• Clustering design
• Complete, partial or no-clustering?
• Number of clusters
• Cluster-head selection & reselection
• Communication Protocol
• Intra-cluster communication protocol
• Inter-cluster communication protocol
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9. Problem formulation
• Clustering design
• Presented in
Energy-Efficient Clustering Design for M2M Communications,
G. Miao and P. Zhang, GlobalSIP 2014
• Communication protocol design
• In this work
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10. Contents:
• Introduction
• System model and problem formulation
• Proposed MAC design
• Clustering for cellular-based M2M
• Intra-cluster communication
• Inter-cluster communication
• Simulation Results
• Conclusion
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11. Proposed MAC design: Clustering
• Clustering
• Given desired receive SNR
• Calculate transmission power at ith node, 𝑃𝑖
• If 𝑃𝑖 > 𝑡ℎ𝑟𝑒𝑠ℎ𝑜𝑙𝑑
– node i is to be clustered
• In each cluster the node with the lowest 𝑃𝑖 will be CH.
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12. Proposed MAC design: Intra-cluster
Communication
• Intra-cluster communication
• Low traffic load
• CSMA/CA has good performance in low-load regime
• Scalable, low signaling overhead, and acceptable EE
• The EE, delay, and user capacity analysis:
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13. Proposed MAC design: Multi-Phase CSMA
• Even more energy efficiency
• Multi-phase CSMA for intra-cluster communication
• Enables close-to-zero power wastage
• Needs local synchronization (tradeoff)
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Analytical performance evaluation is presented to
verify performance improvment.

14. Proposed MAC design: Inter-cluster
• Inter-cluster communication
• Heterogeneous system
• Length of data packet (CH and CM)
• State: delay critical, queue status and residual energy
• Interference to the cellular users must be avoided.
THEN
• Reservation-based protocols (e.g. dynamic TDMA)
• Moderate scalability and energy-saving
• Analytical results are omitted from the paper due to the page
limit.
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15. Proposed MAC: Communication frame
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Inter-clusterIntra-cluster
Multi-phase
CSMA
Reservation
Notification
Transmission
Notification

16. Contents:
• Introduction
• System model and problem formulation
• Proposed MAC design
• Simulation Results
• Conclusion
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17. Simulation Results: System Model
• Single cell with LTE base station
• Uplink transmission of 𝑁 battery-driven machine nodes
• 4-phase CSMA for intra-cluster communication
• Dynamic TDMA for inter-cluster communication
• Poisson packet arrival at nodes
• Clustering threshold: varied
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18. Simulation Results_1
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Partial clustering
Delay and energy performance evaluation
No clustering
Complete
clustering

19. Simulation Results Analysis
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• Clustering is not always (for all nodes) EE
• However, it always eases the massive access problem
• Partial clustering outperforms non- and all-clustering
• Delay performance is sacrificed for getting EE
• Tradeoff delay/energy efficiency

20. Simulation Results_2
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Battery lives of cluster heads (CH) and members (CM) for proposed MAC
and dynamic TDMA
Cluster
member in
proposed
MAC
Cluster head
in proposed
MAC

21. Simulation Results Analysis
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• Proposed MAC has extended the battery life of nodes.
• The extension is 500% on average and 800% at some points.
• The battery life of cluster heads is sacrificed by 50%.
• Cluster-head reselection scheme

22. Conclusion
• Key requirement for enabling M2M communication over
cellular networks
• Providing efficiency
• Energy efficient massive access can prolong the lifetime
• Clustering for all nodes is not EE
• Using CH reselection algorithms, one can prolong the
overall network lifetime
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23. Future works
• Revisiting design principles of cellular networks to address
massive access problem in an efficient way
• Considering heterogeneous characteristics of machine
nodes
• Considering heterogeneous QoS of machine nodes
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24. Thanks for your participation.
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25. Supporting Materials
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26. Cellular-based M2M
M2M communications supported by cellular networks
• Direct or through gateway
Advantages:
• Ubiquitous Coverage
• Mobility & Roaming
• Interference Control
Disadvantages:
• Designed and optimized for small number of long-lived sessions
• Massive access problem
• Energy inefficiency
• Attaching to the network is contention-based, etc.
• Physical layer inefficiency
• Not optimized for small data payload
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27. Problem formulation
• Access schemes
• Contention-free schemes
– Not scalable (High signaling)
– High average packet delay
– High energy efficiency
• Contention-based schemes
– Scalable and distributed
– Low-delay in low-load/ High-delay in high-load
– Energy wasting in medium- to high-load regime
• Reservation-based schemes
– Contention-based in reservation, -free in transmission
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28. Details of the derived performance analyses
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𝑔: aggregated traffic arrival rate
ps: probability of successful transmission
𝜏 𝑠 = 𝜏 𝑝+ 𝜏 𝑟
𝜏 𝑝: packet length
𝜏 𝑟: Round trip time from transmission to acknowledgement.

29. Energy Efficient System Design
• Energy Saving ≠ Energy Efficiency
• Complete Saving of Energy = Shut down network
completely to save the most energy
• Not desired!
• Purpose of energy-efficient wireless network design
• Not to save energy
• Make the best/efficient use of energy!
• Energy saving w/o losing service quality
• Bit-per-Joule design metric
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