Post on 25-Jan-2016
description
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
Contents:
• Introduction • System model and problem formulation • Proposed MAC design • Simulation Results • Conclusion
9/8/2015 2
Motivation Future wireless access (5G) • Key challenges
• Continued traffic growth in terms of volume • Continued traffic growth in terms of number of devices • Energy efficient system design
9/8/2015 3
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)
9/8/2015 4
M2M Communication Enablers
Reliability Av
aila
bilit
y
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
9/8/2015 5
Coverage Mobility & Roaming Interference Control Energy Efficiency ?
☑ ☑ ☑
Contents: • Introduction • System model and problem formulation • Proposed MAC design • Simulation Results • Conclusion
9/8/2015 6
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 and data (Poisson packet arrival)
9/8/2015 7
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
9/8/2015 8
Problem formulation
• Clustering design • Presented in
Energy-Efficient Clustering Design for M2M Communications, G. Miao and P. Zhang, GlobalSIP 2014
• Communication protocol • is discussed in this work
9/8/2015 9
Contents: • Introduction • System model and problem formulation • Proposed MAC design
• Clustering for cellular-based M2M • Intra-cluster communication • Inter-cluster communication
• Simulation Results • Conclusion
9/8/2015 10
Proposed MAC design: Clustering
• Clustering • Given desired receive SNR • Calculate transmission power at ith node, 𝑃𝑖
• If 𝑃𝑖 > 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡
– node i is to be clustered
• In each cluster the node with lowest 𝑃𝑖 will be CH.
9/8/2015 11
Proposed MAC design: Intra-cluster Communication
• Intra-cluster communication • Relatively low-load regime
• CSMA/CA has good performance in low-load regime • Scalable, low signaling overhead, and acceptable EE
• The EE, delay, and user capacity analysis:
9/8/2015 12
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)
9/8/2015 13
Analytical results regarding EE and delay are presented.
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 (dynamic TDMA) • Moderate scalability and energy-saving
• Analytical results are omitted from the paper due to the page limit.
9/8/2015 14
Proposed MAC: Communication frame
9/8/2015 15
Inter-cluster Intra-cluster
Multi-phase CSMA Reservation phase
Notification phase Transmission phase
Contents: • Introduction • System model and problem formulation • Proposed MAC design • Simulation Results • Conclusion
9/8/2015 16
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
9/8/2015 17
Simulation Results_1
9/8/2015 18
Partial clustering
Delay and energy performance evaluation
No clustering
Complete clustering
Simulation Results Analysis
9/8/2015 19
• Clustering is not always (for all nodes) EE • However, it always eases the massive access problem
• Partial clustering is optimal • Delay performance is sacrificed for getting EE • Tradeoff delay/energy efficiency
Simulation Results_2
9/8/2015 20
Battery lives of cluster heads (CH) and members (CM) for proposed MAC and dynamic TDMA
Simulation Results Analysis
9/8/2015 21
• 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
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
9/8/2015 22
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
9/8/2015 23
Thanks for your participation.
9/8/2015 24
Supporting Materials
9/8/2015 25
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
9/8/2015 26
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
9/8/2015 27
Details of the derived performance analyses
9/8/2015 28
𝑔: aggregated traffic arrival rate ps: probability of successful transmission
𝜏𝑠 = 𝜏𝑝+ 𝜏𝑟 𝜏𝑝: packet length 𝜏𝑟: Round trip time from transmission to acknowledgement.
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
9/8/2015 29