Next generation 5G wireless solutions need to meet the anticipated demands of Machine-to-Machine (M2M) communications in the 2020 era with the total number of devices expected to be about 50 billion for a projected population of around 8 billion according to an Ericsson report. M2M applications can be classified into two categories: Low-cost wide-area and low-latency ultra-reliable M2M. Low-cost wide-area M2M communication requires simple hardware architecture, integration of significant energy efficiency methods and energy harvesting technologies, and enhanced coverage, for such applications as smart metering, fire alarms, sensor networks. Despite LTE enhancements proposed for this class of M2M, however, LTE is not expected to be dominantly used in the near future due to its low coverage and high cost equipment, according to Cisco VNI Mobile, 2015. More research is needed to natively include this M2M class in 5G networks. On the other hand, low-latency ultra-reliable M2M communication requires satisfying strict delay constraint and ultra-high reliability of such applications as platooning of vehicles, robotic control and interaction, remote health care. Controlling the elements in our environment based on the data provided from these machines in this class of M2M applications requires a paradigm shift for control and communication systems with novel strategies for their joint design in beyond 5G networks.

1. Machine-to-Machine Communications:
Beyond 5G
Sinem Coleri Ergen
Wireless Networks Laboratory,
Electrical and Electronics Engineering,
Koc University
29/6/2015
Joint Expert Group and Vision Group Workshop - EUCnC

2. Evolution in Telecom Industry into Future
Huawei Technologies, Wireless World Research Forum, 2011
Data rate

3. Alternatives for M2M Communications
Wired: Cable, xDSL,
optical
• High reliability
• High rate
• Small delay
• Not cost effective
• Lack of scalability
• Lack of mobility
Wireless capillary: WLAN,
Zigbee, IEEE 802.15.4x
• Less expensive
• Generally scalable
• Low power
• Weak security
• Interference
• Lack of universal infrastructure
Cellular: 2G, 3G, 4G, 5G
• Ubiquitous coverage
• Mobility
• Roaming
• Security

4. 4G Extensions for M2M
LTE-Release 11
• Overload control
• Use Extended Access Barring
in overload
LTE-Release 12
• New lower device category:
Cat-0
• Complexity reduction
• Elementary power savings
LTE-Release 13
• LTE MTC: Further reduced
category
• New, simpler device
• Significant power savings
• Enhanced coverage

5. Global M2M Mobile Devices
q 2G currently preferred
q Lower device cost
q Greater geographic coverage
q Longer battery lifetime than 3G
and 4G
q Low data rate
q Low Power Wide Area
(LPWA)
q High coverage
q Very low cost connectivity
q Very low data rate
q Long battery life
q Neul, Sigfox, OnRamp
Coverage and cost of LTE MTC not enough
Source: Cisco VNI Mobile, 2015.

6. NGM 5G M2M Use Cases
Low-cost Wide Area M2M
Low data rate: 1-1000kbps
High Energy Efficiency: up to 15
year lifetime
High Density: up to 200,000/
km^2
Low-latency Ultra-Reliable M2M
Low data rate: DL: From 50kbps to 10Mpbs
UL: From a few bps to 10Mpbs
Low E2E latency: <1ms
High reliability: >99.999%
4G and Beyond 5G and Beyond

7. M2M: 5G and Beyond
Low-cost Wide-area M2M
• Goals
• Decrease cost
• Decrease power consumption
• Increase coverage
• Provide scalability
• Research
• Simpler hardware architecture
• Novel waveform design
• UFMC, GFDM, SC, tunable
OFDM
• Energy harvesting
• Vibration, light, wireless energy
harvesting
• Novel delay tolerant reliable access
mechanisms
Low-latency Ultra-reliable M2M
• Goals
• Strict delay constraint
• Ultra-high reliability
• Short packet size
• Low/medium power consumption
• Research
• Novel waveform design
• Novel delay and reliability
constrained access mechanisms
• Short packet transmission
• Model interaction of communication
and control systems

8. M2M: 5G and Beyond
Low-cost Wide-area M2M
• Goals
• Decrease cost
• Decrease power consumption
• Increase coverage
• Provide scalability
• Research
• Simpler hardware architecture
• Novel waveform design
• UFMC, GFDM, SC, tunable
OFDM
• Energy harvesting
• Vibration, light, wireless energy
harvesting
• Novel delay tolerant reliable access
mechanisms
Low-latency Ultra-reliable M2M
• Goals
• Strict delay constraint
• Ultra-high reliability
• Short packet size
• Low/medium power consumption
• Research
• Novel waveform design
• Novel delay and reliability
constrained access mechanisms
• Short packet transmission
• Model interaction of
communication and control
systems

9. Cyber-Physical Systems
q Sensors, actuators and controllers connect through a
wireless network

10. Joint Optimization of Communication and Control Systems
Wireless
Communication
Non-zero packet error probability
• Unreliability of wireless transmissions
Non-zero delay
• Packet transmission and shared
wireless medium
Sampling and quantization errors
• Signals transmitted via packets
Limited battery resources
Control System
Stringent requirements on timing
and reliability
Smaller packet error probability,
delay and sampling period
Better control system
performance
More energy consumed in
wireless communication
Smaller packet error probability,
delay and sampling period
Better control system
performance
More energy consumed in
wireless communication
Y. Sadi, S. C. Ergen and P. Park, "Minimum Energy Data Transmission for Wireless Networked Control Systems", IEEE
Transactions on Wireless Communications, vol. 13, no. 4, pp. 2163-2175, April 2014.
Y. Sadi and S. C. Ergen, "Joint Optimization of Communication and Controller Components of Wireless Networked Control
Systems", IEEE ICC, June 2015.

11. Ultra-Reliable Delivery of Periodic Sensor Packets
EDF
Uniform

12. Ultra-Reliable Delivery of Periodic Sensor Packets
EDF Uniform
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13. Ultra-Reliable Delivery of Periodic Sensor Packets
Uniform distribution minimize max subframe active time
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≡
EDF
Uniform
max active time=0.9ms
max active time=0.6ms
✓
Y. Sadi and S. C. Ergen, "Energy and Delay Constrained Maximum Adaptive Schedule for Wireless Networked Control Systems",
accepted to IEEE Transactions on Wireless Communications.
Y. Sadi and S. C. Ergen, “Optimal Power Control, Rate Adaptation and Scheduling for UWB-Based Intra-Vehicular Wireless Sensor
Networks”, IEEE Transactions on Vehicular Technology, vol. 62, no. 1, pp. 219-234, January 2013.

14. Past and Current Projects
Intra-Vehicular Wireless Sensor
Networks
• Supported by Marie Curie Reintegration Grant
Energy Efficient Robust
Communication Network Design for
Wireless Networked Control Systems
• Supported by TUBITAK (The Scientific and
Technological Research Council of Turkey)
Energy Efficient Machine-to-Machine
Communications
• Supported by Turk Telekom
Cross-layer Epidemic Protocols for
Inter-vehicular Communication
Networks
• Supported by Turk Telekom
RSSI Fingerprinting based Mobile
Phone Localization with Route
Constraints
• Supported by UC Berkeley
Intra Vehicular Sensor Networks
• Supported by TOFAŞ

15. People
Director
• Sinem Coleri Ergen
Ph.D.
Students
• Yalcin Sadi | Seyhan Ucar | Elif Dilek Salik | Merve Saimler | Ali Vosoughi | Adil
Abbas | Melih Karaman | Bugra Turan
M.S.
Students
• Anique Akhtar | Bakhtiyar Farayev
Alumni
• Mehmet Kontik | Utku Demir | Umit Bas | Nabeel Akhtar | Irem Nizamoglu

16. Thank You!
Sinem Coleri Ergen: sergen@ku.edu.tr
Personal webpage: http://home.ku.edu.tr/~sergen
Wireless Networks Laboratory: http://wnl.ku.edu.tr