Reliable Reporting for Massive M2M Communications

In many scenarios, M2M communications involve a massive number of low-rate connections. A showcase application is smart metering, consisting of a massive number of devices, up to 30000 [1], where meters periodically report energy consumption to a remote server for control and billing purposes. Massive communications present a new operating mode, not originally considered in the cellular radio access and that us why M2M-reengineering of the cellular systems has been so much into the research focus. In such a setting, conventional assessment of the system based on the average throughput is not sufficient.

We have instead asked a different question. Let us assume that each message that comes to the sensor needs to be reported within the deadline TRI with guaranteed reliability of, say 99.99%. There is a large number N of potentially reporting devices. How many cellular resources need to be used for such reporting and how to arrange those resources? There are two things that prevent us from assigning deterministic resources for reporting. One is that the arrival of a message at the device is a random process. Another is that the transmission from the device has a random outcome – the packet may end up in error and it will need to be retransmitted. In summary, the amount of resources required by each device is random.

We present a solution to this problem in our paper recently accepted at IEEE Wireless Communications Letters:

[1] Corrales Madueno, G.; Stefanovic, C.; Popovski, P., “Reliable Reporting for Massive M2M Communications With Periodic Resource Pooling,” Wireless Communications Letters, IEEE , vol.3, no.4, pp.429,432, Aug. 2014
doi: 10.1109/LWC.2014.2326674

The key idea to combat the individual randomness associated with each device is to take advantage of the statistical regularity that arises due to the fact that the number of devices N is massive. We show how to allocate resources using this statistical regularity and still guarantee 99.99% to each individual sensor.

A condensed version of the letter is given below.

How to achieve  reliability without sacrificing system efficiency?

Corrales_WCL2014-0193_Fig1

Figure 1: Representation of the LTE uplink resource structure, where a set of RBs has been reserved for M2M purposes.

In [1], we consider a system with a periodically occurring pool of resources that are reserved M2M communications and shared for uplink transmission by all M2M devices (see previous figure). The re-occurring period is selected such that if a report is transmitted successfully within the upcoming resource pool, then the reporting deadline is met.

Corrales_WCL2014-0193_Fig2

Figure 2: a) Periodically occurring M2M resource pool. b) Division of M2M resource pool in the pre-allocated and common pool.

The M2M resource pool is divided into two parts, denoted as the preallocated and  common pool, which reoccur with period TRI, as depicted in previous figure. We assume that there are N reporting devices, and each device is preallocated an amount of RBs from the preallocated pool dimensioned to accommodate a single report and an indication if there are more reports, termed excess reports, from the same device to be transmittedwithin the same interval. The common pool is used to allocate resources for the excess reports, as well as all the retransmissions of the reports/packets that were erroneously received.

The question that arises is:  How many periodically reporting devices can be supported with a desired reliability of report delivery (i.e., 99.99%), for a given number of resources reserved for M2M communications?

We note that, if each device has a deterministic number of packets to transmit in each resource pool and if there are no packet errors, then the problem is trivial, because a fixed number of resources can be preallocated periodically to each device. However, if the number of packets, accumulated between two reporting instances, is random and the probability of packet error is not zero, then the number of transmission resources required per device in each transmission period is random.

The derivation of the individual reporting reliability can be found in [1]. Promising results have been shown in the context of LTE, where even with the lowest-order modulation only 9% of the system resources are required to serve 30K M2M devices with a reliability of 99.99% for a report size of 100 bytes. The proposed method can be applied to other systems, such as 802.11ah.

Corrales_WCL2014-0193_Fig4

Figure 3: Fraction of system capacity used for M2M services, when P[Φ] ≤ 10−3, RI of 1 minute, RS of 100 bytes, bandwidth of 5 MHz and pe = 10−1.

 

[1] Corrales Madueno, G.; Stefanovic, C.; Popovski, P., “Reliable Reporting for Massive M2M Communications With Periodic Resource Pooling,” Wireless Communications Letters, IEEE , vol.3, no.4, pp.429,432, Aug. 2014
doi: 10.1109/LWC.2014.2326674

(Also available in http://massm2m.lab.es.aau.dk/publications.php)

 

MassM2M at the 1st IEEE Workshop on D2D Communications

The IEEE 1st Int. Workshop on D2D and Public Safety Communications (WDPC) took place on April 6, 2014 in Istanbul, in conduction with the IEEE WCNC conference. Petar was one of the keynote speakers, presenting the talk “What is in for D2D in 5G wireless and how to support underlay low-rate M2M links”. The slideshow of the talk can be downloaded here. The full program can be seen at:

http://wdpc.fiu.edu/technical-program/ 

SUNSEED project starts at massM2M group

We announce the beginning of the research project “Sustainable and robust networking for smart electricity distribution – SUNSEED”, funded under call FP7-ICT-2013-11 (STREP). The project started in February 2014, and its duration is three years.

SUNSEED proposes an evolutionary approach to exploitation of already existing communication networks both of energy and telecom operators. The objective of the project is to converge these networks and form a communication infrastructure for future smart energy grids offering open services. The networks’ convergence will be carried out in six steps: overlap, interconnect, interoperate, manage, plan and open; each step involves identification of the related smart grid service requirements and implementation of the appropriate solutions. SUNSEED approach promises much lower investments and total cost of ownership for future smart energy grids with dense distributed energy generation and prosumer involvement.

The researchers from massM2M group, Department of Electronic Systems, AAU, will be primarily involved in M2M aspects of the smart grid services. The focus of the work will be on (1) enhancing and reengineering of the cellular access network, in order to increase its capacity and reliability in order to provide support for massive number of smart grid devices, like PMUs, smart meters, e-cars etc., (2) upgrading the core network in order to provide advanced reliability features, such as path diversity, advanced optimization and healing.

Researchers affiliated to the project: Dr. Cedomir Stefanovic, Dr. Nuno Pratas, Prof. Petar Popovski.

How Many Smart Meters can be Deployed in a GSM cell?

The need to deploy large number of wireless devices, such as electricity or water meters, is becoming a key challenge for any utility. Furthermore, such a deployment should be functional for more than a decade. Many cellular operators consider LTE to be the single long-term solution for wide area connectivity serving all types of wireless traffic. GSM/GPRS is a well-adopted technology and represents a valuable asset to build M2M infrastructure due to the good coverage, device maturity, and low cost. We recently submitted a paper in which we assess the potential of GSM to operate as a dedicated network for M2M communications. In order to enable M2M-dedicated operation in the near future, we reengineer the GSM/GPRS/EDGE protocol in a way that requires only minor software updates of the protocol stack. We propose different schemes to boost the number of M2M devices in the system without affecting the network stability. We show that GSM a single cell can support simultaneous low-data rate connections (e. g. to smart meters) in the order of 10^4 devices.

Ideal system in which the bandwidth is shared among the multiplexed devices. The protocol operation is limiting the number of devices, despite the application requirements.
Ideal system in which the bandwidth is shared among the multiplexed devices. The protocol operation is limiting the number of devices, despite the application requirements.

Ideally, a TDMA system should be able to allocate as many as possible devices as long as the quality of service is guaranteed. However, in practice, systems are typically not able to operate in this manner. GSM and GPRS are an example of a TDMA system limited by the protocol rather than the application requirements of the smart meters. Specifically, for smart metering, a payload below 1000 bytes is expected. Moreover, the traffic patters corresponds to device originated with periodical reporting in the range of 5 mins, 15 mins, 1 hour and 6 hours. These devices tolerate a delay up to the next scheduled transmission opportunity if the message was not successfully delivered.

The main idea is that resources are pre-allocated according the application needs. In this manner, thousands of simultaneous connections can take place in a single cell (a single frequency is considered). In addition, we analyze the probability of reports exceed the deadline.  This probability is presented in the following figure, where it is noticeable that for the most demanding case when RI=1min, a single cell could provide service for up to 5 · 10^3 simultaneous connections with a reliability of 99.99%. This number rises to outstanding value of 5 · 10^4 simultaneous connections that are served with 99.99%, if the reporting interval is set to 15 min.

Probabilty report arriving after deadline as a function of report interval RI, report size 100 bytes.
Probability report arriving after deadline as a function of report interval RI, report size 100 bytes.

The paper has been submitted to ICC’13 (Second IEEE Workshop on Telecommunication Standards). Download

M2M @ IEEE Globecom 2012

M2M has been a notable topic in IEEE Globecom 2012, ranging from tutorials, industry fora and a dedicated workshop, featuring technical papers and a panel. Perhaps the most interesting discussions were circling around the question which of the wide area wireless technologies will prevail and transform itself into a dominant M2M solution.

2G (GSM/GPRS) is a very mature technology, long abandoned by the cutting-edge research in wireless communications, but the one that has won the trust of the end users due to its ubiquity, reliability, energy efficiency and low cost. Our groups will soon publish a paper where we show that GSM/GPRS, using only rather minor software updates of the protocol stack, can be converted into M2M-dedicated system, in which a single cell can support 10000 simultaneous low-data rate connections (e. g. to smart meters). But, although technologically possible, 2Gmay not survive as a dedicated M2M solution on a long run due to other factors. First, in many countries 2G is scheduled to be closed down and release the frequency. the plan is to refarm the spectrum for LTE. Second, even if 2G can keep the operating frequency, the operators will not be willing to maintain multiple technologies in their network, and in that case LTE is a clear winner.

But, if 2G can technologically support various M2M applications, perhaps it can re-emerge in another form. For example, operate on a single frequency, keeping a narrow band and being owned by a M2M service provider i. e. not necessarily by a company that is also a mobile LTE-based provider. A more radical thought could be to put 2G in a certain license-exempt spectrum and large M2M users (e. g. utilities) may have their own 2G cells; the license-exempt operation could be created in a way to facilitate interference management among 2G cells that have different owners and are in proximity where they can cause interference. How about porting 2G into a “cognitive M2M radio”, by re-engineering it through protocol (software) updates?

Another thing is the role of 3G. The M2M discussion is very often between 2G and 4G; however, Qualcomm presented their solution in which CDMA-based protocols are re-engineered to support different M2M requirements (latency, reduced access overhead, etc.). Considering the impact of Qualcomm, it is clear that 3G should also be considered in the M2M discussion.

Finally, an emerging technology in the M2M arena is the sub-GHz WiFi specified as IEEE 802.11ah, dedicated to sensor networks and smart metering, and scheduled for finalization in May 2015.

ETSI M2M Workshop 2012: Day 2 Sony Keynote Highlights

We would like to briefly summarize the keynote given by Sony Limited Europe about Low Cost LTE Devices. The objective of Sony regarding M2M is to integrate in most of their devices some sort of M2M communication technology in the near future. Moreover they want to use the same technology to cover all kind of devices from TVs, cameras, videogame consoles, etc. However this suppose a great challenge due to the wide range of requirements for each of the applications in terms of delay, power and data rates. The question made by the presenter was:

“Is there any technology that encompasses all the varying M2M requirements?”

Nowadays we have a large variety of wireless technologies that could be used such as, ZigBee WiFi, GPRS, LTE, etc.

According to Sony point of view the LTE should be the one. Without going into detail, the overall idea is to develop a LTE Low cost device (approx. 10$ per module) that could be easily integrated in most of the their products.  Sony is not alone in the field of Low cost LTE device, in fact there is a on-going study in 3GPP since September 2011.

How to decrease the cost of LTE?

The main approaches are:

  • Reduction of the bandwidth
  • Hardware simplification
  • Reduction of TX power
  • Reduction of the peak rate

A 59% of cost reduction is expected from these simplifications.

However, the chip development of such Low cost LTE will not take place in the short-term, but in the year 2017.

One of the questions made in regards to this presentation was about using GSM/GPRS technology, which is currently available. According to Sony point of view, GSM may disappear and therefore the longevity of the solutions cannot be guaranteed.

In another post we will try to cover the one million dollar question: which technology will be available ten years or more from the current cellular networks GSM/GPRS, 3G(UMTS) or LTE?

1st day at the ETSI M2M 2012 workshop impressions

The talks on the first day of the 3rd ETSI M2M workshop were interesting. Along the day there were four thematic speaker sessions. The program is available here.

The first thematic session was dedicated to the ETSI current standardization efforts, where the main highlights was the recently started initiative OneM2M partnership project (http://www.onem2m.org/), which the mission statement is:

“The purpose and goal of oneM2M is to develop technical specifications which address the need for a common M2M Service Layer that can be readily embedded within various hardware and software, and relied upon to connect the myriad of devices in the field with M2M application servers worldwide.”

The speaker and ETSI board member Joachim Koss emphasized that the current M2M ETSI standard will be an important part in the upcoming oneM2M standard. The first release of the oneM2M standard is expected to come within one year time.

The second thematic session was dedicated to the ETSI M2M standard and included talks from industry. The focus was put on the current ETSI M2M architecture, what are the contributions of ETSI for M2M security standards, how should the device abstraction and semantics be performed. From these talks, it was interesting to see how the classification of security threats is currently being done (Check the slides when they become available).

The third thematic session was dedicated to the experience that several companies had when implementing the ETSI M2M standard in their products. From this talk it was highlighted that when in M2M the term constrained device is mentioned, it means different things to different people and therefore a holistic characterization should be considered. There was also some discussion about if the gateways are still required when IP become native in all devices, where the conclusion that it is still required but not for protocol translation.

The fourth and last thematic session was dedicated to the M2M in the industry. The talks included the efforts to align the smart metering industry approach with standards requirements and national security demands. The talk about smart grid was focused on how to leverage security and privacy. Finally the last talk was about road traffic assistance and the challenges that need to be addressed in 3GPP networks to be able to meet the requirements. One interesting example of the road assistance is to inform the driver what should be their average speed so that they are able to get in the green wave (i.e., catch green semaphores in a long stretch of the road).

The organizers will release the slides to the public at the end of the event.

M2M traffic in cellular networks

Current cellular mobile networks are designed for human communication, and therefore are optimized for the traffic characteristics of human-based communication applications, i.e. communication with a certain session length, data volume, interaction frequency and patterns.

As the number of Machine-to-Machine (M2M) type devices increases so does the motivation to optimize existing cellular networks. While the features of the traffic generated by M2M devices are varied and application specific, the connected devices will be a mix of sensors and actuators. It is expected that a large majority will be sensors; therefore a bulk of the generated traffic will be in the uplink direction, i.e. from the M2M devices towards the network.

According to a recent market research study, in the next 10 years it is expected that the amount of M2M devices connections will reach 2.1 billion and that from these 61% will be due to the utilities market [1].

There are two interesting points about the characteristics of the traffic generated by this kind of application: The first is that the amount of data reported is generated sporadically and in small amounts, i.e. only a few bytes at a time; The second is that due to the expected density of the devices and the observed correlation between the reporting times [2], then the network will often observe a traffic pattern similar to a botnet, i.e. the traffic will arrive in batches. These two points will have an adverse effect on current cellular networks.

Currently, if one of these M2M devices wants to send a report to the network it will most likely use as carrier a SMS message. For this to happen, first the device needs to be connected to the network, which entails significant signaling overhead [3], then there is also the overhead associated to the transmission of a SMS message. Therefore, in the case of batch arrivals this will easily lead to the network to become overloaded due to signaling, while only transmitting a limited amount of data.

The network overload can occur at the radio access network, i.e. from a multitude of devices towards a base station, where in this case the base station gets overloaded, or globally where several base stations convey the traffic to a core network node. The ultimate consequence is the induction of signaling congestion and high computational load in the network.

In future blog posts we will describe what are the ongoing efforts to optimize the cellular networks to handle the characteristics of this particular type of M2M traffic.

[1] 2.1 billion M2M devices in 2021, http://www.analysysmason.com/About-Us/News/Press-releases1/M2M-forecast-2012-PR-Jun2012/

[2] M. Zubair Shafiq et al, “A First Look at Cellular Machine-to-Machine Traffic – Large Scale Measurement and Characterization” in Proceedings of the International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), London, United Kingdom, June 2012.

[3] Annex B.4 3GPP TR 37.868 V11.0.0