Smart Grid traffic model

For the study in our paper “What Can Wireless Cellular Technologies Do about the Upcoming Smart Metering Traffic?“, published September 2015 in the IEEE Communications Magazine, we derived a smart grid traffic model. This traffic model was based on the Open Smart Grid User Group specifications and some assumptions on system deployment parameters, as we described in the manuscript. Since there has been an interest in the derived model, we have decided to make it publicly available on our webpage.

The file can be downloaded here: traffic_model_shared.xlsx

With this, you can generate scenarios with different ratios of residential and industrial smart meters. For example, if you want to simulate a scenario with 80% residential and  20% industry, you should let 80% of your traffic generators use the traffic of the 40 flows in category 1 and 20% of the 40 flows in category 2. Also, you can scale the number of traffic generators for WAMS, which is category 3.

Please cite our magazine paper if you use the traffic model in any of your work.

Shannon’s capacity of a communication channel made simple

In 2016 we are marking 100 years since the birth of Claude E. Shannon, the man who in 1948 established the area of information theory, which is both a methodology and inspiration in various scientific and technological endeavors. One of his main contributions is the concept of a capacity of a communication channel. This is not the easiest concept around and the scientific literature has witnessed many instances of misunderstanding of the operational notion of channel capacity. This year I am teaching part of an introductory course in information theory and I tried to make a very simple example, with minimal mathematical content and intentionally not related to electronic communication in order to stress the (much) wider significance of Shannon’s theory.

Think of a pre-telecommunication era and of an emperor that wants to send a message to his general through messengers. Each messenger needs to use a horse to traverse the enemy territory in order to get to the general. However, there is a chance, denoted by p, that a messenger gets captured by the enemy. For example, let p=0.1 i.e. the chance of capturing the messenger is 10%. This statistical figure means that, if the emperor sends a large number of, say N=1,000,000 of messengers, then most probably only 90% of them will arrive to the general, or in absolute terms, most probably around 900,000 will traverse the enemy territory successfully. Which strategy should the emperor use to increase the probability that his messages will get through to the general, although any messenger can potentially be captured by the enemy?

Unlike many of today’s politicians, the emperor of our example is smart and does not want to write the message on a paper, since any of the captured messengers will reveal the whole message to the enemy. So, the emperor uses another strategy. Suppose that each messenger can remember a sequence of e.g. M=7 letters. The emperor wants each messenger to remember 7 letters of the message, such that the general can reconstruct the message from all messengers that manage to cross the enemy territory. We note that, in order to reconstruct the message, the general needs to put the letters of the messengers in the correct order. Therefore, each messenger also knows his ordinal number: the first group of 7 letters are from messenger #1, the second group of 7 letters are from messenger #2, etc. On the other hand, the enemy cannot reconstruct the message by capturing a single, or even several messengers – and since the message is not written on a paper, the captured messenger can always lie about the 7 letters that s/he was supposed to remember. It is noted that here we are not dealing with the problem of secure communication, i.e. protecting the data from being acquired by the enemy (although that was also formalized mathematically by C. E. Shannon in 1949). Instead, we are dealing with the problem of reliable communication, i.e. how to ensure that the general gets the message of the emperor with very high probability.

The trouble that the emperor has is that he does not know in advance which one of the messengers will be captured. However, he knows the law of large numbers: random fluctuations start to even out when one observes a large population of messengers. This is the same law that says that, if you roll a die 6,000 times, then most likely you will observe around 1,000 1s, around 1,000 2s, etc. The emperor knows that, if the chance that a messenger is captured is 10% and if he sends N=10,000 messengers, then around 9,000 will arrive to the general. Since each messenger carries 7 letters, the general will receive 7*9,000=63,000 letters from which he can try to reconstruct the message. However, we repeat here that the emperor does not know in advance which messengers will arrive to the general. Hence, the general should be able to reconstruct the message if the 9,000 messengers that are actually arriving are #1, #3, #6, #7, #8, #10, …, but he should be able to reconstruct the same message if the arriving messengers are #2, #3, #4, #7, #8, … or, in fact, any combination of 9,000 out of 10,000 messengers.

We now come to the main point. Shannon has proved that there exists a way for the emperor to encode 63,000 letters into a large number of 70,000 letters and tell 7 of those letters to each of the 10,000 messengers, such that if each messenger has a chance of 90% (or more) to pass through the enemy territory without being captured, then with very high probability, the general can reconstruct the original message of 63,000 letters.  Shannon did not provide a way to actually code the 63,000 letters into 70,000 letters, but made a mathematically powerful statement that a code with that capability must exist.

Finally, the capacity of a channel. If 63,000 letters arrive at the general after being coded and sent through 10,000 messengers, then the information transfer is 6.3 letters per messenger. In our example this is the capacity of the channel and stands for the maximal amount of information transfer per single carrier of information, i.e. messenger. If  10,000 messengers are used and the original message has 63,000 letters or less, then the general will reconstruct the message almost surely. On the other hand, communication above the channel capacity is unreliable: if the number of messengers is kept to 10,000, but the original message has more than 63,000 letters, then the general will almost certainly not be able to reconstruct the message.

At the first glance this is counterintuitive, as we tend to look at one messenger and think of him/her as an unreliable carrier of information. But Shannon showed that it is possible to send a message reliably by using many unreliable carriers of information, as long as the number of messages is lower than what is dictated by the channel capacity.

Information-theoretic purists may be horrified by the brutal lack of rigor in this example, but I hope it introduces the basic idea. And I think that the ingenious work of Shannon deserves to reach to a broader audience.

Special Session on Ultra-Reliable and Mission Critical Communication

We have organized a special session on Ultra-Reliable and Mission Critical Communications, together with Frank Schaich (Nokia), Berna Sayrac (Orange) and Salah Eddine Elayoubi (Orange). This special session was created within the context of the H2020-5GPPP project FANTASTIC-5G and it was held at the 2016 edition of the European Conference on Networks and Communications (EUCNC) in Athens, Greece.

We had four presentations, which covered four essential aspects of Ultra-Reliable and Mission Critical Communications. We would like to thank the presenters and attendees for the very interesting discussions, from which we could see that this topic is extremely relevant for both the industry and academy and will have an impact on 5G systems.

Petar and Nuno

These presentations where:

Presentation: Security on a 5G setting”, by Gerhard Wunder (FU-Berlin)

Abstract: MCC requirements such as high reliability, low latency etc. affect also security (and safety) procedures. In this talk we highlight some challenges of MCC from a 5G security perspective and discuss physical layer security (PHYSEC) as a potential remedy. To counter both passive eavesdropper and active radio hacking systems, that operate at the radio interface of wireless networks, to enable efficient, scalable key pre-distribution and authentication, and to enable much faster key establishment / authentication / attack detection procedures, PHYSEC has emerged as a promising approach, in complement of classical ciphering. PHYSEC strengthens the security of wireless communications by catching and exploiting the intrinsic randomness of the radio propagation, which avoids the use of pre-shared keys and guarantees full secrecy independently of the adverse computing capabilities. In this context we discuss several interesting new “fast” security procedures on radio level such as secret key generation “on the fly”, secrecy coding, secure pairing, etc.

Presentation: “Ultra-Reliable and Low-Latency 5G Communication”, Osman Yilmaz ( Ericsson), Manuscript

Abstract: Machine-to-machine communication, M2M, will make up a large portion of the new types of services and use cases that the fifth generation (5G) systems will address. On the one hand, 5G will connect a large number of low-cost and low-energy devices in the context of the Internet of things; on the other hand it will enable critical machine type communication use cases, such as smart factory, automotive, energy, and e-health – which require communication with very high reliability and availability, as well as very low end-to-end latency. In this paper, we will discuss the requirements, enablers and challenges to support these emerging mission-critical 5G use cases.

Presentation: “Code Design for Short Blocks: A Survey”, Gianluigi Liva (DLR), Manuscript

Abstract: “The design of block codes for short information blocks (e.g., a thousand or less information bits) is an open research problem which is gaining relevance thanks to emerging applications in wireless communication networks. In this work, we review some of the most recent code constructions targeting the short block regime, and we compare then with both finite length performance bounds and classical error correction coding schemes. We will see how it is possible to effectively approach the theoretical bounds, with different performance vs. decoding complexity trade-offs.”

Presentation: “Achieving low-latency communication in future wireless networks: the 5G NORMA approach”, Alessandro Colazzo (AZCOM), Manuscript

Abstract: “The end-to-end network latency is generally considered by the 5G community a key requirement for future wireless networks, enabling new applications by means of end-to-end figures up to a few ms, which is a target that cannot be achieved by the current 4G technology. 5G Novel Radio Multiservice adaptive network Architecture (5G NORMA) project aims at providing a new network architecture design able to cope with the diverse and stringent 5G KPIs, including network latency. This paper describes the low latency issue from a network architecture perspective, starting from the 3GPP state-of-the-art and then describing the 5G NORMA novelties.”

Workshop “Communication theory for 5G wireless systems”

Recently we hosted the workshop “Communication theory for 5G wireless systems”. The aim of the workshop was to present some novel research approaches and trends related to the challenges of 5G.
The list of speakers and their presentations can be find at this link:


We extend a sincere thanks to the guest speakers and all who attended the event!



Two awards received in IEEE ICC

Yesterday, in the 2016 IEEE International Conference on Communications (ICC) in Kuala Lumpur, Prof. Petar Popovski from our group received the best paper award of IEEE Communications Magazine, as a co-author of the paper: “Five disruptive technology directions for 5G”.

Also, during the conference, Prof. Petar Popovski has been officially awarded with the IEEE fellowship, as a recognition of his many contributions to the research community.


Invited talk at FABULOUS conference in Ohrid

Two weeks I attended the FABULOUS conference in Ohrid, Macedonia, where I gave an invited talk with the title “How Suitable are Cellular Networks for Connecting Future Electricity Smart Meters?”. In this talk I presented the main findings of our just published paper that appeared in the IEEE Communications Magazine in the September 2015 issue. The conference featured several high-quality keynotes in different areas that gave food for thought in the areas that I am already familiar with and provided insights into the concepts and challenges in other areas such as DataFlow supercomputing. Despite the slightly challenging travel to Ohrid, it was an interesting conference location due to the beautiful nature, excellent food, and interesting old town that is considered to be the cradle of literacy.

Wireless M-Bus: Part 1, an overview

When one hears: Smart Meter, the picture that immediately comes to mind is an electricity meter which can measure the energy consumption of a household, where there optionally are installed PVs at the roof. Somewhere between electricity meters, and sensors (in the broad term) in a sensor network, we have a device that is typically overseen in the smart metering context: a Water Meter. One of the reasons why we do not see these devices as anything even close to smart is because they, in general, are not “smart”.

In the recent years, things have changed a lot though. The meters are being extended with wireless capabilities, either in the form of a module attached directly on top of a plain old meter, “reading” the display and relay its values, or inherently build into the meter itself, as for the Kamstrup Multical 21. Also larger cities are buying into this type of technology. This mainly to cut labor cost, but also for the more advanced meters, to get more fine grained insight into the installation state with leak alarms, etc. One example is New York City [1].


But what language do these devices speak? At least in EU, the answer is: Wireless M-Bus, a wireless extension of the original M-Bus protocol developed back in the nineties. Wireless M-Bus is specifically designed for battery powered meters. This is seen in the lifetime for these devices: The Multical 21 for example guarantees 16 years, with a broadcast transmission every 16 seconds [2]. That is a total of 1.973.062 transmissions – impressive. No matter how low-power Bluetooth, LTE, Zig-Bee, or any other more general protocol ever becomes, they will hardly be able to beat these numbers. The protocol is not specifically designed for water meters, and other (mainly battery powered) product types within metering also uses the protocol, for example gas meters, or even district heating meters.

Wireless M-Bus is a three-layered protocol: PHL, DLL and APL, and these layers will be analyzed separately in future posts, so stay tuned.