There is an old joke, circulating around the Balkans, about a lawyer and a tree. The main case of the lawyer was the dispute between two neighbors about a tree placed at the common border of their properties. The case was going on for decades, the lawyer was mediating, but no solution came and eventually, the lawyer retired and his son took his office. A couple of days later the son came to his father and said “I have solved the problem – I have cut the tree down.” Then the father said “That tree was feeding our family for decades, now you need to find something else to do.”

This technology-agnostic joke has a lot to do with researchers working with technology. Being very successful in creating a certain technology (call it X) also means that the perception of the general public, as well as the research funding agencies, leans towards “there is not much to do about that X in terms of research, it works already.” The most extreme example of this is the widely-feared singularity moment of artificial intelligence, after which the humans get a secondary role and the artificial intelligence decides what to do with them (including whether it will keep funding agencies to support research by humans).

Taking several steps back from the gloomy singularity predictions, we can look at the state of research in communication engineering. Communication technology, and specifically wireless communication, is arguably one of the fastest growing technologies in history. In just two decades, wireless connection achieved the status of a commodity. In 2016 the World Bank published its report [1], where it is shown that in the developing countries more people have a mobile phone rather than reliable access to other commodities, such as water or electricity. And the R&D party of communication technologies is still going on. Research and standardization of 5G is in full steam, supported with large and competitive research programs by, for example, the European Commission [2]. The Internet of Things is seen as the post-smartphone business ecosystem for all stakeholders that are involved with communication-related products and services. Some more bold views [3] state that the Internet of Things will bring an end to the capitalism as we know it, by facilitating zero marginal costs for products and services. Regardless of how profound the consequences of the Internet of Things will be, we are moving to an age where everything that can be connected, will become connected. But what then, do we still need a research in communication engineering, say ten years from now? Or we just need to have engineers to maintain the systems? Will the exciting things happen only in areas that assume that connectivity is already there?

This is not only a speculative question, as there are clear signs that the communication engineering, and especially research in communication engineering, is losing its traction and gives way to other engineering disciplines, such as e.g. machine learning. I have not documented a statistically correct study to confirm these statements, but being an academic in communication engineering, I have talked in the past years to hundreds of my peers and concluded that we share the same observation. And the observation is that the number of students and Ph.D. students in communication engineering is seriously declining. The Deans are not hiring as many communication-focused faculty members. The role and popularity of communication-related courses in the curricula is rather modest compared to ten years ago. The research funding for the pure subject matter of communication engineering is declining. The latter has motivated (forced?) many academics to migrate to other areas that deal with probability and statistics and/or window-dress their communication engineering ideas with popular spices (big data, smart <something>, machine learning, etc.) in order to increase the chances of getting research funding. To avoid any misunderstanding - this is quite fine, part of the natural evolution of curious minds and broadening of the research horizons.

Yet, I still think that there are important research tracks that have the potential to produce new fundamental results in communication theory over a longer term. Furthermore, the rich methodology of communication theory can be purposefully used to achieve novel system design and optimization within other disciplines. Sure, there will be still the standard research track in communication theory in terms of improving transmitters and receivers, optimize the latency, or increase the rate. But what I am after are the tracks that have the potential to drive a new and exciting research in communication theory over a longer period. Having no ambition to be comprehensive, I have picked three such tracks. None of them is new, as a diligent reader can immediately find the “this has already been done” references, but I have selected them due to their potential.

Communication Under Adversarial Impact

A majority of the works in communication theory have been dedicated to optimize the systems with respect to the physical constraints, i.e. the “nature,” such as noise, unintended interference, etc. The communication theory community has paid much less attention to security and optimization of communication systems against impact of adversaries. In 1949, Shannon (yes, the same Claude E. Shannon) published a fundamental paper on the topic of security [4], but this one has received less attention from communication theorists compared to his 1948 paper [5], the holy script of information and communication theory. At the time of writing this, Shannon’s security paper has ten times less citations compared to his 1948 paper. On the other hand, the main problems related to communication today in the coming years, will be likely related to security. Cybersecurity can impact elections, economic outcomes, and war conflicts. The growing importance of bitcoin and other cryptocurrencies is heavily relying on a reliable communication infrastructure. There is a significant potential for communication theorists to build models and address the fundamental problems in cybersecurity, ranging from how to deal with fake news and up to protecting the communication infrastructure for smooth transactions of bitcoin and other cryptocurrencies. The advances in communication with respect to the impairments that come from the “nature” will happen at a much slower pace compared to the advances that need to happen in the race with the “bad guys.” In other words, when dealing with adversarial impact instead of dealing only with physical limits, it is much more difficult, if at all possible, to reach a saturation point for research, since the adversary is doing his/her research as well. This is why this area has a long-term perspective for research in communication engineering and this opportunity should be seized. Here I am not speaking about “physical layer security”-like research, which is fine by itself, but very much similar to the traditional problems in communication and information theory. I am instead referring to pursuing new models and theories that can capture the large-scale cybersecurity problems.

Interaction Among Vertical Services

Communication and networking technologies are based on the layering paradigm. The layers can be thought of as a hierarchical tower of bricks, with the brick underneath representing a module that providing a certain service for the brick (module) above it, see Figure 1(a). An end-to-end connection is built by creating a vertical pipe that goes vertically through all the layers (bricks) and each layer needs to be configured in a way that supports the specific requirements of that connection in terms e.g. rate, latency, etc.