One example is the number of mobile phone users that grows with hundreds of million people every year (!), of which many people did not previously have access to telephony. The traffic generated by existing devices also increases by 30-40 percent annually. The Internet traffic shows a similar, impressive growth rate. The wireless communication technology is very important nationally, both for the export industry and the infrastructure sector, since Sweden has world-leading companies and research groups in the telecom field. Communication systems are also a vital component of various complex systems, for example, in aviation and in the military.
In parallel, new application areas are emerging. One example is wireless sensor networks, consisting of many small sensors that communicate wirelessly and report measurements or audio/video recordings of different kinds. Sensor networks have applications in security, surveillance, environmental monitoring, health care, and factories. The process industry is interested in replacing cables on moving equipment (e.g., robots) with wireless links. Autonomous vehicles and drones must communicate with their surroundings to avoid collisions and other incidents. Many of these applications have extreme requirements on reliability and latency.
Given the advanced systems that already exist, why do we need further research in the field?
Although the current communication systems are rather well-functioning, the increasing use of the technology and the new applications call for a continuous development. New technology generations are released once per decade and gradual improvements are introduced in between generations.
All systems for information transfer are fundamentally limited by the laws of physics. There are two main factors that limit the service quality that a communication system can achieve. These are the amount of available frequency spectrum and the amount of power at the transmitter and receiver. Broadly speaking, the research in communications determines new ways to utilize these fundamental resources in the best way and push the limits of what is practically possible.
Another important aspect is availability. For instance, mobile networks typically provide a coverage of 99%; that is, there is a 1% risk that a phone call is disconnected. This typically occurs at the same time or place every day. If we want to increase the availability to 99.9% using conventional technology, then disproportionally large investments are required; for example, 10 times more base stations need to be deployed. New technology can, however, increase the availability without increasing the cost. Robust communication is particularly important for critical communication links, required by the police, emergency services, military, and aviation industry. As the society becomes more dependent on wireless technology, people will expect the mobile networks to be continuously available, in the same way as they expect the electrical grid to be extremely reliable.
Time-critical communication, such as real-time video transfer or control over networks, has its own challenges. One issue is that the quality of a communication channel often fluctuates over time, especially in wireless communications. This leads to natural delays when we need to wait for the channel to be sufficiently good before a transmission is possible. Another problem arises when many users are using the same system. Since the available spectrum is limited, not every user can get a dedicated channel when needed. The systems are dimensioned so that the risk that it is overloaded at a particular moment is small. In many everyday applications, a delay of one second is unnoticeable, but there are special applications where the delays must be smaller than a millisecond. It is incredibly important to utilize the spectrum efficiently, both to deliver high data rates and limit delays.
Spectrum, why is that such a limited resource?
The main issue is that the part of the electromagnetic frequency band that is best suited for wireless communications is rather small (around 0-6 GHz). The spectrum is thus a fundamentally limited resource. Traditionally, the resources are divided into licensed and unlicensed spectrum. In licensed spectrum, an operator has an exclusive license to transmit and can therefore plan and optimize its network. Mobile networks, such as 3G and LTE, mainly utilize licensed spectrum. The licenses are very expensive, as can be seen from recent spectrum auctions in Europe or USA. This creates a very high barrier for new operators to enter the market.
On the other hand, in unlicensed spectrum, anyone can send without having a license. However, we need to comply with certain regulations on the transmit power and behavior, since otherwise, we will disturb other systems. The main problem with the unlicensed bands is that they are typically filled with interference from neighboring systems. WiFi for local area networks is an example of a system that utilizes unlicensed spectrum. The interference issue can be easily observed: if we deploy too many WiFi networks in an area, they will all stop functioning.
What are the trends and the potentials for improvements?
The current trend is Massive MIMO, where the base stations are equipped with hundreds of antennas that collaborate phase-coherently. The Massive MIMO technology makes sure that the electromagnetic waves from the base station antennas add constructively at the location of the desired receiver while this does not happen at other locations. An analogy is that a conventional base station is like a light bulb that illuminates in all directions, while the Massive MIMO technology sends out laser-like beams towards the desired receivers. This enables very energy-efficient data transfer. With Massive MIMO technology, one can also transmit and receive data from tens of users in parallel, which leads to a ten-fold increase in data rates in the network.
Which problems do you work with?
One key issue is that all communication electronics are limited by the energy consumption. The battery life is one important limitation, but the network operators are also keen on reducing their energy bills. In advanced systems, a lot of energy is consumed by signal processing, which includes the transformation of digital data, or the human voice, into waves that can be transmitted by an antenna (and vice versa).
New applications, such as Massive MIMO and advanced industrial use cases, will require even more signal processing than today. At the same time, the customers have growing demands on mobility and battery life. This calls for new energy-efficient and flexible processing hardware and algorithms that can fully utilize such hardware. In principle, each algorithm should quickly and energy-efficiently compute the answer to a complicated mathematic formula. Paradoxically, it is often easy to determine which is "optimal" under ideal conditions, while it is very challenging to take practical conditions and implementation constraints into account.
In our research, we have developed practical signal processing solutions for Massive MIMO, which have been internationally acclaimed and awarded. We are now using these solutions as the foundation to maximize the data rates in future networks, to achieve higher energy efficiency, and to develop tailored solutions to the new application areas mentioned above.
In the Shanghai Ranking's of universities 2017, Linköping University was ranked as 32 in the world in the Telecommunication engineering field and was ranked as number 5 in Europe.
Which theoretical tools are used in communication research?
Communications is an interdisciplinary research field and we use many different tools, particularly advanced mathematics and computer simulations. When it comes to designing transmitters and receivers, we use advanced physical models and mathematical analysis. Probability theory is, for example, an important component when modeling noise and other random behaviors. Images and videos that are sent of a communication link are often modeled as structured but random data.
When it comes to utilizing the spectrum efficiently, there are often resource conflicts. An example is when two networks compete for the same unlicensed spectrum. A tool that is useful to model and analyze such conflicts is game theory, which is a mathematical framework that is also used for research in economy. Another example is a mobile network with licensed spectrum that needs to serve thousands of simultaneous users in a city. Optimization theory can then be useful to identify solutions where all the users have their data rate requirements satisfied simultaneously.
Apart from wireless communications, what research are you conducting?
Another important area is large, complex networks. There are networks around us at many different levels. Examples include social networks, transportation networks, Internet, and networks of genes and proteins in living organisms. The study of such networks has shown similarities in their structure and the way they evolve over time. The fact that data from such networks is becoming easily accessible has contributed to the formation of the new research field of network science.
As this type of networks grow faster and faster and appear in new parts of the society, network science is a research field that will play a key role in making our complex society work in the future.
How is the labor market for engineers that have graduated in communication systems?
Those that study communication technology at the Master level can look forward to a vibrant labor market that grows both globally, nationally, and locally in Östergötland. Some engineers are employed by the major companies (e.g., Ericsson, Saab), but many students are recruited by smaller companies that have found their own niche (e.g., Attentec, Autoliv, Cinside, Combitech, WISI, Zenuity). All electronic devices will eventually be wirelessly connected and to achieve this goal, communication engineers are becoming important also for industries that traditionally have lacked such competence.