MobileNET is a Marie Curie Career Integration Grant funded by the European Union under the 7th Framework Programme. It addresses challenges that need to be overcome in order to build an efficient mobile Internet.

Wireless communication systems have experienced a formidable growth in the past 15 years, with the number of mobile subscriptions having reached about 5.6 billion by the end of 2011. It is expected that, very soon, the Internet will not only connect billions of mobile device users, but also objects such as household appliances or components of transportation vehicles, building a genuine “Internet of Things.” This places high demands on the communications infrastructure and on the mobile devices. Specifically, future networks should support heterogeneous mobile, wired, and wireless network technologies; be dynamic, self-organizing, and robust; and at the same time offer high data rates and use resources, such as bandwidth and energy, in the most efficient way. Future mobile devices should be small and have low energy-consumption while offering high functionality.

To meet future demands on wireless communication systems, network equipment operators predict that network throughput will have to increase 70-100 times in the next 8 years. Unfortunately, current wireless network technology is not able to deliver the throughput gains that will be required soon. Indeed, most of today’s communication networks are built based on the paradigm of first creating reliable point-to-point links between the nodes (using channel-access methods such as time-division, frequency-division, or code-division multiple-access) and then using these links to distribute data. This approach has major weaknesses and may even be infeasible since the interference experienced in wireless communications is typically strong, so creating interference-free links requires a considerable amount of resources. Furthermore, this approach does not exploit possible cooperation between the users, which could potentially increase the throughput significantly.

To explore how to use the resources in wireless networks in a more efficient way, this project will study such networks from an information-theoretic perspective. Since the landmark work by Shannon, information theory has guided engineers and computer scientists in the design and implementation of ever more efficient communication systems by providing fundamental limits of such systems, and by suggesting communication strategies that attain these limits. For example, it is known that for every communication channel there exists a fundamental limit on the data rates, named channel capacity, below which data can be transmitted with arbitrarily small decoding error probability, provided that we encode them with sufficiently long codewords. Fundamental limits of communication networks have been studied extensively in the past. Inter alia, it has been demonstrated that cooperation between the nodes in wireless networks can increase the channel capacity substantially, thus promising large throughput gains if we manage to establish cooperation between nodes rather than treating the network as a collection of point-to-point links. However, the majority of this work is based on simplifying assumptions, such as that the nodes are perfectly synchronized or have perfect knowledge of the channel propagation characteristics (an assumption usually referred to as perfect CSI). Since perfect synchronization and CSI are difficult to establish in decentralized wireless networks, these assumptions may disagree with the requirement of the network to be dynamic, self-organizing, and robust. Furthermore, these fundamental limits are commonly derived using techniques from large deviations theory and are therefore only significant if one allows for very long codewords. This assumption is particularly unrealistic in wireless systems where short codeword lengths are required – even more so in dynamic wireless networks where each node may communicate only for a short period of time.

MobileNET derives realistic fundamental limits by including asynchronism, noncoherence, and latency constraints in its analysis. Based on these limits, it will then propose communication strategies that attain these limits. A related topic addressed in MobileNET is the design of mobile devices. Using tools from information theory, MobileNET will study the fundamental tradeoff between performance, robustness against nonlinearities in the devices, and implementation complexity, aiming at novel encoding and decoding algorithms that can be implemented efficiently in hardware.