2019 European Future of Wireless
The conference will be carried out in an interactive format and organized in themes in which invited speakers present their ideas of future technologies or solutions for wireless networks followed by a Q&A session. Huawei speakers will present 2019 challenges and trends. All participants will have the opportunity to ask questions and participate in the discussions.
Creating trustworthy software for trustworthy products requires a theoretical foundation for trustworthiness. With that a framework can be formulated and evaluated. Ensuring nonfunctional properties of the product builds trust. The wireless domain has a lot of performance requirements that needs to be fulfilled for customers to trust the product.
Defining quality requirements and ensuring requirement fulfilment builds trust by showing that the product does precisely what it is meant to do.
The trustworthiness of the product can be tested and statically analyzed.
Incorporating already trusted components like open source can be used as a strategy to build trust.
OPEX cost savings and CO2 reduction are becoming major objectives for operators. To maintain a competitive edge, low energy consumption may become a key differentiator. Increased network complexity is both a risk as well as an opportunity for energy saving. Energy Efficiency and related functionalities will typically need to be distributed across management-, RAN- and BTS domains, thereby impacting network architecture as well as hardware realizations of various nodes.
Network energy consumption scales badly with traffic today; improved scalability and modularity are key for reduction, both at network and equipment level. This is especially important for the introduction of 5G that by careful design can take advantage of improved sleep modes. In this block we will address energy saving features – primarily employing machine learning techniques – to gain RAN level energy savings.
Machine learning (ML) is gaining increasing attention in wireless communications with applications spanning over the different network layers. Recently, ML has demonstrated great potential in physical layer applications mainly due to the emerging challenges that the signal processing algorithms face from the complex environments and scenarios, as well as due to the fact that these algorithms have solid foundations in statistics and information theory. Thus, the potential application of ML to physical layer has been increasingly recognized as leverage to redesign modules of the conventional communication systems.
The evolution of RF Technologies for higher bandwidths and higher frequencies are playing an essential role in wireless communication networks. Various key RF technologies including advanced power amplifier architectures, micromachining techniques for terahertz communication systems, and passive and active beam-steerable millimeter-wave phased-array solutions, will be addressed. The topics are expected to provide great technical value to 5G radio base stations at both sub 6 GHz and millimeter-wave frequencies.