Techniques for Wireless Channel Modeling in Harsh Environments

With the rapid growth in the networked environments for different industrial, scientific and defense applications, there is a vital need to assure the user or application a certain level of Quality of Service (QoS). Environments like the industrial environment are particularly harsh with interference from metal structures (as found in the manufacturing sector), interference generated during wireless propagation, and multipath fading of the radio frequency (RF) signal all invite novel mitigation techniques. The challenge of achieving the benefits like improved energy efficiency using wireless is closely coupled with maintaining network QoS requirements. Assessment and management of QoS needs to occur, allowing the network to adapt to changes in the RF, information, and operational environments. The capacity to adapt is paramount to maintaining the required operational performance (throughput, latency, reliability and security). This thesis address the need for accurate radio channel modeling techniques to improve the performance of the wireless communication systems. Multiple different channel modeling techniques are considered including statistical models, ray tracing techniques, finite time-difference technique, transmission line matrix method (TLM), and stochastic differential equation-based (SDE) dynamic channel models. Measurement of ambient RF is performed at several harsh industrial environments to demonstrate the existence of uncertainty in channel behavior. Comparison of various techniques is performed with metrics including accuracy, applicability, and computational efficiency. SDE- and TLM-based methods are validated using indoor and outdoor measurements. Fast, accurate techniques for modeling multipath fading in harsh environments is explored. Application of dynamic channel models is explored for improving QoS of wireless communication system. The TLM-based models provide accurate site-specific path loss calculations taking into consideration materials and propagation characteristics of propagating environment. The validation studies confirm the technique is comparable with existing channel models. The TLM-based channel models is extended to compute the site-specific multipath characteristics of the radio channel eliminating the need for experimental measurement. The TLM-based simulator is also integrated with packet-level network simulator to perform end to end-to-end site specific calculation of wireless network performance. The SDE-channel models provide accurate online estimations of the channel performance along with accurate one-step prediction of the signal strength. The validation studies confirm the accuracy of the technique. Application of the SDE-based models for adaptive antenna control is formulated using online recursive estimation

Joint-rollout of FTTH and smart city fiber networks as a way to reduce rollout cost

Making cities smarter is the future. By bringing more technology into existing city infrastructure, smart city applications can arise. Whether these applications track devices e.g. public lightning, environmental measurements e.g. temperature or air quality, or analyze video streams e.g. for people density, it is expected that these will require a (near-) real time data connection. Upcoming 5G networks will be able to handle large amounts of connections at high speeds and low latencies and will therefor outperform current technologies such as 4G and low-power wide-area networks. In order to do so, these 5G networks fall back to numerous fiber connected small cells for up & downlink to the Internet. In this publication, we are looking into the additional fiber equipment and deployment cost to connect the required smart city network infrastructure, taking into account a Fiber-to-the-Home (FTTH) network is already available or will be installed as part of the smart city network rollout. More concretely, we are proposing a methodology comparing an anticipated and incremental planning approach for a number of different extensions upon the FTTH-network: connecting all electrical cabinets, connecting public lightning, and the connection of 5G using small cells. From this, we want to learn how much the total rollout cost can be reduced using a future-oriented smart city approach taking into account all future extensions, compared to an incremental short-time planning only planning additional fiber when required. In the meantime, we want to show the additional cost of creating a smart city network is limited when it is being combined with a FTTH rollout. Results of the proposed methodology and use case will be modeled planning and design software Comsof Fiber and will be published in a future work

A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G

Sixth-generation (6G) mobile communication networks are expected to have dense infrastructures, large-dimensional channels, cost-effective hardware, diversified positioning methods, and enhanced intelligence. Such trends bring both new challenges and opportunities for the practical design of 6G. On one hand, acquiring channel state information (CSI) in real time for all wireless links becomes quite challenging in 6G. On the other hand, there would be numerous data sources in 6G containing high-quality location-tagged channel data, making it possible to better learn the local wireless environment. By exploiting such new opportunities and for tackling the CSI acquisition challenge, there is a promising paradigm shift from the conventional environment-unaware communications to the new environment-aware communications based on the novel approach of channel knowledge map (CKM). This article aims to provide a comprehensive tutorial overview on environment-aware communications enabled by CKM to fully harness its benefits for 6G. First, the basic concept of CKM is presented, and a comparison of CKM with various existing channel inference techniques is discussed. Next, the main techniques for CKM construction are discussed, including both the model-free and model-assisted approaches. Furthermore, a general framework is presented for the utilization of CKM to achieve environment-aware communications, followed by some typical CKM-aided communication scenarios. Finally, important open problems in CKM research are highlighted and potential solutions are discussed to inspire future work