Localization in Long-range Ultra Narrow Band IoT Networks using RSSI

Internet of things wireless networking with long range, low power and low throughput is raising as a new paradigm enabling to connect trillions of devices efficiently. In such networks with low power and bandwidth devices, localization becomes more challenging. In this work we take a closer look at the underlying aspects of received signal strength indicator (RSSI) based localization in UNB long-range IoT networks such as Sigfox. Firstly, the RSSI has been used for fingerprinting localization where RSSI measurements of GPS anchor nodes have been used as landmarks to classify other nodes into one of the GPS nodes classes. Through measurements we show that a location classification accuracy of 100% is achieved when the classes of nodes are isolated. When classes are approaching each other, our measurements show that we can still achieve an accuracy of 85%. Furthermore, when the density of the GPS nodes is increasing, we can rely on peer-to-peer triangulation and thus improve the possibility of localizing nodes with an error less than 20m from 20% to more than 60% of the nodes in our measurement scenario. 90% of the nodes is localized with an error of less than 50m in our experiment with non-optimized anchor node locations.Comment: Accepted in ICC 17. To be presented in IEEE International Conference on Communications (ICC), Paris, France, 201

Ultra Reliable UAV Communication Using Altitude and Cooperation Diversity

The use of unmanned aerial vehicles (UAVs) that serve as aerial base stations is expected to become predominant in the next decade. However, in order for this technology to unfold its full potential it is necessary to develop a fundamental understanding of the distinctive features of air-to-ground (A2G) links. As a contribution in this direction, this paper proposes a generic framework for the analysis and optimization of the A2G systems. In contrast to the existing literature, this framework incorporates both height-dependent path loss exponent and small-scale fading, and unifies a widely used ground-to-ground channel model with that of A2G for analysis of large-scale wireless networks. We derive analytical expressions for the optimal UAV height that minimizes the outage probability of a given A2G link. Moreover, our framework allows us to derive a height-dependent closed-form expression and a tight lower bound for the outage probability of an \textit{A2G cooperative communication} network. Our results suggest that the optimal location of the UAVs with respect to the ground nodes does not change by the inclusion of ground relays. This enables interesting insights in the deployment of future A2G networks, as the system reliability could be adjusted dynamically by adding relaying nodes without requiring changes in the position of the corresponding UAVs

6G Wireless Communications in 7-24 GHz Band: Opportunities, Techniques, and Challenges

The sixth generation (6G) wireless communication nowadays is seeking a new spectrum to inherit the pros and discard the cons of sub-6 GHz, millimeter-wave (mmWave), and sub-terahertz (THz) bands. To this end, an upper mid-band, Frequency Range (FR) spanning from 7 GHz to 24 GHz, also known as FR3, has emerged as a focal point in 6G communications. Thus, as an inexorable prerequisite, a comprehensive investigation encompassing spectrum utilization and channel modeling is the first step to exploit potential applications and future prospects of using this FR in the 6G ecosystem. In this article, we provide FR3 deployment insights into emerging technologies including non-terrestrial network (NTN), massive multi-input multi-output (mMIMO), reconfigurable intelligent surface (RIS), and joint communications and sensing (JCAS). Furthermore, leveraging ray-tracing simulations, our investigation unveils the channel characteristics in FR3 are close to those in the sub-6 GHz band. The analysis of RIS-aided communication shows a higher spectral efficiency achieved in FR3 compared to other FRs when using the same RIS size. Finally, challenges and promising directions are discussed for FR3-based communication systems.Comment: 7 pages, 5 figures, 1 tabl

Understanding interdependency through complex information sharing

The interactions between three or more random variables are often nontrivial, poorly understood, and yet, are paramount for future advances in fields such as network information theory, neuroscience, genetics and many others. In this work, we propose to analyze these interactions as different modes of information sharing. Towards this end, we introduce a novel axiomatic framework for decomposing the joint entropy, which characterizes the various ways in which random variables can share information. The key contribution of our framework is to distinguish between interdependencies where the information is shared redundantly, and synergistic interdependencies where the sharing structure exists in the whole but not between the parts. We show that our axioms determine unique formulas for all the terms of the proposed decomposition for a number of cases of interest. Moreover, we show how these results can be applied to several network information theory problems, providing a more intuitive understanding of their fundamental limits.Comment: 39 pages, 4 figure