Localization and sensing inputs are enabling new and improved Internet of Things (IoT) applications and have been studied extensively over the past decade. Unfortunately, many solutions focus primarily on improving localization performance, which in turn reduces communication capabilities. Driven by the Integrated Sensing and Communication (ISAC) aspects, we investigate how localization functionality can be seamlessly integrated into a IEEE 802.15.4 TSCH communication protocol. We present two new methods of phase-based ranging that estimate the distance between two devices with each transmitted data packet. We further analyze the effects of introduced changes on communication, their power consumption, and ranging operability. We improve the state-of-the-art algorithm of phase-based distance estimation by reducing the number of phase samples required, without reducing its accuracy and sensitivity while increasing the energy efficiency.

Accurate localization of devices within Internet of Things (IoT) networks is driven by the emergence of novel applications that require context awareness to improve operational efficiency, resource management, automation, and safety in industry and smart cities. With the Integrated Localization and Communication (ILAC) functionality, IoT devices can simultaneously exchange data and determine their position in space, resulting in maximized resource utilization with reduced deployment and operational costs. Localization capability in challenging scenarios, including harsh environments with complex geometry and obstacles, can be provided with robust, reliable, and energy-efficient communication protocols able to combat impairments caused by interference and multipath, such as the IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol. This paper presents an enhancement of the TSCH protocol that integrates localization functionality along with communication, improving the protocol’s operational capabilities and setting a baseline for monitoring, automation, and interaction within IoT setups in physical environments. A novel approach is proposed to incorporate a hybrid localization by integrating Direction of Arrival (DoA) estimation and Multi-Carrier Phase Difference (MCPD) ranging methods for providing DoA and distance estimates with each transmitted packet. With the proposed enhancement, a single node can determine the location of its neighboring nodes without significantly affecting the reliability of communication and the efficiency of the network. The feasibility and effectiveness of the proposed approach are validated in a real scenario in an office building using low-cost proprietary devices, and the software incorporating the solution is provided. The experimental evaluation results show that a node positioned in the center of the room successfully estimates both the DoA and the distance to each neighboring node. The proposed hybrid localization algorithm demonstrates an accuracy of a few tens of centimeters in a two-dimensional space.

The LOG-a-TEC testbed is a combined outdoor and indoor heterogeneous wireless testbed for experimentation with sensor networks and machine-type communications, which is included within the Fed4FIRE+ federation. It supports continuous deployment principles; however, it is missing an option to monitor and control the experiment in real-time, which is required for experiment execution under comparable conditions. The paper describes the implementation of the experiment control and monitoring system (EC and MS) as the upgrade of the LOG-a-TEC testbed. EC and MS is implemented within existing infrastructure management and built systems as a new service. The EC and MS is accessible as a new tab in sensor management system portal. It supports several commands, including start, stop and restart application, exit the experiment, flash or reset the target device, and displays the real-time status of the experiment application. When nodes apply Contiki-NG as their operating system, the Contiki-NG shell tool is accessible with the help of the newly developed tool, giving further experiment execution control capabilities to the user. By using the ZeroMQ concurrency framework as a message exchange system, information can be asynchronously sent to one or many devices at the same time, providing a real-time data exchange mechanism. The proposed upgrade does not disrupt any continuous deployment functionality and enables remote control and monitoring of the experiment. To evaluate the EC and MS functionality, two experiments were conducted: the first demonstrated the Bluetooth Low Energy (BLE) localization, while the second analysed interference avoidance in the 6TiSCH (IPv6 over the TSCH mode of IEEE 802.15.4e) wireless technology for the industrial Internet of Things (IIoT).

Direction-of-arrival (DoA) estimation in the Internet of Things (IoT) and embedded devices is typically performed using single-RF chain systems and antenna switching using time-division multiplexing. The accuracy of the DoA estimation is reduced due to the additional phase shifts between the samples on the antenna elements caused by the carrier frequency offset (CFO). We propose to use optimized antenna switching patterns (ASPs) to mitigate the effect of CFO on accuracy in DoA estimation using a multiple signal classification (MUSIC) algorithm. We evaluated two switching methods referred to as EvenCFO-SP and Mirror-SP with simulations and confirmed the validity with measurements. Performance is analyzed and compared with a standard sequential sampling (SS) method. Uniform linear and circular array configurations are considered to evaluate the impact of the noise and the CFO value on estimation accuracy. The results show that the optimized ASPs outperform the SS method, with lower performance gain at small signal-to-noise ratios. The ASP sensitivity to the CFO value is studied, and the frequency bounds within which the optimized ASPs maintain high estimation accuracy are identified. A coarse CFO correction, effective for frequency estimation errors within the kHz range, extends the frequency bounds. Compared to a fine calibration, this reduces computational requirements, making it a viable option for embedded and IoT devices with limited hardware resources.

Accurate distance estimation in two-way multi-carrier phase difference (MCPD) ranging systems is degraded by carrier frequency offset (CFO) and timing discrepancies caused by asynchronized clocks between nodes. In previous work, carrier frequencies were typically utilized in ascending order during the MCPD process, a method referred to as sequential switching (SS) frequency switching pattern (FSP). Under asynchronous conditions, the SS FSP induces a linear phase trend across the frequency spectrum, resulting in systematic biasing. Existing works address this problem by estimating and compensating for the phase shifts caused by the asynchronization, but introduce additional computational complexity, latency, and power consumption. In this paper, we present a new signal model accounting for the relevant hardware imperfections, characterizing the effects of asynchronization on the phase measurements, and highlighting the limitations of the SS FSP. Building on this analysis, we propose rearranging carrier frequencies in the FSP and introduce a set of novel FSPs that eliminate the linear phase trend across the frequency spectrum and reduce the estimation error without requiring estimation or correction procedure. The results of the simulation study show that the proposed FSPs outperform the SS FSP under different oscillator mismatches achieving sub-centimeter systematic error at high signal-to-noise ratios (SNR), with performance gain decreasing with decreasing SNR and performance variability occurring with different numbers of carriers. Real-world experimental validation confirms a strong agreement between simulated and measured channel impulse responses and that the proposed FSPs produce more robust distance estimates to CFO variations than the SS FSP.

The integration of communications and wireless sensing using the same frequency spectrum is likely to be one of the key features beyond 5G wireless systems, enabling digital transformation to its full potential. Therefore, future wireless communication networks will have to become intelligent, meaning environment-aware, adaptive and parsimonious in terms of radio resources and energy. In this chapter, we propose a system architecture that enables the introduction of intelligent environment-aware wireless communications. Special attention has been paid to the description of the wireless channel in the database with a set of radio rays, generated by the calibrated ray tracing using the ray bouncing method. The proposed approach enables straightforward calculation of the channel impulse response enriched with information about the angle of arrival and angle of departure for the band-limited multiple antenna wireless communication systems. The proposed architecture introduces the concept of local and global agents, used for retrieving associated parameters from the user requirements and the existing radio channel characteristics data.