The need for generating radio signals with a high frequency stability and very low phase noise is a demanding requirement in communication systems. In low-power designs, such high-frequency signal generation is often the main source of power consumption, which necessitates low-power alternatives. Although tunnel diodes can generate high-frequency signals at low power, the generated signal is frequency unstable with high phase noise and unwanted harmonics. State-of-the-art address these limitations through injection locking, which requires an external signal generator that significantly increases the overall system power consumption. We present SharpPeak, a low-power long-range transmitter design that achieves high frequency stability using tunnel diodes without relying on external injection signals. This design lowers both system power and transmitter complexity, while improving frequency stability, phase noise, and frequency drifts. SharpPeak achieves high (370 kbps) data rates and long (1 km) communication range with under 175 μW power consumption at the RF front-end, advancing the state-of-the-art in energy-efficient communication systems. We believe that this work is a significant advancement in the development of a new generation of low-power communication systems.

Analog backscatter communication enables ultra-low-power and low-cost wireless connectivity, making it a promising alternative to traditional RFID systems. Although analog backscatter systems offer simplicity, they are by design less capable compared to their digital backscatter counterparts. A key drawback of existing analog backscatter systems is their single-tag operation, which poses limitations for applications that require multiple tags to function simultaneously. In this paper, we propose a novel low-cost analog backscatter system that allows multiple tags to sense the channel concurrently, thereby enabling signal strength-based localization and tracking of ambient RF sources. The ability to localize RF sources is essential for interference management, security, and optimization of wireless networks, particularly in dynamic environments. We evaluate our system in indoor settings, and demonstrate localization accuracy of RF sources with an average error of 20 cm in a 3m range, without requiring calibration. Our system is also capable of tracking RF sources with an average speed up to 0.6m/s with an average power consumption of 526µW, making it a promising solution for real-time and energy-constrained applications.

In-body communication is a key enabler for next-generation healthcare applications, allowing seamless networking of implants. Fat tissue, with its lower water content and reduced signal attenuation compared to other body tissues at microwave frequencies, has emerged as a promising medium for radio-based in-body networks. Despite this advantage, signal leakage through the body can compromise privacy, exposing sensitive data and the mere presence of implants to external adversaries. This paper investigates the feasibility of covert communication in fat tissue-based in-body networks by leveraging the previously unexplored signal attenuation properties of human tissue to transmit data undetectable to adversaries, ensuring privacy beyond encryption. We develop a system in which an implanted transmitter communicates discreetly with an implanted receiver, shielded from external passive eavesdroppers. Our theoretical analysis and experimental results demonstrate that the attenuation properties of human tissues enable covert communication at reduced transmit power levels without requiring friendly jamming, unlike over-the-air systems. To further enhance covertness, we explore the use of an external friendly jammer and show its significant benefits. Experimental results show a 500% increase in the maximum channel capacity of covert communication, from 2.86 bps/Hz at -56 dBm transmit power without jamming, to 17 bps/Hz with no bit errors at 0 dBm transmit power with a friendly jammer, using the IEEE 802.15.4 standard for communication in the 2.45 GHz frequency band. These findings highlight that covert communication is achievable in fat tissue-based in-body networks at low data rates without additional infrastructure such as an external jammer. For applications requiring higher data rates, a friendly jammer offers a scalable solution, making this approach practical for a wide range of implant communication scenarios.

Innovative medical applications based on networked implants foster the development of in-body communication technologies. Among the in-body communication technologies that are being considered, fat intra-body communication (Fat-IBC) is a very recent approach. Its main advantage lies in its higher data rate compared to earlier approaches based on capacitive and galvanic coupling. However, Fat-IBC faces privacy-, security-, as well as safety-related attacks. In this paper, we discuss security and privacy concerns about Fat-IBC, as well as corresponding countermeasures. Furthermore, we present our secure protocol stack for Fat-IBC and suggest directions for future research.

Analog backscatter enables sensing and communication at lower power consumption than digital backscatter. In analog tags, a sensor typically changes the resistance or capacitance value that then translates into a frequency change that is backscattered on top of a carrier. However, to read the sensor data with high resolution, a powerful receiver is required. The resolution of sensor data is limited by the FFT size and computation at the receiver. This limits the use of low-cost radio receivers, like RTL-SDR, that are gaining popularity in the RF community. We propose to use higher order harmonic frequencies, that are inherently generated by square wave backscattering at no extra cost, to derive sensor data using such low-cost radio receivers. We present experimental results that demonstrate the viability of our approach.

Medical implants are becoming increasingly widespread, and with that comes a need for networking multiple implants in the human body. This puts new demands on in-body communication, where conventional techniques (such as galvanic coupling) suffer from low bandwidth and data rates that can be insufficient for a network with several medical implants. Radio-based techniques at microwave frequencies can, on the other hand, provide a high-capacity communication channel, with the caveat that wave propagation through bodily materials at such frequencies is associated with significant signal loss, which limits the range. Fat tissue has been shown to have low loss compared to other tissues at frequencies such as 2.45 GHz and 5.8 GHz and could be a good choice of medium for a high-capacity channel. However, a drawback of radio-based in-body communication remains: signals may "leak'' out of the channel to the outside environment. This work investigates the leakage aspects of fat tissue-based in-body communication and explores methods for preserving the privacy of data from implants communicating through fat tissue. Through both simulations and practical experiments, we show that signals are heavily attenuated (on average by about 27 dB) when leaving the fat channel through the skin. Signal attenuation through the skin layer is similar even when the channel is not straight. Additionally, we demonstrate that reducing the transmit power as well as using an external, friendly "jamming'' signal can prevent that an external eavesdropper receives the data packets. In summary, we show that there is indeed RF leakage from in-body communication through fat tissue. However, the skin layer attenuates the signal quite heavily so that reducing the transmit power in combination with external jamming may prevent eavesdroppers outside the body from receiving sensitive in-body data.

Automating processes with the increased use of robots is one of the key vertical applications enabled by 6G. Sensing the surrounding environment, localization and communication become crucial factors for these robots to operate. Light detection and ranging (LiDAR) has emerged as an appropriate method for sensing due to its capability generating detail-rich positional information with high accuracy. However, LiDARs are power-hungry devices that generate bulk amounts of data, limiting their use as on-board sensors in robots. In this paper, we present a novel approach to the methodology of generating an enhanced 3D map with improved field-of-view using multiple LiDAR sensors. This offloads the sensing burden from robots to the infrastructure where a centralized communication network will establish localization. We utilize an inherent property of LiDAR point clouds; point rings with Inertial Measurement Unit (IMU) data embedded in the sensor for point cloud registration. The generated 3D point cloud map has an accuracy of 10 cm compared to the real-world measurements. We also carry out a proof of concept design of the proposed method using two LiDAR sensors fixed in the infrastructure at elevated positions. This extends to an application where a robot is navigated through the mapped environment using a wireless link with minimal support from the on-board sensors. Our results further validate the idea of using multiple elevated LiDARs as a part of the infrastructure for various localization applications.

Though fat channel communication has advantages over earlier intra-body communication (IBC) technologies based on galvanic or capacitive coupling, the development of a protocol stack on top of fat channel communication is still at its infancy. In this paper, we consider Krentz's denial-of-sleep-resilient multi-channel medium access control (MAC) layer for IEEE 802.15.4 networks as a starting point for such a protocol stack. In brief, we conducted the following experiment with a phantom that mimics human tissues. Two devices exchanged IEEE 802.15.4 radio frames in a ping-pong manner on the phantom's fat tissue using Krentz's MAC layer. The data collected from this experiment lends itself to two purposes. First, it can serve to benchmark and tune algorithms for selecting radio channels. Second, it can also serve to benchmark and tune schemes for deriving cryptographic keys from received signal strength indicator (RSSI) readings. We made the data available at https://uppsala.box.com/s/z2a6jpigswpoifd5l73yophokcfwd88b.

Simultaneous localization and mapping (SLAM) has been extensively researched in past years particularly with regard to range-based or visual-based sensors. Instead of deploying dedicated devices that use visual features, it is more pragmatic to exploit the radio features to achieve this task, due to their ubiquitous nature and the widespread deployment of the Wi-Fi wireless network. This article presents a novel approach for collaborative simultaneous localization and radio fingerprint mapping (C-SLAM-RF) in large unknown indoor environments. The proposed system uses received signal strengths (RSS) from Wi-Fi access points (APs) in the existing infrastructure and pedestrian dead reckoning (PDR) from a smartphone, without a prior knowledge about map or distribution of AP in the environment. We claim a loop closure based on the similarity of the two radio fingerprints. To further improve the performance, we incorporate the turning motion and assign a small uncertainty value to a loop closure if a matched turning is identified. The experiment was done in an area of 130 m by 70 m and the results show that our proposed system is capable of estimating the tracks of four users with an accuracy of 0.6 m with Tango-based PDR and 4.76 m with a step counter-based PDR.