Advancements in computing have enabled emerging applications such as telesurgery, robot automation, holographic telepresence, and extended reality, which require gigabitper-second throughput, sub-millisecond latency, and highly reliable wireless connectivity. Millimeter wave (mmWave) technology has promised to enable such connectivity by operating over a large bandwidth in the high-frequency spectrum bands (24 GHz and above). However, due to the short wavelength and high directionality of mmWave signals, mmWave networks have limited coverage and are highly susceptible to blockage. In particular, high-data-rate mmWave networks work reliably only when there is a clear line-of-sight (LOS) path between users and base stations. Unfortunately, due to this problem, mmWave networks have not been able to scale and become ubiquitous. Past work has proposed mmWave repeaters and intelligent surfaces to solve this issue by rerouting signal around blockages. However, these solutions are expensive and complex to build, consume high power, or/and require constant feedback from the network to operate since they use active techniques for beam steering. In this paper, we present the first mmWave repeater which uses passive beamforming technique. Our repeater is low-cost, low-power, and can support multiple users simultaneously. Most importantly, it does not require any feedback from the network to operate. Hence, it can be easily deployed on-demand to solve the coverage and blockage problem of mmWave networks whenever and wherever high-data-rate and low-latency connectivity is needed.

With the advancement of the Internet of Things (IoT), many devices will be connected to the Internet, enabling digital twin and smart home applications. However, currently, these IoT devices are operating at lower frequency bands of the wireless spectrum, typically ranging from a few hundred MHz (such as RFID and LoRa) to a few GHz (such as BLE and WiFi). As a result, the current IoT devices not only place a huge strain on these bands, but also cannot benefit from the large bandwidth available in the higher frequencies of the spectrum such as mmWave bands. In this paper, our goal is to bring mmWave technology to existing IoT devices so they can benefit from the advantages this technology offers, such as high network capacity, low interference, and Space Division Multiple Access. To this end, we design mmPlug, a novel plug-and-play module which is simple and energy-efficient. mmPlug can be easily connected to the antenna port of any IoT device, enabling it to operate in the mmWave band. mm-Plug is compatible with different wireless technologies (such as WiFi, Lora, etc.) and does not require any modification to the circuit, firmware or communication protocols of the existing IoT devices. mmPlug achieves this by a novel design which can seamlessly be connected to the antenna port of the IoT device. We have implemented mmPlug on PCB and empirically evaluated its performance. Our results show that mmPlug enables existing IoT devices (such as WiFi and Lora) to operate at mmWave band while achieving accurate localization, uplink and downlink even when they are more than 30 m far from the access point.

Millimeter wave (mmWave) technology enables wireless devices to communicate using very high-frequency signals. Operating at those frequencies provides larger bandwidth which can be used to enable high-data-rate links, and very accurate localization of devices. However, radios operating at high-frequencies consume significant amount of power, making them unsuitable for applications with limited energy sources. This paper presents MilBack, a backscatter network operating at mmWave bands. Backscattering is the most energy-efficient wireless communication technique, where nodes piggyback their data on an access point's signal instead of generating their own signals. Eliminating the need for signal generation significantly reduces the energy-consumption of the nodes. In contrast to past mmWave backscatter work which supports only uplink, MilBack is the first mmWave backscatter network which supports uplink, downlink, and accurate localization. MilBack addresses the key challenges that prevent existing backscatter networks to enable both uplink and downlink at mmWave bands. We implemented MilBack and evaluated its performance empirically. Our results show that MilBack is capable of achieving accurate localization, uplink, and downlink communication at up to 8 m while consuming only 32 mW and 18 mW, respectively.

Recent advances in IoT, machine learning and cloud computing have placed a huge strain on wireless networks. In particular, many emerging applications require streaming rich content (such as videos) in real time, while they are constrained by energy sources. A wireless network which supports high data-rate while consuming low-power would be very attractive for these applications. Unfortunately, existing wireless networks do not satisfy this requirement. For example, WiFi backscatter and Bluetooth networks have very low power consumption, but their data-rate is very limited (less than a Mbps). On the other hand, modern WiFi and mmWave networks support high throughput, but have a high power consumption (more than a watt).

Backscatter networks (such as RFID, and WiFi backscatter) are very attractive for IoT applications due to their ultra-low energy consumption. In fact, their required energy to operate is low enough that it can be harvested from the environment without having a battery. However, existing backscatter networks offer very limited data-rates (i.e. at most one Mbps). Hence, despite their energy benefit, their applications are very limited. This paper presents the design of mmTag, a backscatter network which can achieve Gbps data-rates. mmTag achieves this by developing a backscatter technology operating in the mmWave spectrum band. mmWave promises to enable high throughput wireless links by offering massive chunks of high-frequency spectrum. However, to use mmWave frequencies in backscatter networks, we need to address a fundamental challenge: beam alignment. mmWave devices require highly directional antennas with very narrow beams, and communication is possible only when the transmitter's beam is aligned with the receiver's beam. However, existing beam searching techniques require power hungry components, and most importantly require the node to transmit a signal which is not possible for a backscatter device. mmTag solves this problem by building a mmWave backscatter tag which performs beam alignment without using any active component. Finally, we implement mmTag and empirically demonstrate some results.

We introduce a passive Radio Frequency IDentification (RFID) based system to detect finger gesture input for Human-Computer Interaction applications. The device is simple, inexpensive and does not require calibration to accommodate changes in the device location or the Radio Frequency (RF) environment. This is achieved by connecting the chips of two RFID tags together using a strip transmission line. The key observation is that touching different positions along the transmission line changes the impedance matching between each chip and its antenna, changing Received Signal Strength (RSS) values for each tag. When a finger slides in different directions between key positions along the transmission line, there are relative RSS patterns and trends that are robust to changes in the device location and the RF environment. We implemented and evaluated an detection algorithm and system using a commercial RFID reader and two commercial RFID chips. Results show that precision and recall are greater than 95% and 94% when detecting 10 finger gesture inputs across 48 different device locations.

WiFi backscatter communication has the potential to enable battery-free sensors which can transmit data using a WiFi network. In order for WiFi backscatter systems to be practical they should be compatible with existing WiFi networks without any hardware or software modifications. Moreover, they should work with networks that use encryption. In this paper, we present WiTAG which achieves these requirements, making the implementation and deployment of WiFi backscatter communication more practical. In contrast with existing systems which utilize the physical layer for backscatter communication, we take a different approach by leveraging features of the MAC layer to communicate. WiTAG is designed to send data by selectively interfering with subframes (MPDUs) in an aggregated frame (A-MPDU). This enables standard compliant communication using modern, open or encrypted 802.11n and 802.11ac networks without requiring hardware or software modifications to any devices. We implement WiTAG using off-the-shelf components and evaluate its performance in line-of-sight and non-line-of-sight scenarios. We show that WiTAG achieves a throughput of up to 4 Kbps without impacting other devices in the network.

With the advent of the Internet of Things (IoT), billions of new connected devices will come online, placing a huge strain on today's WiFi and cellular spectrum. This problem will be further exacerbated by the fact that many of these IoT devices are low-power devices that use low-rate modulation schemes and therefore do not use the spectrum efficiently. Millimeter wave (mmWave) technology promises to revolutionize wireless networks and solve spectrum shortage problem through the usage of massive chunks of high-frequency spectrum. However, adapting this technology presents challenges. Past work has addressed challenges in using mmWave for emerging applications, such as 5G, virtual reality and data centers, which require multiple-gigabits-per-second links, while having substantial energy and computing power. In contrast, this paper focuses on designing a mmWave network for low-power, low-cost IoT devices. We address the key challenges that prevent existing mmWave technology from being used for such IoT devices. First, current mmWave radios are power hungry and expensive. Second, mmWave radios use directional antennas to search for the best beam alignment. Existing beam searching techniques are complex and require feedback from access points (AP), which makes them unsuitable for low-power, low-cost IoT devices. We present mmX, a novel mmWave network that addresses existing challenges in exploiting mmWave for IoT devices. We implemented mmX and evaluated it empirically.

WiFi-based backscatter systems provide the potential to deliver battery-free sensors (tags) which can transmit data using a WiFi network. Existing backscatter systems have several problems which make them impractical to deploy and operate using existing WiFi networks. First, they require software or hardware modifications to WiFi access points and devices. Second, they do not work with WiFi networks that use a security protocol such as WPA. Third, they interfere with existing WiFi communication because they reflect their signal to another channel without implementing channel sensing. In this paper, we present WiTAG which addresses these problems, making the implementation and deployment of backscatter systems significantly more practical. In contrast with existing systems that build tags to communicate using the physical layer, we take a radically different approach by building tags that leverage features of the MAC layer to communicate. We design tags which can selectively interfere with subframes (MPDUs) in an aggregated frame (A-MPDU). This enables standard compliant communication using modern 802.11n and 802.11ac networks with minimal infrastructure and without requiring hardware or software modifications to any devices. The evaluation of our prototype system shows that with a client and an access point that are 8 meters apart, a tag can achieve data rates of 40 Kbps when located anywhere between the two devices.

Recently there has been a huge interest in performing research on millimeter wave (mmWave) communications. Prior work utilize this technology in enabling Gbps wireless links. In contrast, we exploit mmWave technology in designing high-density IoT networks, where there are hundreds of nodes, but each requiring only a Mbps wireless link. However, existing mmWave radios are costly and have high power consumption which makes them unsuitable for IoT sensors. We have built mmPi: a low-cost and low-power mmWave radio that operates as a daughterboard for the Raspberry Pi platform. We believe that mmPi helps advance mmWave research in the IoT domain.