Researchers from UC San Diego have developed RadSenNet, a new approach of sequential fusing of information from radars and cameras. The key idea of sequential fusion is to fundamentally shift the center of focus in radar-camera fusion systems from cameras to radars. This shift enables their invention (RadSegNet) to achieve all-weather perception benefits of radar sensing. Keeping radars as the primary modality ensures reliability in all situations including occlusions, longrange and bad weather.

Researchers from UC San Diego present a fully-passive, miniaturized, flexible form factor sensor interface titled ZenseTag that uses minimal electronics to read and communicate analog sensor data, directly at radio frequencies (RF). The technology exploits the fundamental principle of resonance, where a sensor's terminal impedance becomes most sensitive to the measured stimulus at its resonant frequency. This enables ZenseTag to read out the sensor variation using only energy harvested from wireless signals. UCSD inventors further demonstrate its implementation with a 15x10mm flexible PCB that connects sensors to a printed antenna and passive RFID ICs, enabling near real-time readout through a performant GUI-enabled software. They showcase ZenseTag's versatility by interfacing commercial force, soil moisture and photodiode sensors. 

Researchers from UC San Diego developed a patent-pending novel Synthesis of Virtual Array Manifold (SVAM) sensing approach for the mmWave single RF chain systems. More specifically, this new technology for sensing leads to faster and more robust beam alignment. UCSD believes this contribution will have significant impact on the traditional paradigm for sensing in mmWave systems.

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This technology revolutionizes health monitoring by integrating smart textiles with body area networks for real-time biometric data collection.

Many people have learned to appreciate the advent of GPS based navigational applications in our daily lives through the use of street level navigation, and many more loathe the same applications when using them to navigate established public transportation systems. Many of these travelers become confused and frustrated when attempting to understand and act on the directions given to them by such existing applications that primarily focus on large-scale street navigation, especially if the user has a visual or cognitive impairment. Several existing applications will not even attempt to aid someone in the navigation of say, a metro, train or bus station, and instead simply inform the user of the label of the route that the application intends the user to take. Without any small-scale directions many people find themselves struggling to figure out what platform or boarding zone they need to use to get on their preferred method of transportation, as well as how to get to these platforms and boarding zones in the first place. These transit hubs, plazas, malls, and the like have long been a pain in the side of developers and users alike when it comes to navigation. Innovation has long been overdue in this space concerning small scale transit plaza navigation, with major players holding large market shares in navigation not even attempting to address this longstanding problem. The only existing application to offer indoor navigation offers very limited as well as inconsistent functionality including only two-dimensional indoor mapping, due to manually uploaded floor plans that are only available in the first place from partnering locations. This has continued to be an issue due to a lack of adoption by existing locations, as each location is required to draw out their floor plan on an antiquated image file and submit it for approval. Solving this problem would ease a large amount of stress for those navigating in areas they are not familiar with, as well as saving time that could possibly make the difference between a missed train and a nearly missed train.

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Extended Reality (XR), broadly encompassing virtual, augmented, and mixed reality technologies, can potentially revolutionize fields such as education, healthcare, and gaming. The primary ethos for XR is to provide immersive, interactive, and realistic experiences for users. A key component of delivering this user experience is to transfer the physical world into the virtual space. For example, our everyday spaces and objects can be transformed into video game assets (like tennis racquets, swords, or chess pieces) for interactive gaming applications. To enable these applications, we find a common thread — any XR system should localize and track objects in an environment.Extended Reality (XR), broadly encompassing virtual, augmented, and mixed reality technologies can potentially revolutionize fields such as education, healthcare, and gaming. Applications include VR gaming, full body tracking, warehouse automation.Understanding the location of objects and people in the real world is key to enabling a smooth cyber-physical transition. However, most localization systems today require the deployment of multiple anchors in the environment, which can be very cumbersome to set up.

It is well known that the communication capacity of wireless networks is limited by interference. Depending on the strength of the interference, there are three conventional approaches to this problem. If the interference is very strong, then the receiver can decode the interfering signal and subtract from the desired signal using successive interference cancelation. If the interference signal is very weak compared to the desired signal, it can be treated as noise. The third and most common possibility is when the interference is comparable with the desired signal. In this case the interference can be avoided by orthogonalizing it with the desired signal using techniques such as time division multiple access (TDMA) or frequency division multiple access (FDMA). In addition to interference, wireless networks also experience channel fading. Conventional approaches to wireless networking attempt to combat fading. Depending on the coherence time of the fading, various approaches have been used. For example, fast fading may be mitigated by the use of diversity techniques, interleaving, and error-correcting codes. Certain diversity techniques, such as the use of multiple antennas, has been shown to help combat fading as well as increase multiplexing gain and system capacity. Multiuser diversity scheme is a technique to increase the capacity of wireless networks using multiple antennas at the base station. In this approach the base station selects a mobile device that has the best channel condition, maximizing the signal-to-noise ratio (SNR). According to some implementations of this approach, K random beams are constructed and information is transmitted to the users with the highest signal-to-noise plus interference ratio (SINR). Searching for the best SINR in the network, however, requires feedback from the mobile devices that scales linearly with the number of users. These implementations also use beamforming, which is complex to implement. In addition, the cooperation requirement is substantial.

         Recent mass evacuation events, including the 2018 Camp Fire and 2023 Maui Fire, have demonstrated shortcomings in our communication abilities during natural disasters and emergencies. Individuals fleeing dangerous areas were unable to obtain fast or accurate information pertaining to open evacuation routes and faced traffic gridlocks, while nearby communities were unprepared for the emergent situation and influx of persons. Climate change is increasing the frequency, areas subject to, and risk-level associated with natural hazards, making effective communication channels that can operate when mobile network-based systems and electric distribution systems are compromised crucial.         To address this need UC Berkeley researchers have developed a mobile network-free communication system that can function during natural disasters and be adapted to most communication devices (mobile phones and laptops). The self-organized, mesh-based and low-power network is embedded into common infrastructure monitoring device nodes (e.g., pre-existing WSN, LoRa, and other LPWAN devices) for effective local communication. Local communication contains dedicated Emergency Messaging and “walkie-talkie” functions, while higher level connectivity through robust gateway architecture and data transmission units allows for real-time internet access, communication with nearby communities, and even global connectivity. The system can provide GPS-free position information using trilateration, which can help identify the location of nodes monitoring important environmental conditions or allowing users to navigate.

Networks of connectivity-enabled devices, known as internet of things or IoT, involve interrelated devices that connect and exchange data with other IoT devices and the cloud. As the number of IoT devices and their applications continue to significantly increase, managing and administering edge and access networks have become increasingly more challenging. Currently, there are approximately 31 billion ‘‘things’’ connected to the internet, with a projected rise to 75 billion devices by 2025. Because of IoT interconnectivity and ubiquitous device use, assessing the risks, designing/specifying what’s reasonable, and implementing controls can be overwhelming to conventional frameworks. Any approach to better IoT network security, for example by improved detection and denial or restriction of access by unauthorized devices, must consider its impact on performance such as speed, power use, interoperability, and scalability. The IoT network’s physical and MAC layers are not impenetrable and have many known threats, especially identity-based attacks such as MAC spoofing events. Common network infrastructure uses WPA2 or IEEE 802.11i to help protect users and their devices and connected infrastructure. However, the risk of MAC spoofing remains, as bad actors leverage public tools on 802.11 commodity hardware, or intercept sensitive data packets at scale, to access users physical layer data, and can lead to wider tampering and manipulation of hardware-level parameters.

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Researchers from UC San Diego have developed MIRAGE, an algorithm that the user can employ on their devices (e.g., smartphone) to maintain their location privacy if desired without compromising their Wi-Fi’s quality of service.The innovation would be additional software on the user's WiFI device, enabling which would make the listening WiFI AP infrastructure unable to detect the user's location unless and until the user is willing to provide it. All of this happens without any compromise to the data rate of the WiFi-user communication.

This invention is a new system of algorithms for decoding linear block codes. Given the received message block, the decoding algorithm is designed to recover the truly transmitted symbols.Engineers from UC San Diego have invented a decoding system that can be shown to achieve near-optimal decoding performance for general linear codes of dimension less than or equal to 128. In particular, for Reed–Muller codes, this new algorithm is the first to be shown with simulation evidence to achieve the optimal block error rate for communications over binary symmetric channels. This invention employs multiple Monte Carlo Markov chain subdecoders in parallel, which is a novel idea compared to the existing art. 

Millimeter wave sensing has recently attracted a lot of attention given its environmental robust nature. In situations where visual sensors like cameras fail to perform, mmwave radars can be used to achieve reliable performance. However, because of the poor scattering performance and lack of texture in millimeter waves, radars can not be used in several situations that require precise identification of objects.  A video demonstration of R-fiducial could be found at https://streamable.com/7ax59s 

Frequency-division multiple access (FDMA) is a channel access method used in some multiple-access protocols. FDMA allows multiple users to send data through a single communication channel, such as a coaxial cable or microwave beam, by dividing the bandwidth of the channel into separate non-overlapping frequency sub-channels and allocating each sub-channel to a separate user. FDMA is highly power‐efficient and can work with single antenna base stations. This is because FDMA separates users in spectrum and then samples the net increased bandwidth.Digital beamforming is highly spectrum efficient, however needs multiple antenna base stations. This is because to resolve the multiple users interfering we need to sample the signals from multiple antennas to cancel out the interferences, which requires a dedicated downconversion chain per antenna. The requirement of multiple downconversion chains makes the solution power hungry, and thus has limited adoption.

Antennas are transducers that convert electronic signals into electromagnetic (EM) waves and vice-versa. An antenna can be electrically excited by a transmission line, an aperture coupling, or wirelessly by another source of electromagnetic wave. One type of antenna is a patch antenna formed by mounting a first sheet of metal over a second sheet of metal serving as a ground plane. Patch antennas have a low profile and are thus suitable for mounting on a surface. However, patch antennas may be less efficient and exhibit higher than desirable return loss. A dielectric resonator antenna (DRA), which that includes a dielectric resonator disposed on top of another substrate in which the dielectric resonator is housed, may exhibit significantly lower losses than traditional metallic patch antennas. Nevertheless, conventional dielectric resonator antennas have limited beam steering capabilities. In particular, conventional dielectric resonator antennas exhibit a low quality factor (Q factor) at millimeter wave (mm-wave) frequencies. 

Wireless researchers at UC San Diego have invented a wireless force sensor comprising a deformable passive force sensor that induces a change in an interrogation RF signal present on a conductive connection to produce a changed reflective signal and an ID circuit that responds with an ID and the changed reflective signal.

Modern mmWave systems cannot scale to a large number of users because of the inflexibility in performing directional frequency multiplexing. All the frequency components in the mmWave signal are beamformed to one direction via pencil beams and cannot be streamed to other user directions. Engineers from UC San Diego present mmFlexible, a flexible mmWave system that enables flexible directional frequency multiplexing, allowing different frequency components to radiate in multiple arbitrary directions with the same pencil beam.

The exchange of information among nodes in a communications network is based upon the transmission of discrete packets of data from a transmitter to a receiver over a carrier according to one or more of many well-known, new or still developing protocols. In this context, a protocol consists of a set of rules defining how the nodes interact with each other based on information sent over the communication links. Often, multiple nodes will transmit a packet at the same time and a collision occurs. During a collision, the packets are disrupted and become unintelligible to the other devices listening to the carrier activity. In addition to packet loss, network performance is greatly impacted. The delay introduced by the need to retransmit the packets cascades throughout the network to the other devices waiting to transmit over the carrier. Therefore, packet collision has a multiplicative effect that is detrimental to communications networks. As a result, multiple international protocols have been developed to address packet collision, including collision detection and avoidance. Within the context of wired Ethernet networks, the issue of packet collision has been largely addressed by network protocols that try to detect a packet collision and then wait until the carrier is clear to retransmit. Emphasis is placed in collision detection, i.e., a transmitting node can determine whether a collision has occurred by sensing the carrier. At the same time, the nature of wireless networks prevents wireless nodes from being able to detect a collision. This is the case, in part, because in wireless networks the nodes can send and receive but cannot sense packets traversing the carrier after the transmission has started. Another problem arises when two transmitting nodes are out of range of each other, but the receiving node is within range of both. In this case, a transmitting node cannot sense another transmitting node that is out of communications range. IEEE 802.11 protocols are the basis for wireless network products using the Wi-Fi brand and are the world's most widely used wireless computer networking standards. With IEEE 802.11 packet collision features come deficiencies, like fairness. 802.11’s approach to certain parameters after each successful transmission may cause the node who succeeds in transmitting to dominate the channel for an arbitrarily long period of time. As a result, other nodes may suffer from severe short-term unfairness. Also, the current state of the network (e.g., load) is something that also should be factored. In general, there is a need for techniques to recognize network patterns and determine certain parameters that are responsive to those network patterns.

Researchers from UC San Diego have developed a technology that integrates WiFi as a sensor to simultaneously locate the robot and Map the WiFi access point (APs) in the environment.The invention allows for any WiFi receiver and transmitter to be repurposed to be used for localization purposes for a robot. The invention makes use of both WiFi access points deployed in the environment and one deployed on the robot to get accurate location of the robot in large spaces. Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

Although GPS can be used for localization outdoors, indoor environments (office buildings, shopping malls, transit hubs) can be particularly challenging for many of the general population, and especially for blind walkers. GPS-denied environments have received considerable attention in recent years as our population’s digital expectations grow. To address GPS-denied environments, various services have been explored, including technology based on Bluetooth low energy (BLE), Wi-Fi, and camera. Drawbacks with these approaches are common, including calibration (fingerprinting) overhead using Wi-Fi, beacon infrastructure costs using BLE, and unoccluded visibility requirements in camera-based systems. While localization and wayfinding using inertial sensing overcomes these challenges, large errors with accumulated drift are known. Moreover, the decoupling of the orientation of the phone from the direction of walking, as well as accurately detecting walker’s velocity and detecting steps and measuring stride lengths, have also been challenges for traditional pedestrian dead reckoning (PDR) systems. Relatedly, blind walkers (especially those who do not use a dog guide) often tend to veer when attempting to walk in a straight line, and this unwanted veering may generate false turn detections with such inertial methods.

In most wireless ad-hoc multi-hop networks, a node competes for access to the same wireless communication channel, often resulting in collisions (interference) and ineffective carrier sensing. These issues have been targeted through the medium access control (MAC) interconnection layer by a variety of channel access schemes, towards improving how the nodes share the wireless channel and achieve a high quality of service. For example, there are contention-based MAC schemes, like Carrier-Sense Multiple Access (CSMA) and Additive Links On-Line Hawaii Area (ALOHA), and contention-free MAC schemes, like time division multiplexing access (TDMA). However, the former is a poor performer in hidden- and exposed-terminal environments, and the latter, where the node system is time-synchronized and the time frame is divided and multiple time-slots are allocated to the nodes, has limited data rates (bandwidth) and undesirable latency. Over the years, there have been many other MAC schemes that address interference and conflict, as well as improving criteria like throughput, fairness, latency, energy, and overhead. These modern protocols implement more sophisticated distributed transmission queues consisting of a sequence of transmission turns that grows and shrinks on demand. However, challenges remain in these more recent MAC protocols, such as long delays for allowing nodes to join the network, and/or the use of transmission frames with complex structures to allocate time slot portions to signaling packets for elections.

Measurement of electrical activity in nervous tissue has many applications in medicine, but the implantation of a large number of sensors is traditionally very risky and costly. Devices must be large due to their necessary complexity and power requirements, driving up the risk further and discouraging adoption. To address these problems, researchers at UC Berkeley have developed devices and methods to allow small, very simple and power-efficient sensors to transmit information by backscatter feedback. That is, a much more complex and powerful external interrogator sends an electromagnetic or ultrasound signal, which is modulated by the sensor nodes and reflected back to the interrogator. Machine learning algorithms are then able to map the reflected signals to nervous activity. The asymmetric nature of this process allows most of the complexity to be offloaded to the external interrogator, which is not subject to the same constraints as implanted devices. This allows for larger networks of nodes which can generate higher resolution data at lower risks and costs than existing devices.