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.

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.

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.

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.

WiFi backscattering can enable direct connectivity of IoT devices with commodity WiFi hardware at low power. However, most existing work in this area has overlooked the importance of synchronization and, as a result, accepted either limited range between the transmitter and the IoT device, reduced throughput via bit repetition, or both.

Wi-Fi is the most ubiquitous wireless networking technology for loT in homes, offices, and businesses. Since the power of Wi-Fi transceivers (10s-to-100s of mW) can be prohibitively high for emerging classes of loT devices (which desire <100μW), recent work has suggested piggybacking baseband signals from the loT device directly on top of incident Wi-Fi signals generated by access points (APs) via Wi-Fi-compatible backscatter modulation, where as low as 28μW of active power has been demonstrated. However, the major limitation of this approach is range.

Researchers from UC San Diego have developed ULoc, a scalable, low-power, and cm-accurate UWB localization and tracking system in the form of a VR headset tracking, that provides real-time accurate 3D indoor localization.

Power amplifier performance for emerging 5G mm-wave systems poses significant challenges for output power, efficiency and linearity. Efficiency in backoff is a key concern, given the peak-to-average power ratio of order 6-9dB for 5G signals. As a result, considerable attention has been given to composite amplifiers featuring backoff efficiency enhancement, particularly Doherty amplifiers. Adaptive bias circuits have been previously developed for use with power amplifiers at low microwave frequencies (for example, 1-2GHz as applied in 2G, 3G and 4G cellular networks).  Direct application of these techniques is not straightforward at higher frequencies, such as 28GHz as used for 5G wireless communications, because the transistors have less gain at the high frequencies. 

There has been a steady rise in interest in utilizing Fin high-electron mobility transistors HEMT devices to reduce the source access resistance and enhance the linearity but this linearity is not accessible at gate voltages beyond those at which the gate Schottky diode turns on (~2 V). All known transistor technologies are intrinsically non-linear. This non-linearity leads to signal distortion and power loss. Non-linearity is embodied in a decrease of the transistor current gain cut-off frequency, fT, and maximum oscillation frequency, fmax, with an increase in the drain current.  In contrast, the patented technology here is one of a new Fin MOS-HEMT device permits flexible engineering of the device threshold voltage in order to attain linearity over a wider VGS range (voltage between transistor gate and source (VGS) in excess of the threshold voltage (Vt) where Vt is defined as the minimum).

Contact force is a natural way for humans to interact with the physical world around us. However, most of our interactions with the digital world are largely based on a simple binary sense of touch (contact or no contact). Similarly, when interacting with robots to perform complex tasks, such as surgery, we need to acquire the rich force information and contact location, to aid in the task. To address these issues, researchers at UC San Diego have developed WiForce, which is a ‘wireless’ sensor that can be attached to an object or robot, like a sticker. WiForce’s sensor transduces force magnitude and location into phase changes of an incident RF signal, which is reflected back to enable measurement of force and contact location.

Indoor localization has been studied for nearly two decades fueled by wide interest in indoor navigation, achieving the necessary decimeter-level accuracy. However, there are no real-world deployments of WiFi-based user localization algorithms, primarily because these algorithms are infrastructure dependent and therefore assume the location of the Access Points, their antenna geometries, and deployment orientations in the physical map. In the real world, such detailed knowledge of the location attributes of the access point is seldom available, thereby making WiFi localization hard to deploy.   Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Location services, fundamentally, rely on two components: a mapping system and a positioning system. The mapping system provides context, and the positioning system identifies the position within the map. Outdoor location services have thrived over the last couple of decades because of wellestablished platforms for both these components (e.g. Google Maps for mapping, and GPS for positioning). In contrast, indoor location services haven’t caught up because of the lack of reliable mapping and positioning frameworks (and lack of integration between the two). SLAM methods construct maps that aren’t tagged with locations. Wi-Fi positioning lacks maps, and is also prone to environmental errors. In contrast, indoor navigation even with significant interest from industry and academia lacks further behind.  We cannot use our smartphone to navigate to a conference room in a new building or to find a product of interest in a shopping mall. The primary reason for the poor indoor navigation system is the unavailability of indoor localization augmented maps and floor plans. On one hand, Google and a few other providers make indoor floor plans for airports, malls, and famous buildings, those floor-plans have to be created manually and often need to updated as floor plans change and they lack details such as the position of furniture and other obstacles. On the other hand, besides mapping, ability to position users’ location on these indoor maps is necessary for indoor navigation  

Millimeter-wave communication with high throughput and high reliability is poised to be a gamechanger for V2X and VR applications. However, mmWave links are notorious for low reliability since they suffer from frequent outages due to blockage and user mobility. Traditional mmWave systems are hardly reliable for two reasons. First, they create a highly directional link that acts as a single point of failure and cannot be sustained for high user mobility. Second, they follow a `reactive' approach, which reacts after the link has already suffered an outage. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

Brief description not available

In the last decade, the bandwidth expansion and MIMO spatial multiplexing have promised to increase data throughput by orders of magnitude. However, we are yet to enjoy such improvement in real-world environments, as they lack rich scattering and preclude effective MIMO spatial multiplexing.

Bluetooth Low Energy (BLE) tags have become very prevalent over the last decade for tracking applications in homes as well as businesses. These tags are used to track objects, navigate people, and deliver contextual advertisements. However, in spite of the wide interest in tracking BLE tags, the primary methods of tracking them are based on signal strength (RSSI) measurements. Past work has shown that such methods are inaccurate, and prone to multipath and dynamic environments. As a result, localization using Wi-Fi has moved to Channel State Information (CSI, includes both signal strength and signal phase) based localization methods. In indoor environments, BLE tags are the methods of choice. They provide sufficiently long range indoors, are resistant to frequency selective fading and have low power operation. BLE tags are readable by off-the-shelf smartphones and access points, because of their co-existence in the 2.4 GHz Wi-Fi band. BLE tags are, therefore, getting very popular for tracking operations in homes, factory floors, etc. Google’s vision for physical web is based on extensive deployment of BLE beacons. It is in this context that localization for BLE devices becomes crucial. Deep Neural Networks and Convolutional Neural Network techniques to overcome these limitations.

Existing cellular networks assume that interference from neighboring cells is treated as noise and mobile devices are selected (scheduled) to communicate based on performance metrics for each device. When sliding-window coded modulation (SWCM) is used however, the performance metrics depend on those of interfering devices in neighboring cells, and hence scheduling has to be performed simultaneously over multiple cells.

To meet the demand for wireless data traffic having increased since deployment of 4G communication systems, efforts have been made to develop an improved 5G or pre-5G communication system. Therefore, the 5G or pre-5G communication system is also called a 'Beyond 4G Network' or a 'Post LTE System'. The 5G communication system is considered to be implemented in higher frequency (mm Wave) bands, e.g., 60GHz bands, so as to accomplish higher data rates. To decrease propagation loss of the radio waves and increase the transmission distance, the beamforming, massive multiple-input multiple-output (MIMO), Full Dimensional MIMO (FD-MIMO), array antenna, an analog beam forming, large scale antenna techniques are discussed in 5G communication systems In addition, in 5G communication systems, development for system network improvement is under way based on advanced small cells, cloud Radio Access Networks (RANs), ultra-dense networks, device-to-device (D2D) communication, wireless backhaul, moving network, cooperative communication, Coordinated Multi-Points (CoMP), reception-end interference cancellation and the like. In the 5G system, Hybrid FSK and QAM Modulation (FQAM) and sliding window superposition coding (SWSC) as an advanced coding modulation (ACM), and filter bank multi carrier(FBMC), non-orthogonal multiple access(NOMA), and sparse code multiple access (SCMA) as an advanced access technology have been developed. The sliding-window superposition coding (SWSC) is a coding method capable of reaching a theoretical critical value performance of a physical layer in an additive white Gaussian noise (A WGN) interference environment where a fading is not generated, and thus the SWSC has a high efficiency.