The spatial features of emitted wireless signals are the basis of location distinction and determination for wireless indoor localization. Available in mainstream wireless signal measurements, the Received Signal Strength Indicator (RSSI) has been adopted in vast indoor localization systems. However, it suffers from dramatic performance degradation in complex situations due to multipath fading and temporal dynamics.Break-through techniques resort to finer-grained wireless channel measurement than RSSI. Different from RSSI, the PHY layer power feature, channel response, is able to discriminate multipath characteristics, and thus holds the potential for the convergence of accurate and pervasive indoor localization. Channel State Information (CSI, reflecting channel response in 802.11 a/g/n) has attracted many research efforts and some pioneer works have demonstrated submeter or even centimeter-level accuracy. In this article, we survey this new trend of channel response in localization. The differences between CSI and RSSI are highlighted with respect to network layering, time resolution, frequency resolution, stability, and accessibility. Furthermore, we investigate a large body of recent works and classify them overall into three categories according to how to use CSI. For each category, we emphasize the basic principles and address future directions of research in this new and largely open area.

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=5541&context=sis_research

From RSSI to CSI: Indoor localization via channel response

The spatial features of emitted wireless signals are the basis of location distinction and determination for wireless indoor localization. Available in mainstream wireless signal measurements, the Received Signal Strength Indicator (RSSI) has been adopted in vast indoor localization systems. However, it suffers from dramatic performance degradation in complex situations due to multipath fading and temporal dynamics. Break-through techniques resort to finer-grained wireless channel measurement than RSSI. Different from RSSI, the PHY layer power feature, channel response, is able to discriminate multipath characteristics, and thus holds the potential for the convergence of accurate and pervasive indoor localization. Channel State Information (CSI, reflecting channel response in 802.11 a/g/n) has attracted many research efforts and some pioneer works have demonstrated submeter or even centimeter-level accuracy. In this article, we survey this new trend of channel response in localization. The differences between CSI and RSSI are highlighted with respect to network layering, time resolution, frequency resolution, stability, and accessibility. Furthermore, we investigate a large body of recent works and classify them overall into three categories according to how to use CSI. For each category, we emphasize the basic principles and address future directions of research in this new and largely open area.

From RSSI to CSI: Indoor Localization via Channel Response, A survey on indoor localization using PHY-layer information

Aspects of the subject disclosure may include, for example, a transmission device that includes a transmitter that generates a first electromagnetic wave to convey data. A coupler couples the first electromagnetic wave to a single wire transmission medium having an outer surface, to forming a second electromagnetic wave that is guided to propagate along the outer surface of the single wire transmission medium via at least one guided wave mode that includes an asymmetric or non-fundamental mode having a lower cutoff frequency. A carrier frequency of the second electromagnetic wave is selected to be within a limited range of the lower cutoff frequency, so that a majority of the electric field is concentrated within a distance from the outer surface that is less than half the largest cross sectional dimension of the single wire transmission medium, and/or to reduce propagation loss. Other embodiments are disclosed.

Guided-wave transmission device with non-fundamental mode propagation and methods for use therewith

Aspects of the subject disclosure may include, for example, a system for generating electromagnetic waves having a fundamental wave mode, and directing the electromagnetic waves to an interface of a transmission medium for guiding propagation of the electromagnetic waves. Other embodiments are disclosed.

Methods and apparatus for inducing a non-fundamental wave mode on a transmission medium

Aspects of the subject disclosure may include, for example, a waveguide system that includes a transmission device having a coupler positioned with respect to a transmission medium to facilitate transmission or reception of electromagnetic waves that transport communications data. The electromagnetic waves propagate along an outer surface of the transmission medium. A training controller detects an impairment on the transmission medium adverse to the transmission or reception of the electromagnetic waves and adjusts the electromagnetic waves to reduce the effects of the impairment on the transmission medium. Other embodiments are disclosed.

Transmission device with impairment compensation and methods for use therewith

In this paper, we design and develop RIO, a novel battery-free touch sensing user interface (UI) primitive for future IoT and smart spaces. RIO enables UIs to be constructed using off-the-shelf RFID readers and tags, and provides a unique approach to designing smart IoT spaces. With RIO, any surface can be turned into a touch-aware surface by simply attaching RFID tags to them. RIO also supports custom-designed RFID tags, and thus allows specially customized UIs to be easily deployed into a real-world environment. RIO is built using the technique of impedance tracking: when a human finger touches the surface of an RFID tag, the impedance of the antenna changes. This change manifests as a change in the phase of the RFID backscattered signal, and is used by RIO to track fine-grained touch movement over both off-the shelf and custom built tags. We study this impedance behavior in-depth and show how RIO is a reliable UI primitive that is robust even within a multi-tag environment. We leverage this primitive to build a prototype of RIO that can continuously locate a finger during a swipe movement to within 3 mm of its actual position. We also show how custom-design RFID tags can be built and used with RIO, and provide two example applications that demonstrate its real-world use.

RIO: A Pervasive RFID-based Touch Gesture Interface

The advances in unmanned aerial vehicle (UAV) technology have empowered mobile operators to deploy LTE base stations (BSs) on UAVs, and provide on-demand, adaptive connectivity to hotspot venues as well as emergency scenarios. However, today's evolved packet core (EPC) that orchestrates the LTE RAN faces fundamental limitations in catering to such a challenging, wireless and mobile UAV environment, particularly in the presence of multiple BSs (UAVs). In this work, we argue for and propose an alternate, radical edge EPC design, called SkyCore that pushes the EPC functionality to the extreme edge of the core network - collapses the EPC into a single, light-weight, self-contained entity that is co-located with each of the UAV BS. SkyCore incorporates elements that are designed to address the unique challenges facing such a distributed design in the UAV environment, namely the resource-constraints of UAV platforms, and the distributed management of pronounced UAV and UE mobility. We build and deploy a fully functional version of SkyCore on a two-UAV LTE network and showcase its (i) ability to interoperate with commercial LTE BSs as well as smartphones, (ii) support for both hotspot and standalone multi-UAV deployments, and (iii) superior control and data plane performance compared to other EPC variants in this environment.

SkyCore: Moving Core to the Edge for Untethered and Reliable UAV-based LTE Networks

In this work, we explore the potential and impact of unlicensed LTE on WiFi in unlicensed spectrum. Our experiments demonstrate that the large asymmetry in the channel access methodologies employed by WiFi and LTE (carrier sensing/notification in WiFi, energy sensing alone in LTE-U), can result LTE-U completely blocking WiFi transmissions, and causing significant degradation to either technologies from collisions. We address this critical sensing asymmetry with Ultron, a LTE-WiFi co-existence solution that integrates WiFi's carrier sensing and notification mechanisms into LTE, without any modifications to the LTE PHY standard. Ultron operates at the LTE base station and consists of two key components: (a) WiFi embedding that embeds appropriate data into the LTE-subframes through an intelligent reverse-engineering of the LTE PHY, so as to realize a WiFi PLCP preamble-header transmission over the air directly using the LTE PHY; and (b) scalable WiFi sensing that employs a single WiFi interface and maximizes its carrier sensing benefits to all the unlicensed channels operating at the LTE node. Our evaluations demonstrate that Ultron can increase the WiFi and LTE throughput by 5x and 6x respectively, resulting from a sharp reduction in LTE-WiFi interference.

LTE in unlicensed spectrum: are we there yet?

Material sensing is an essential ingredient for many IoT applications. While hyperspectral camera, infrared, X-Ray, and Radar provide potential solutions for material identification, high cost is the major concern limiting their applications. In this paper, we explore the capability of employing RF signals for fine-grained material sensing with commodity RFID device. The key reason for our system to work is that the tag antenna's impedance is changed when it is close or attached to a target. The amount of impedance change is dependent on the target's material type, thus enabling us to utilize the impedance-related phase change available at commodity RFID devices for material sensing. Several key challenges are addressed before we turn the idea into a functional system: (i) the random tag-reader distance causes an additional unknown phase change on top of the phase change caused by the target material; (ii) the tag rotations cause phase shifts and (iii) for conductive liquid, there exists liquid reflection which interferes with the impedance-caused phase change. We address these challenges with novel solutions. Comprehensive experiments show high identification accuracies even for very similar materials such as Pepsi and Coke.

Tagtag: material sensing with commodity RFID

A computing device can determine a radio frequency (RF) bandwidth in which one or more frames are to be transmitted by the computing device. The RF bandwidth is within the operating transmission bandwidth of the computing device. A signal interference having an interference bandwidth can interfere with the transmission of the one or more frames. In response to detecting the signal interference, one or more frames can be transmitted within the operating transmission bandwidth and not within the interference bandwidth.

Eugene Chai

Papers

RIO: A Pervasive RFID-based Touch Gesture Interface

SkyCore: Moving Core to the Edge for Untethered and Reliable UAV-based LTE Networks

LTE in unlicensed spectrum: are we there yet?

Tagtag: material sensing with commodity RFID

Transmitting a wireless signal based on detected signal interference