Showing papers by "Neal Patwari published in 2010"

Radio Tomographic Imaging with Wireless Networks

Abstract: Radio Tomographic Imaging (RTI) is an emerging technology for imaging the attenuation caused by physical objects in wireless networks. This paper presents a linear model for using received signal strength (RSS) measurements to obtain images of moving objects. Noise models are investigated based on real measurements of a deployed RTI system. Mean-squared error (MSE) bounds on image accuracy are derived, which are used to calculate the accuracy of an RTI system for a given node geometry. The ill-posedness of RTI is discussed, and Tikhonov regularization is used to derive an image estimator. Experimental results of an RTI experiment with 28 nodes deployed around a 441 square foot area are presented.

High-Rate Uncorrelated Bit Extraction for Shared Secret Key Generation from Channel Measurements

Abstract: Secret keys can be generated and shared between two wireless nodes by measuring and encoding radio channel characteristics without ever revealing the secret key to an eavesdropper at a third location. This paper addresses bit extraction, i.e., the extraction of secret key bits from noisy radio channel measurements at two nodes such that the two secret keys reliably agree. Problems include 1) nonsimultaneous directional measurements, 2) correlated bit streams, and 3) low bit rate of secret key generation. This paper introduces high-rate uncorrelated bit extraction (HRUBE), a framework for interpolating, transforming for decorrelation, and encoding channel measurements using a multibit adaptive quantization scheme which allows multiple bits per component. We present an analysis of the probability of bit disagreement in generated secret keys, and we use experimental data to demonstrate the HRUBE scheme and to quantify its experimental performance. As two examples, the implemented HRUBE system can achieve 22 bits per second at a bit disagreement rate of 2.2 percent, or 10 bits per second at a bit disagreement rate of 0.54 percent.

RF Sensor Networks for Device-Free Localization: Measurements, Models, and Algorithms

Abstract: In this paper, we discuss the emerging application of device-free localization (DFL) using wireless sensor networks, which find people and objects in the environment in which the network is deployed, even in buildings and through walls. These networks are termed “RF sensor networks” because the wireless network itself is the sensor, using radio-frequency (RF) signals to probe the deployment area. DFL in cluttered multipath environments has been shown to be feasible, and in fact benefits from rich multipath channels. We describe modalities of measurements made by RF sensors, the statistical models which relate a person's position to channel measurements, and describe research progress in this area.

Robust uncorrelated bit extraction methodologies for wireless sensors

Abstract: This paper presents novel methodologies which allow robust secret key extraction from radio channel measurements which suffer from real-world non-reciprocities and a priori unknown fading statistics. These methodologies have low computational complexity, automatically adapt to differences in transmitter and receiver hardware, fading distribution and temporal correlations of the fading signal to produce secret keys with uncorrelated bits. Moreover, the introduced method produces secret key bits at a higher rate than has previously been reported. We validate the method using extensive measurements between TelosB wireless sensors.

Mobility Assisted Secret Key Generation Using Wireless Link Signatures

Abstract: We propose an approach where wireless devices, interested in establishing a secret key, sample the channel impulse response (CIR) space in a physical area to collect and combine uncorrelated CIR measurements to generate the secret key. We study the impact of mobility patterns in obtaining uncorrelated measurements. Using extensive measurements in both indoor and outdoor settings, we find that (i) when movement step size is larger than one foot the measured CIRs are mostly uncorrelated, and (ii) more diffusion in the mobility results in less correlation in the measured CIRs. We develop efficient mechanisms to encode CIRs and reconcile the differences in the bits extracted between the two devices. Our results show that our scheme generates very high entropy secret bits and that too at a high bit rate. The secret bits, that we generate using our approach, also pass the 8 randomness tests of the NIST test suite.

RF Sensor Networks for Device-Free Localization: Measurements, Models, and Algorithms This paper considers situations where a person or an object can be examinedVeven in buildings and through wallsVbecause a wireless network uses RF signals as a probe.

Abstract: In this paper, we discuss the emerging applica- tion of device-free localization (DFL) using wireless sensor networks, which find people and objects in the environment in which the network is deployed, even in buildings and through walls. These networks are termed ''RF sensor networks'' because the wireless network itself is the sensor, using radio- frequency (RF) signals to probe the deployment area. DFL in cluttered multipath environments has been shown to be feasible, and in fact benefits from rich multipath channels. We describe modalities of measurements made by RF sensors, the statistical models which relate a person's position to channel measurements, and describe research progress in this area.

Special issue on sensor network applications [Scanning the Issue]

Abstract: This special issue highlights the state-of-the-art enabling technologies which are critical to sensor networking and explores today?s application areas as well as expected future developments.

Channel Sounding for the Masses: Low Complexity GNU 802.11b Channel Impulse Response Estimation

Abstract: New techniques in cross-layer wireless networks are building demand for ubiquitous channel sounding, that is, the capability to measure channel impulse response (CIR) with any standard wireless network and node. Towards that goal, we present a software-defined IEEE 802.11b receiver and CIR estimation system with little additional computational complexity compared to 802.11b reception alone. The system implementation, using the universal software radio peripheral (USRP) and GNU Radio, is described and compared to previous work. By overcoming computational limitations and performing direct-sequence spread-spectrum (DS-SS) matched filtering on the USRP, we enable high-quality yet inexpensive CIR estimation. We validate the channel sounder and present a drive test campaign which measures hundreds of channels between WiFi access points and an in-vehicle receiver in urban and suburban areas.

Secret key extraction in MIMO-like sensor networks using wireless signal strength

Abstract: In this work, we evaluate the use of multiple sensors for secret key extraction. We find that the key generation rate increases linearly with the number of nodes. We show that the use of multiple nodes causes a significant mismatch in the extracted bits. We address the high bit mismatch problem by adding an iterative distillation stage to the key extraction process.

Keynote address: Building RF sensor networks

Abstract: An RF sensor network is a sensor network, which measures the radio frequency (RF) channel at its sensor nodes, and infers properties of the network or the surrounding environment. General wireless sensor networks sense using other modalities — an RF sensor network uses its radio as a sensor. Applications include sensor localization, network management, secret key establishment, and device-free localization. This talk will explore RF sensor network applications, with an emphasis on received-signal strength (RSS)-based device-free localization, that is, locating moving people and objects based on measurements of RSS between pairs of nodes in the sensor network. We will describe 1) new multipath channel fading models which provide the basis for our ability to accurately estimate a person's location; 2) algorithms for RSS-based device-free localization; and 3) lessons learned from prototype development and deployment.