Impulse Radio Ultra-Wideband Ranging Algorithm under Multi User Environments

Practical impulse radio ultra-wideband (IR-UWB) ranging systems always have to work in multi-user and weak non-line-of-sight (NLOS) environments. In this paper, we derive a novel IR-UWB ranging estimator under multi-user and weak NLOS environments. We model MUI with complex Gaussian mixture model (CGMM) in the frequency domain. We propose a novel estimator for the UWB time of arrival (ToA) parameters based on the expectation maximization (EM) algorithm, the pseudo quadratic maximum likelihood (PQML) algorithm and CGMM. The estimator reduce the MUI in the frequency domain so that the cost function becomes asymptotically noiseless. Ranging is obtained by translating the obtained delay estimates into an estimate of the distance. And numerical evaluations under IEEE 802.15.3a channel model are presented to demonstrate the good performance of the proposed estimator.

One Step Impulse Radio Ultra-WideBand Positioning Algorithm

John Farserotu, Jean-Yves Le Boudec, Hai Zhan

We consider the problem of positioning estimation with impulse radio (IR) ultra-wideband (UWB) radio under dense multipaths and additive Gaussian noise environments. Most popular positioning algorithms first estimate certain parameters (such as time of arrival (TOA), angle of arrival (AOA) and time difference of arrival (TDOA)) from the received signals. These parameters are then used to estimate the targeted position. In practice, the estimation of these parameters is not errors free and the distribution of the errors is difficult to model exactly. In contrast, we propose a novel one-step approach, which estimates the position and channels directly and jointly from the received signals of the used base stations. We use a Bayesian approach where the prior distribution of the channels follows the IEEE 802.15.4a channel model to estimate the joint posterior probability density function (pdf) of the channels, the targeted position and the transmit time. One application of the joint posterior pdf of the channels, the targeted position and the transmit time is the position determination with classical posterior estimator (such as minimum mean square error estimator (MMSE)). For computing the joint posterior pdf of the channels, the targeted position and the transmit time, we derived an algorithm which is based on sampling-importance resampling and the expectation maximization technique. Furthermore, we propose a reduced-complexity architecture of the proposed IR UWB localization system using our proposed algorithm. The algorithm can be easily implemented on hardware. Numerical evaluations under the IEEE 802.15.4a channel model are presented to demonstrate the good performance of the proposed estimator.

IEEE2009

A Novel Bayesian Impulse Radio Ultra-WideBand Ranging Algorithm

John Farserotu, Jean-Yves Le Boudec, Hai Zhan

We consider the problem of ranging with Impulse Radio (IR) Ultra-WideBand (UWB) radio under weak Line Of Sight (LOS) environments and additive Gaussian noise. We use a Bayesian approach where the prior distribution of the channel follows the IEEE 802.15.4a channel model, to estimate the joint posterior probability density function (pdf) of the channel and the targeted distance. One of applications of the joint posterior pdf of the channel and the targeted distance is the ranging determination with classical posterior estimators (such as Minimum Mean Square Error Estimator (MMSE)). For computing the joint posterior pdf of the channel and the targeted distance, we derived a novel algorithm which is based on importance sampling and expectation maximum techniques. Furthermore, we propose a reduced-complexity architecture of IR UWB ranging system using our proposed algorithm. The complexity analysis of the algorithm shows the proposed algorithm is a low-complexity one. Numerical evaluations under the IEEE 802.15.4a channel model are presented to demonstrate the good performance of the proposed estimator.

IEEE2009

Cooperative Data Exchange and Private Information Retrieval

Su Li

Coding techniques have been well studied and used for improving communication quality by combating noise and mitigating interference. Recently, it has been shown that the same coding techniques can also be exploited to further improve communication performance and provide specific communication features even when the communication channel is ideal. In this thesis, we study two problems where coding techniques are used for improving communications in distributed systems and protecting the privacy of the client from untrusted servers, respectively.\ The first part of this thesis studies the cooperative data exchange problem for fully connected networks. While many previous studies have shown that the problem can be solved by algorithms based on submodular function minimization, we tackle this problem via a concept we refer to as "conditioning basis", which is closely linked to linear coding schemes with particular additional properties. We show that such special linear coding schemes are optimal for the cooperative data exchange problem. Hence, by searching the existence of such a conditioning basis and special linear coding schemes, we can solve this problem with lower complexity. We propose a deterministic algorithm for this problem and briefly show how to construct the optimal linear coding schemes starting from a Vandermonde matrix. Moreover, we show that our new method can be used to solve two generalized problems, which are cooperative data exchange with weighted cost and successive local omniscience problems.\ The second part of this thesis investigates the problem of private information retrieval with side information. Specifically, three different extensions are studied: multi-message, multi-server, and multi-user, respectively. For each problem, we provide a proof of the converse for the download rate as well as propose efficient approaches to construct optimal coding schemes. For multi-message and multi-server cases, we give closed-form expressions for the download rates and introduce two useful tools, {\it conditioning answer string} and {\it virtual private information}, to analyze the problem. For multi-user cases, we show that the optimal download rate can be obtained by solving an optimization problem over all partitions of the total number of messages and propose a novel algorithm based on dynamic programming to solve the optimization problem.\

EPFL2020

Cooperative Data Exchange and Private Information Retrieval

Su Li

EPFL2020