Location-aware technologies will revolutionize many aspects of commercial, public service, and military sectors, and are expected to spawn numerous unforeseen applications. A new era of highly accurate ubiquitous location-awareness is on the horizon, enabled by a paradigm of cooperation between nodes. In this paper, we give an overview of cooperative localization approaches and apply them to ultrawide bandwidth (UWB) wireless networks. UWB transmission technology is particularly attractive for short- to medium-range localization, especially in GPS-denied environments: wide transmission bandwidths enable robust communication in dense multipath scenarios, and the ability to resolve subnanosecond delays results in centimeter-level distance resolution. We will describe several cooperative localization algorithms and quantify their performance, based on realistic UWB ranging models developed through an extensive measurement campaign using FCC-compliant UWB radios. We will also present a powerful localization algorithm by mapping a graphical model for statistical inference onto the network topology, which results in a net-factor graph, and by developing a suitable net-message passing schedule. The resulting algorithm (SPAWN) is fully distributed, can cope with a wide variety of scenarios, and requires little communication overhead to achieve accurate and robust localization.

Cooperative Localization in Wireless Networks

In this paper, we present space shift keying (SSK) as a new modulation scheme, which is based on spatial modulation (SM) concepts. Fading is exploited for multiple-input multiple-output(MIMO) channels to provide better performance over conventional amplitude/phase modulation (APM) techniques. In SSK, it is the antenna index used during transmission that relays information, rather than the transmitted symbols themselves. This absence of symbol information eliminates the transceiver elements necessary for APM transmission and detection (such as coherent detectors). As well, the simplicity involved in modulation reduces the detection complexity compared to that of SM, while achieving almost identical performance gains. Throughout the paper, we illustrate SSK's strength by studying its interaction with the fading channel. We obtain tight upper bounds on bit error probability, and discuss SSK's performance under some non-ideal channel conditions (estimation error and spatial correlation). Analytical and simulation results show performance gains over APM systems (3 dB at a bit error rate of 10-5), making SSK an interesting candidate for future wireless applications. We then extend SSK concepts to incorporate channel coding, where in particular, we consider a bit interleaved coded modulation (BICM) system using iterative decoding for both convolutional and turbo codes. Capacity results are derived, and improvements over APM are illustrated (up to 1 bits/s/Hz), with performance gains of up to 5 dB.

/pdf/space-shift-keying-modulation-for-mimo-channels-4za6dmyo4w.pdf

Space shift keying modulation for MIMO channels

Over the coming decades, high-definition situationally-aware networks have the potential to create revolutionary applications in the social, scientific, commercial, and military sectors Ultrawide bandwidth (UWB) technology is a viable candidate for enabling accurate localization capabilities through time-of-arrival (TOA)-based ranging techniques These techniques exploit the fine delay resolution property of UWB signals by estimating the TOA of the first signal path Exploiting the full capabilities of UWB TOA estimation can be challenging, especially when operating in harsh propagation environments, since the direct path may not exist or it may not be the strongest In this paper, we first give an overview of ranging techniques together with the primary sources of TOA error (including propagation effects, clock drift, and interference) We then describe fundamental TOA bounds (such as the Cramer-Rao bound and the tighter Ziv-Zakai bound) in both ideal and multipath environments These bounds serve as useful benchmarks in assessing the performance of TOA estimation techniques We also explore practical low-complexity TOA estimation techniques and analyze their performance in the presence of multipath and interference using IEEE 802154a channel models as well as experimental data measured in indoor residential environments

/pdf/ranging-with-ultrawide-bandwidth-signals-in-multipath-illizjdvoz.pdf

Ranging With Ultrawide Bandwidth Signals in Multipath Environments

The availability of position information is of great importance in many commercial, public safety, and military applications. The coming years will see the emergence of location-aware networks with submeter accuracy, relying on accurate range measurements provided by wide bandwidth transmissions. In this two-part paper, we determine the fundamental limits of localization accuracy of wideband wireless networks in harsh multipath environments. We first develop a general framework to characterize the localization accuracy of a given node here and then extend our analysis to cooperative location-aware networks in Part II. In this paper, we characterize localization accuracy in terms of a performance measure called the squared position error bound (SPEB), and introduce the notion of equivalent Fisher information (EFI) to derive the SPEB in a succinct expression. This methodology provides insights into the essence of the localization problem by unifying localization information from individual anchors and that from a priori knowledge of the agent's position in a canonical form. Our analysis begins with the received waveforms themselves rather than utilizing only the signal metrics extracted from these waveforms, such as time-of-arrival and received signal strength. Hence, our framework exploits all the information inherent in the received waveforms, and the resulting SPEB serves as a fundamental limit of localization accuracy.

Fundamental Limits of Wideband Localization— Part I: A General Framework

This paper presents an overview of ultrawideband (UWB) propagation channels. It first demonstrates how the frequency selectivity of propagation processes causes fundamental differences between UWB channels and "conventional" (narrowband) channels. The concept of pathloss has to be modified, and the well-known WSSUS model is not applicable anymore. The paper also describes deterministic and stochastic models for UWB channels, identifies the key parameters for the description of delay dispersion, attenuation, and directional characterization, and surveys the typical parameter values that have been measured. Measurement techniques and methods for extracting model parameters are also different in UWB channels; for example, the concepts of narrowband channel parameter estimation (e.g., maximum-likelihood estimation) have to be modified. Finally, channel models also have an important impact on the performance evaluation of various UWB systems.

Ultrawideband propagation channels-theory, measurement, and modeling

A comprehensive statistical model is described for ultrawideband (UWB) propagation channels that is valid for a frequency range from 3-10 GHz. It is based on measurements and simulations in the following environments: residential indoor, office indoor, builtup outdoor, industrial indoor, farm environments, and body area networks. The model is independent of the used antennas. It includes the frequency dependence of the path gain as well as several generalizations of the Saleh-Valenzuela model, like mixed Poisson times of arrival and delay-dependent cluster decay constants. A separate model is specified for the frequency range below 1 GHz. The model can thus be used for realistic performance assessment of UWB systems. It was accepted by the IEEE 802.15.4a Task Group as standard model for evaluation of UWB system proposals. This paper also presents a critical assessment of the applicability of the model and possible generalizations and improvements

/pdf/a-comprehensive-standardized-model-for-ultrawideband-5f122zska0.pdf

A Comprehensive Standardized Model for Ultrawideband Propagation Channels

This paper describes a comprehensive statistical model for UWB propagation channels that is valid for a frequency range from 3-10 GHz. It is based on measurements and simulations in the following environments: residential indoor, office indoor, built-up outdoor, industrial indoor, farm environments, and body area networks. The model is independent of the used antennas. It includes the frequency dependence of the pathloss, as well as several generalizations of the Saleh-Valenzuela model, like mixed Poisson times of arrival and delay dependent cluster decay constants. The model can thus be used for realistic performance assessment of UWB systems. It was accepted by the IEEE 802.15.4a working group (WG) as standard model for evaluation of UWB system proposals

/pdf/a-comprehensive-model-for-ultrawideband-propagation-channels-2edixb00xk.pdf

A comprehensive model for ultrawideband propagation channels

This paper suggests an innovative approach to define and perform tests of communication systems in cars. The test concept requires the placement of the vehicle under test on a planar turntable in an anechoic chamber. Software-defined multimode transceiver modules, referred to as radio heads, are placed in a quarter circle or half circle around the car at an adequate distance. This setup allows flexible, realistic, reproducible and dynamic over-the-air testing of the cars communication systems in the sense of a virtual drive test. One key topic - which is still open - is the definition of sufficiently realistic test scenarios related to real outdoor scenarios. The full description of those scenarios would require a prohibitively large number of parameters from the network and the channel to be considered, making it impractical to perform this derivation following a classical straight-forward approach. Therefore, this paper suggests the derivation of realistic test cases via a machine learning (ML) approach: instead of attempting to create a 1:1 mapping of real scenarios into the test chamber, we propose to use ML to identify and classify critical test cases via analysis of key performance indicators (KPI) of test data and from this to create representative synthetic test cases. This approach is currently under development and open for discussion here.

Automotive Performance Tests Based on Machine Learning Algorithms

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A Comprehensive Standardized Model for Ultrawideband Propagation Channels

A comprehensive model for ultrawideband propagation channels

Automotive Performance Tests Based on Machine Learning Algorithms