Abstract-This paper introduces the notion of network experimentation and proposes an experimentation methodology particularly suited for cooperative wireless networks. Based on this methodology we performed extensive measurement campaigns and compare various cooperative localization techniques under a common setting. Network experiments enable (i) the quantification of cooperation benefits, (ii) the development of techniques for harnessing environmental information, and (iii) the characterization of network localization algorithms. As a case study, we consider ultrawide bandwidth cooperative locationaware networks in cluttered indoor environments and evaluate their performance based on measurements collected from network experiments.

This paper considers a scenario where a reconfigurable intelligent surface (RIS) is deployed to allow the localization of mobile users adopting a single anchor node, even under non-line-of-sight (NLOS) channel conditions. When the RIS is large and the operating frequency is high, as in the millimeter-wave band, the system is likely to operate in the near-field propagation regime, which can be exploited to obtain robust localization. To this purpose, two practical signaling and positioning algorithms, based on an orthogonal frequency division multiplexing (OFDM) downlink system, are proposed along with methods to design the RIS time-varying reflection coefficients. In the numerical results, the two algorithms are compared in terms of performance in the presence of a synchronization mismatch and considering trade-offs between bandwidth, overhead, operating frequency, and latency. Finally, we provide an analysis of the soft-coverage capability, i.e., on the possibility of maintaining a high level of localization accuracy when in the presence of increasing levels of obstruction of the RIS.

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Passive and semipassive ultrawideband (UWB) radio-frequency identification (RFID) technology has been recently proposed to offer high-accuracy localization capabilities in next-generation RFID systems. This technology relies on the modulation of backscattered signals, i.e., backscatter modulation, from multiple tags present in the environment. The detection of multiple tags based on backscattered signals is challenging in harsh environments with nonideal conditions such as clutter, near–far interference effects, and clock drift. This paper analyzes the detection of multiple tags employing UWB backscatter modulation and proposes practical signaling, spreading codes, and detection schemes that are robust to nonideal conditions. A case study is presented to evaluate the performance of the proposed technique for the detection of multiple tags based on impulsive backscattered signals

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International audienceIn the new scenarios foreseen by the Internet of Things, industrial and commercial systems will be required to detect and localize tagged items with high accuracy, as well as to monitor the level of certain parameters of interest through the deployment of wireless sensors. To meet these challenging requirements, the adoption of passive and semi-passive ultra-wideband (UWB) radio-frequency identification (RFID) appears a promising solution which overcomes the limitations of standard Gen.2 ultra-high frequency (UHF) RFID. The design and implementation of such systems pose several practical constraints, impacting the overall network architecture. In this paper, the main issues and challenging aspects for the design of a UWB-RFID network considering architectural and protocol choices are discussed in a unitary framework, and practical solutions, accounting for the presented issues, are proposed. Moreover, the possible integration of UWB-RFID with standard Gen.2 UHF-RFID is proposed as an interesting option, discussing architectural solutions, their advantages and drawbacks

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Abstract-In this paper the problem of detecting the channel state between LOS and NLOS conditions is addressed using UWB signals. A new distribution-based identification approach is proposed and its performance is compared with that of other classic schemes. To this purpose experimental data collected in realistic environments have been used.