Over the last few years, the convincing forward steps in the development of Internet-of-Things (IoT) enabling solutions are spurring the advent of novel and fascinating applications. Among others, mainly Radio Frequency Identification (RFID), Wireless Sensor Network (WSN), and smart mobile technologies are leading this evolutionary trend.In the wake of this tendency, this paper proposes a novel, IoTaware, smart architecture for automatic monitoring and tracking of patients, personnel, and biomedical devices within hospitals and nursing institutes. Staying true to the IoT vision, we propose a Smart Hospital System (SHS) which relies on different, yet complementary, technologies, specifically RFID, WSN, and smart mobile, interoperating with each other through a CoAP/6LoWPAN/REST network infrastructure. The SHS is able to collect, in real time, both environmental conditions and patients' physiological parameters via an ultra-low-power Hybrid Sensing Network (HSN) composed of 6LoWPAN nodes integrating UHF RFID functionalities. Sensed data are delivered to a control center where an advanced monitoring application makes them easily accessible by both local and remote users via a REST web service. The simple proof of concept implemented to validate the proposed SHS has highlighted a number of key capabilities and aspects of novelty which represent a significant step forward compared to the actual state of art. support and improve healthcare and biomedical-related processes [2]. Automatic identification and tracking of people and biomedical devices in hospitals, correct drug-patient associations, real-time monitoring of patients' physiological parameters for early detection of clinical deterioration are only a few of the possible examples.Among others, Ultra-High-Frequency (UHF) Radio Frequency Identification (RFID), Wireless Sensor Network (WSN), and smart mobile represent three of the most promising technologies enabling the implementation of smart healthcare systems. RFID is a low-cost, low-power technology consisting of passive and/or battery-assisted passive (BAP) devices, named tags, which are able to transmit data when powered by the electromagnetic field generated by an interrogator, named reader. Since passive RFID tags do not need a source of energy to operate, their lifetime can be measured in decades, thus making the RFID technology well suited in a variety of application scenarios, including the healthcare one [3]- [5]. The recent availability of UHF RFID tags with increased capabilities, e.g. sensing and computation [6]-[8], represents a further added value. In fact, RFID-based sensing in healthcare enables zero-power, low-cost, and easyto-implement monitoring and transmission of patients' physiological parameters. Nevertheless, the main drawback of RFID tags stems from the fact that they can operate solely under the reader coverage region, i.e. up to 15 m and 25 m when respectively fully-passive and BAP tags are used. Clearly, such an aspect limits the use of UHF RFID technology to object/patient identific...

Abstract-In order to cope with the severe path loss, millimeter-wave (mm-wave) systems exploit highly directional communication. As a consequence, even a slight beam misalignment between two communicating devices (for example, due to mobility) can generate a significant signal drop. This leads to frequent invocations of time-consuming mechanisms for beam re-alignment, which deteriorate system performance. In this paper, we propose smart beam training and tracking strategies for fast mm-wave link establishment and maintenance under node mobility. We leverage the ability of hybrid analogdigital transceivers to collect channel information from multiple spatial directions simultaneously and formulate a probabilistic optimization problem to model the temporal evolution of the mmwave channel under mobility. In addition, we present for the first time a beam tracking algorithm that extracts information needed to update the steering directions directly from data packets, without the need for spatial scanning during the ongoing data transmission. Simulation results, obtained by a custom simulator based on ray tracing, demonstrate the ability of our beam training/tracking strategies to keep the communication rate only 10% below the optimal bound. Compared to the state of the art, our approach provides a 40% to 150% rate increase, yet requires lower complexity hardware.

Millimeter-wave (mm-wave) communication systems can provide much higher data rates than systems operating at lower frequencies, but achieving such rates over sufficiently large distances requires highly directional beamforming at both the transmitter and receiver. These antenna beams have to be aligned very precisely in order to obtain sufficient link margin. In this paper, we first propose a parallel-adaptive beam training protocol which significantly accelerates the link establishment between mm-wave devices by exploiting the ability of hybrid analog-digital beamforming antennas to scan multiple spatial sectors simultaneously. Second, we deal with practical constraints of mm-wave transceivers and design a novel greedy geometric algorithm to synthesize sector beam patterns featuring configurable beamwidth and multi-beam radiation as required by the proposed beam training protocol. These multi-beam patterns are then also used for concurrent data communication over multiple paths, in case several suitable directions are found during the beam training. Simulation results show that our algorithm is able to shape antenna patterns very close to those attained by a fullydigital beamforming architecture, yet requires lower complexity hardware compared with state-of-the-art solutions. Exploiting such multi-beam antenna patterns, our parallel beam training protocol can provide up to 82% effective rate increase and 70% search time decrease compared to existing sequential protocols. The acceleration of the beam training phase shifts the optimum balance between the search overhead and the achieved directivity gain so that the best performance is reached with a training load 30% to 60% lower than that of sequential beam training. Index Terms-Millimeter wave systems, hybrid beamforming, beam training, channel estimation, antenna patterns.

Millimeter wave (mmWave) wireless technologies are expected to exploit large-scale multiple-input multiple-output and adaptive antenna arrays at both the transmitter and receiver to deal with unfavorable radio propagation and realize sufficient link margin. However, the high cost and power consumption of mmWave radio components prohibit the use of fully-digital precoding/combining architectures, which incurs one dedicated RF chain per antenna element. This paper proposes a practical design of multi-beamwidth codebook exploiting hybrid analogdigital architectures with a number of RF chains much lower than the number of antenna elements and 2-bit RF phase shifters. The proposed solution relies on the orthogonal matching pursuit algorithm enhanced by a dynamic dictionary learning mechanism. Simulation results show that the designed hybrid codebooks are able to shape beam patterns very close to those attained by a fully-digital beamforming architecture. Furthermore, when leveraged in the framework of an adaptive, multiresolution beam training protocol, our hybrid codebooks are able to estimate the most promising angle-of-departure and angle-ofarrival directions with extreme accuracy, yet requiring lower complexity hardware compared to the state of art.