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We present a set of experiments utilizing wideband real-time adaptive full-duplex (FD) radios, demonstrating simultaneous transmission and reception on the same frequency channel. Each FD radio consists of a circulator-based antenna interface, a switched-capacitor delay-line-based configurable Radio-Frequency Integrated Circuit (RFIC) that implements Self-Interference Cancellation (SIC), an FPGA that optimizes the RFIC configuration in under 1.1 sec and can adapt to environmental changes in under 0.3 sec, and a Software-Defined Radio (SDR) transmitting OFDM-like packets. We demonstrate a real-time adaptive FD radio that achieves the SIC necessary to reach the noise floor across a wide bandwidth of 50 MHz. Then, we use two FD radios to create a wireless link and showcase the superior FD throughput. 

Next generation wireless services and applications, including Augmented Reality, Internet-of-Things, and Smart- Cities, will increasingly rely on Dynamic Spectrum Access (DSA) methods that can manage spectrum resources rapidly and efficiently. Advances in regulatory policies, standardization, networking, and wireless technology are enabling DSA methods on a more granular basis in terms of time, frequency, and geographical location which are key for the operation of 5G and beyond-5G networks. In this context, this paper proposes a novel DSA algorithm that leverages IEEE 1900.5.2 Spectrum Consumption Models (SCMs) which offer a mechanism for RF devices to: (i) “announce” or “declare” their intention to use the spectrum and their needs in terms of interference protection; and (ii) determine compatibility (i.e., non-interference) with existing devices. In this paper, we develop an SCM-based DSA algorithm for spectrum deconfliction in large-scale wireless network environments and evaluate this algorithm in terms of computation time, efficiency of spectrum allocation, and number of device reconfigurations due to interference using a custom simulation platform. The results demonstrate the benefits of using SCMs and their capabilities to perform fine grained spectrum assignments in dynamic and dense communication environments. 

4G, 5G, and smart city networks often rely on microwave and millimeter-wave x-haul links. A major challenge associated with these high frequency links is their susceptibility to weather conditions. In particular, precipitation may cause severe signal attenuation, which significantly degrades the network performance. In this paper, we develop a Predictive Network Reconfiguration (PNR) framework that uses historical data to predict the future condition of each link and then prepares the network ahead of time for imminent disturbances. The PNR framework has two components: (i) an Attenuation Prediction (AP) mechanism; and (ii) a Multi-Step Network Reconfiguration (MSNR) algorithm. The AP mechanism employs an encoder-decoder Long Short-Term Memory (LSTM) model to predict the sequence of future attenuation levels of each link. The MSNR algorithm leverages these predictions to dynamically optimize routing and admission control decisions aiming to maximize network utilization, while preserving max-min fairness among the nodes using the network (e.g., base-stations) and preventing transient congestion that may be caused by switching routes. We train, validate, and evaluate the PNR framework using a dataset containing over 2 million measurements collected from a real-world city-scale backhaul network. The results show that the framework: (i) predicts attenuation with high accuracy, with an RMSE of less than 0.4 dB for a prediction horizon of 50 seconds; and (ii) can improve the instantaneous network utilization by more than 200% when compared to reactive network reconfiguration algorithms that cannot leverage information about future disturbances. 

Outdoor-to-indoor (OtI) signal propagation further challenges link budgets at millimeter-wave (mmWave). To gain insight into OtI mmWaveat28GHz, we conducted an extensive measurement campaign consisting of over 2,000 link measurements in West Harlem, NewYorkCity, covering seven highly diverse buildings. A path loss model constructed over all links shows an average of 30dB excess loss over free space at distances beyond 50m. We find the type of glass to be the dominant factor in OtI loss, with 20dB observed difference between clustered scenarios with low- and high-loss glass. Other factors, such as difference in floor height, are found to have an impact between 5ś10dB. We show that for urban buildings with high-loss glass, OtI data rates up to 400Mb/s are supported for 90% of indoor users by a base station (BS) up to 49m away. For buildings with low-loss glass, such as our case study covering multiple classrooms of a public school, data rates over 2.8/1.4Gb/s are possible from a BS 68/175m away when a line-of-sight path is available. We expect these results to be useful for the deployment of OtI mmWave networks in dense urban environments and the development of scheduling and beam management algorithms. 

This paper describes a wireless experimentation framework for studying dynamic spectrum access mechanisms and an experiment that showcases its capabilities. The framework was built on COSMOS, an advanced wireless testbed designed to support real-world experimentation of next generation wireless technologies and applications. Our deployed framework supports experimentation over a large number of wireless networks, with a PUB-SUB based network interaction structure, based on the Collaborative Intelligent Radio Networks (CIRN) Interaction Language (CIL) developed by DARPA for the Spectrum Collaboration Challenge (SC2). As such, it enables interaction and message exchanges between the networks for the purposes of coordinating spectrum use. For our experiment, the message exchanges are aimed primarily for, but not limited to, Spectrum Consumption Model (SCM) messages. RF devices/systems use SCM messages which contain detailed information about their wireless transmission characteristics (i.e., spectrum mask, frequency, bandwidth, power and location) to determine their operational compatibility (non-interference) with prior transmitters and receivers, and to dynamically determine spectrum use characteristics for their own transmissions.