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The Open Radio Access Network (RAN) and its embodiment through the O-RAN Alliance specifications are poised to revolutionize the telecom ecosystem. O-RAN promotes virtualized RANs where disaggregated components are connected via open interfaces and optimized by intelligent controllers. The result is a new paradigm for the RAN design, deployment, and operations: O-RAN networks can be built with multi-vendor, interoperable components, and can be programmatically optimized through a centralized abstraction layer and data-driven closed-loop control. Therefore, understanding O-RAN, its architecture, its interfaces, and workflows is key for researchers and practitioners in the wireless community. In this article, we present the first detailed tutorial on O-RAN. We also discuss the main research challenges and review early research results. We provide a deep dive of the O-RAN specifications, describing its architecture, design principles, and the O-RAN interfaces. We then describe how the O-RAN RAN Intelligent Controllers (RICs) can be used to effectively control and manage 3GPP-defined RANs. Based on this, we discuss innovations and challenges of O-RAN networks, including the Artificial Intelligence (AI) and Machine Learning (ML) workflows that the architecture and interfaces enable, security, and standardization issues. Finally, we review experimental research platforms that can be used to design and test O-RAN networks, along with recent research results, and we outline future directions for O-RAN development. 

With the unprecedented rise in traffic demand and mobile subscribers, real-time fine-grained optimization frameworks are crucial for the future of cellular networks. Indeed, rigid and inflexible infrastructures are incapable of adapting to the massive amounts of data forecast for 5G networks. Network softwarization, i.e., the approach of controlling “everything” via software, endows the network with unprecedented flexibility, allowing it to run optimization and machine learning-based frame- works for flexible adaptation to current network conditions and traffic demand. This work presents QCell, a Deep Q-Network- based optimization framework for softwarized cellular networks. QCell dynamically allocates slicing and scheduling resources to the network base stations adapting to varying interference con- ditions and traffic patterns. QCell is prototyped on Colosseum, the world’s largest network emulator, and tested in a variety of network conditions and scenarios. Our experimental results show that using QCell significantly improves user’s throughput (up to 37.6%) and the size of transmission queues (up to 11.9%), decreasing service latency. 

The realization of efficient, robust, and adaptable applications for the emergent Internet of Underwater Things enables the sustainable and effective conservation and exploitation of our oceans and waterways. Recent advances have fo- cused on Orthogonal Frequency-Division Multiplexing (OFDM) physical layers for supporting applications requiring high data rates and swift adaptation to changing underwater conditions. This prompts the need of tools for testing new OFDM-enabled underwater solutions. To this aim, this paper presents the implementation and evaluation of an OFDM-based physical layer module for the popular underwater network simulator DESERT. We aim at modeling the flexibility of the software-defined acoustic SEANet modem by realizing OFDM features that can vary in time, including the number and the selection of subcarriers and their modulation on a per-transmission basis. We demonstrate the usage of the proposed module through the DESERT-based simulation of three simple OFDM-enabled cross-layer MAC protocols in underwater acoustic networks of different sizes. The diverse and detailed set of results are obtained by using our physical layer module simply and swiftly. Our results also confirm the advantages of using the OFDM technology in solutions for underwater networking in challenging environments. 

Recent years have seen the introduction of large- scale platforms for experimental wireless research. These platforms, which include testbeds like those of the PAWR program and emulators like Colosseum, allow researchers to prototype and test their solutions in a sound yet realistic wireless environment before actual deployment. Emulators, in particular, enable wire- less experiments that are not site-specific as those on real testbeds. Researchers can choose among different radio frequency (RF) scenarios for real-time emulation of a vast variety of different situations, with different numbers of users, RF bandwidth, antenna counts, hardware requirements, etc. Although very powerful, in that they can emulate virtually any real-world deployment, emulated scenarios are only as useful as how accurately they can capture the targeted wireless channel and environment. Achieving emulation accuracy is particularly challenging, especially for experiments at scale for which emulators require considerable amounts of computational resources. In this paper we propose a framework to create RF scenarios for emulators like Colosseum from rich forms of inputs, like those obtained by measurements through radio equipment or via software (e.g., ray-tracers and electromagnetic field solvers). Our framework optimally scales down the large set of RF data in input to the fewer parameters allowed by the emulator by using efficient clustering techniques and channel impulse response re-sampling. We showcase our method by generating wireless scenarios for Colosseum by using Remcom’s Wireless InSite, a commercial-grade ray-tracer that produces key characteristics of the wireless channel. Examples are provided for line-of-sight and non-line-of-sight scenarios on portions of the Northeastern University main campus. 

Underwater wireless communication and network- ing are becoming key enablers of a number of critical marine and underwater applications. Experimentation is underway, in controlled environments as well as at sea, that concerns the deployment of several underwater devices providing wireless communication capabilities to sensors of different nature. Con- trolling the deployment at sea of these devices, remotely and efficiently, is paramount for enabling expedite testing of hardware and protocol development. To address this need, this paper presents the design, development, and testing of a Smart Buoy for real-time remote access to underwater devices and for provision of power and extended computational capabilities. Experimental results are shown concerning the time needed to connect with the Smart Buoy, the power consumption of its operations, and the energy harvesting intake (via solar panels) in time. We also investigate the buoy lifetime when powered by solar panels and supporting acoustic modems over varying traffic scenarios. 

Underwater networks of wireless sensors deployed along the coast or in the deep water are the most promising solution for the development of underwater monitoring, exploration and surveillance applications. A key feature of underwater networks that can significantly enhance current monitoring applications is the ability to accommodate real-time video information on an underwater communication link. In fact, while today monitoring relies on the exchange of simple discrete information, e.g., water temperature, and particle concentration, among others, by introducing real-time streaming capability of non-static images between wireless underwater nodes one can completely revolutionize the whole underwater monitoring scenario. To achieve this goal, underwater links are required to support a sufficiently high data rate, compatible with the streaming rates of the transmitted video sequence. Unfortunately, the intrinsic characteristic of the underwater propagation medium has made this objective extremely challenging. In this paper, we present the first physical layer transmission scheme for short-range and high-data rate ultrasonic underwater communications. The proposed solution, which we will refer to as Underwater UltraSonar (U2S), is based on the idea of transmitting short information-bearing carrierless ultrasonic signals, e.g., pulses, following a pseudo-random adaptive time-hopping pattern with a superimposed rate-adaptive Reed-Solomon forward error correction (FEC) channel coding. We also present the design of the first prototype of a software-defined underwater ultrasonic transceiver that implements U2S PHY transmission scheme through which we evaluate the U2S performance in real-scenario underwater experiments at the PHY layer, i.e., Bit Error Rate (BER) extensively, and at the application layer, i.e., structural similarity (SSIM) index. Results show that U2S links can support point-to-point data rate up to 1.38 Mbps and that by leveraging the flexibility of the adaptive time-hopping and adaptive channel coding techniques, one can trade between link throughput and energy consumption, still satisfying application layer requirements.