Wide-ranging applications for underwater acoustic communication are attracting attention. However, the challenges of underwater acoustic communications make it necessary to advance communication techniques significantly. Underwater networks with wider coverage areas and more reliable communication links may be possible with the distributed deployment of several reception nodes. Using Single Input Multiple Output (SIMO) systems, power, and bandwidth resources can be utilized effectively without compromising spectral efficiency. In this work, we propose a communication system that employs software- defined distributed SIMO networking to exploit the spatial diversity of multiple receiver nodes for high data rates and reliable communication. To take advantage of spatial diversity, we develop and implement a software-defined architecture for the maximal-ratio combining receiver. Then, we conduct a thorough experimental evaluation in ocean environments for various subcarrier bandwidths and constellations using three distributed receivers. Our results show that our proposed distributed SIMO system, for both 1x2 and 1x3 settings, outperforms individual receiver modems in terms of bit error rate (BER) performance by 95.20% and 99.57%, respectively.

Underwater acoustic communication and networking have been instrumental in enabling various commercial and military applications such as underwater surveillance, environmental monitoring, data-driven intelligent aquaculture, and unmanned underwater vehicles. However, the development of an underwater communication and networking system poses significant challenges due to spatially and temporally varying underwater acoustic channels. These channels are subject to severe multipath propagation and the Doppler effect, which can impose frequency-dependent distortions on underwater acoustic signals through frequency shifts and spreading. In high-frequency underwater acoustic communication systems, the Doppler effect is amplified, making its estimation and compensation even more challenging. In this paper, we present a detailed set of field experiments characterizing the Doppler effect in a high-frequency underwater acoustic channel. We also introduce a multicarrier communication system incorporating a Doppler estimation and compensation method. Through extensive field experiments, we quantify the performance of the Doppler estimation and compensation technique over high-frequency channels.

Carrierless Amplitude and Phase (CAP) modulation has been widely used in the emerging visible light communication (VLC) paradigm. Compared to other modulation schemes, CAP is in fact known to be comparatively easy to implement, to have lower computational complexity, high spectral efficiency, and superior noise performance. However, as of today, how to select optimal parameters in CAP links for a desired target bit error rate (BER) performance and spectral efficiency requirements is still an open problem, because of the absence of closed-form expressions for the bit error probability under different signal-to-noise ratio (SNR) conditions. In this article, we present a comprehensive analysis on the impact of different CAP parameters on the bit error probability under different noise levels. We first describe the system model and derive a theoretical expression for the bit error rate of a CAP-modulated communication system. Then, we present detailed simulation and experimental results for different CAP parameters. The derived theoretical expression is also validated through simulations and experiments for each different CAP parameter. Then, with this expression, we show how to select optimal link parameters for different noise levels, by maximizing the spectral efficiency while keeping the BER lower than a predefined threshold.

Underwater vehicles (UVs) are becoming essential for a vast range of novel commercial, scientific and military applications. These include seabed exploration, monitoring of critical infrastructure and resources, and coastal surveillance. However, usage of UVs is currently beset by limitations preventing them to carry critical equipment, such as agile wireless communication systems, which would facilitate and enable those applications. To overcome these limitations, in this paper we present the design blueprint and evaluation of a wireless UV, obtained by integrating a custom software-defined underwater acoustic networking platform integrated to a UV. We first describe the integration of the platform with a commercially available UV. We then present results from experimental campaigns at sea using our wireless UV to generate datasets for studying the Doppler effect due to mobility. Our results indicate the effectiveness of our design for ease of deployment and dataset generation.

The Internet of Underwater Things (IoUT) will enable new military, scientific, and commercial applications at sea. However, powering of electronic devices in deep water still remains one of the main challenges, since these systems are typically powered by traditional batteries. This article presents the design of the first batteryless underwater sensor node that can be wirelessly recharged through ultrasonic waves from longer distances than allowed by current technologies. First, the architecture of an underwater platform capable of extracting electrical energy from ultrasonic waves is introduced. We then illustrate how to interface this system with an underwater digital communication unit. We discuss the design of a prototype where the storage unit is realized with a batch of supercapacitors. We show through experiments that the harvested energy is sufficient to provide the sensor node with the power necessary to perform a sensing operation and power a modem for ultrasonic communications. In the article, we evaluate the system power transfer efficiency. Given the reduced attenuation of ultrasonic waves in water, we show that our approach can cover longer distances with less transmission power than alternative solutions. Last, we experimentally evaluate the overall operating efficiency of the system.

Autonomous networks of sensors, unmanned aerial vehicles (UAVs) and unmanned underwater vehicles (UUVs) will play a vital role in scenarios/applications where a plethora of distributed assets across multiple domains – air and water - operate in unison to accomplish a common goal. However, establishing high data rate, robust, and bi-directional communication links across the air-water interface between aerial and underwater assets is still an open problem. In this article, we propose a communication system based on visible (blue) light that enables aerial and underwater assets to establish bi-directional links through the air-water interface without requiring any preexisting communication infrastructure such as buoys acting as relay nodes. We first derive a mathematical model and accordingly build a simulator for the bi-directional air-water visible light communication (VLC) channel accounting for water surface distribution, optical parameters and path losses. Then, we design and prototype a software-defined visible light communication (VLC) modem. We present an extensive experimental evaluation conducted both in a test tank and in the ocean using the proposed VLC modem prototypes.

This article investigates the basic design principles for a new Wireless Network Operating System (WNOS), a radically different approach to software-defined networking (SDN) for infrastructure-less wireless networks. Departing from well-understood approaches inspired by OpenFlow, WNOS provides the network designer with an abstraction hiding (i) the lower-level details of the wireless protocol stack and (ii) the distributed nature of the network operations. Based on this abstract representation, the WNOS takes network control programs written on a centralized, high-level view of the network and automatically generates distributed cross-layer control programs based on distributed optimization theory that are executed by each individual node on an abstract representation of the radio hardware. We first discuss the main architectural principles of WNOS. Then, we discuss a new approach to automatically generate solution algorithms for each of the resulting subproblems in an automated fashion. Finally, we illustrate a prototype implementation of WNOS on software-defined radio devices and test its effectiveness by considering specific cross-layer control problems. Experimental results indicate that, based on the automatically generated distributed control programs, WNOS achieves 18%, 56% and 80.4% utility gain in networks with low, medium and high levels of interference; maybe more importantly, we illustrate how the global network behavior can be controlled by modifying a few lines of code on a centralized abstraction.

Networks of Unmanned Aerial Vehicles (UAVs), composed of hundreds, possibly thousands of highly mobile and wirelessly connected flying drones will play a vital role in future Internet of Things (IoT) and 5G networks. However, how to control UAV networks in an automated and scalable fashion in distributed, interference-prone, and potentially adversarial environments is still an open research problem. This article introduces SwarmControl, a new software-defined control framework for UAV wireless networks based on distributed optimization principles. In essence, SwarmControl provides the Network Operator (NO) with a unified centralized abstraction of the networking and flight control functionalities. High-level control directives are then automatically decomposed and converted into distributed network control actions that are executed through programmable software-radio protocol stacks. SwarmControl (i) constructs a network control problem representation of the directives of the NO; (ii) decomposes it into a set of distributed sub-problems; and (iii) automatically generates numerical solution algorithms to be executed at individual UAVs.We present a prototype of an SDR-based, fully reconfigurable UAV network platform that implements the proposed control framework, based on which we assess the effectiveness and flexibility of SwarmControl with extensive flight experiments. Results indicate that the SwarmControl framework enables swift reconfiguration of the network control functionalities, and it can achieve an average throughput gain of 159% compared to the state-of-the-art solutions.

This article studies an essential yet challenging problem in 5G wireless networks: Is it possible to enable spectrally-efficient spectrum sharing for heterogeneous wireless networks with different, possibly incompatible, spectrum access technologies on the same spectrum bands; without modifying the protocol stacks of existing wireless networks? To answer this question, this article explores the system challenges that need to be addressed to enable a new spectrum sharing paradigm based on beamforming, which we refer to as CoBeam. In CoBeam, a secondary wireless network is allowed to access a spectrum band based on cognitive beam-forming without mutual temporal exclusion, i.e., without interrupting the ongoing transmissions of coexisting wireless networks on the same bands; and without cross-technology communication. We first describe the main components of CoBeam, including programmable physical layer driver, cognitive sensing engine, and beamforming engine, and then we showcase the potential of the CoBeam framework by designing a practical coexistence scheme between Wi-Fi and LTE on unlicensed bands. We present a prototype of the resulting coexisting Wi-Fi/U-LTE network built on off-the-shelf software radios based on which we evaluate the performance of CoBeam through an extensive experimental campaign. Performance evaluation results indicate that CoBeam can achieve on average 169% throughput gain while requiring no signaling exchange between the coexisting wireless networks.

Current cellular networks rely on closed and inflexible infrastructure tightly controlled by a handful of vendors. Their configuration requires vendor support and lengthy manual operations, which prevent Telco Operators (TOs) from unlocking the full network potential and from performing fine grained performance optimization, especially on a per-user basis. To address these key issues, this paper introduces CellOS, a fully automated optimization and management framework for cellular networks that requires negligible intervention (“zero-touch”). CellOS leverages softwarization and automatic optimization principles to bridge Software-Defined Networking (SDN) and cross-layer optimization. Unlike state-of-the-art SDN-inspired solutions for cellular networking, CellOS: (i) Hides low-level network details through a general virtual network abstraction; (ii) allows TOs to define high-level control objectives to dictate the desired network behavior without requiring knowledge of optimization techniques, and (iii) automatically generates and executes distributed control programs for simultaneous optimization of heterogeneous control objectives on multiple network slices. CellOS has been implemented and evaluated on an indoor testbed with two different LTE-compliant implementations: OpenAirInterface and srsLTE. We further demonstrated CellOS capabilities on the long-range outdoor POWDER-RENEW PAWR 5G platform. Results from scenarios with multiple base stations and users show that CellOS is platform-independent and self-adapts to diverse network deployments. Our investigation shows that CellOS outperforms existing solutions on key metrics, including throughput (up to 86% improvement), energy efficiency (up to 84%) and fairness (up to 29%).

Indoor Visible Light Communications (VLC) are a promising technology to alleviate the looming spectrum crunch crisis in traditional RF spectrum bands. This article studies how to provide throughput-optimal WiFi-like downlink access to users in indoor visible light networks through a set of centrally-controlled and partially interfering light emitting diodes (LEDs). To reduce the effect of interference among users created by the partial overlap of each LED's field of view, we propose LiBeam, a cooperative beamforming scheme, based on forming multiple LED clusters. Each cluster then serves a subset of users by jointly determining the user-LED association strategies and the beamforming vectors of the LEDs. The paper first proposes a mathematical model of the cooperative beamforming problem, presented as maximizing the sum throughput of all VLC users. Then, we solve the resulting mixed integer nonlinear nonconvex programming (MINCoP) problem by designing a globally optimal solution algorithm based on a combination of branch and bound framework as well as convex relaxation techniques. We then design for the first time a large programmable visible light networking testbed based on USRP X310 software-defined radios, and experimentally demonstrate the effectiveness of the proposed joint beamforming and association algorithm through extensive experiments. Performance evaluation results indicate that over 95% utility gain can be achieved compared to suboptimal network control strategies.

The promise of real-time detection and response to life-crippling diseases brought by the Implantable Internet of Medical Things (IIoMT) has recently spurred substantial advances in implantable technologies. Yet, existing devices do not provide at once the miniaturized end-to-end sensing-computation-communication-recharging capabilities to implement IIoMT applications. This paper fills the existing research gap by presenting U-Verse, the first FDA-compliant rechargeable IIoMT platform packing sensing, computation, communication, and recharging circuits into a penny-scale platform. U-Verse uses a single miniaturized transducer for data exchange and for wireless charging. To predict U-Verse's performance, we (i) derive and experimentally validate a mathematical model of U-Verse's charging efficiency; and (ii) experimentally calculate the resistance-reactance parameters of our ultrasonic transducer and rectifying circuit. We design a matching circuit to maximize the amount of power transferred from the outside. We also go through the challenge of fabricating a full-fledged cm-scale printed circuit board (PCB) for U-Verse. Extensive experimental evaluation indicates that U-Verse (i) is able to recharge a 330mF and 15F energy storage unit - several orders of magnitude higher than existing work - respectively under 20 and 60 minutes at a depth of 5cm; (ii) achieves stored charge duration of up to 610 and 40 hours in case of battery and supercapacitor energy storage, respectively. Finally, U-Verse is demonstrated through (i) a closed-loop application where a periodic sensing/actuation task sends data via ultrasounds through real porcine meat; and (ii) a real-time reconfigurable pacemaker.

In this paper we present HIRO-NET, Heterogeneous Intelligent Robotic Network. HIRO-NET is an emergency infrastructure-less network tailored to address the problem of providing connectivity in the immediate aftermath of a natural disaster, where no cellular or wide area network is operational and no Internet access is available. HIRO-NET establishes a two-tier wireless mesh network where the Lower Tier connects nearby survivors in a self-organized mesh via Bluetooth Low Energy (BLE)and the Upper Tier creates long-range VHF links between autonomous robots exploring the disaster stricken area. HIRO-NET main goal is to enable users in the disaster to exchange text messages in order to share critical information and request help from first responders. The mesh network discovery problem is analyzed and a network protocol specifically designed to facilitate the exploration process is presented. We show how HIRO-NET robots successfully discover, bridge and interconnect local mesh networks. Results show that the Lower Tier always reaches network convergence and the Upper Tier can virtually extend HIRO-NET functionalities to the range of a small metropolitan area. In the event of an Internet connection still being available to some user, HIRO-NET is able to opportunistically share and provide access to low data-rate services (e.g. Twitter, Gmail)to the whole network. Results suggest that a temporary emergency network to cover a metropolitan area can be created in tens of minutes.

This article investigates the basic design principles for a new Wireless Network Operating System (WNOS), a radically different approach to software-defined networking (SDN) for infrastructure-less wireless networks. Departing from well-understood approaches inspired by OpenFlow, WNOS provides the network designer with an abstraction hiding (i) the lower-level details of the wireless protocol stack and (ii) the distributed nature of the network operations. Based on this abstract representation, the WNOS takes network control programs written on a centralized, high-level view of the network and automatically generates distributed cross-layer control programs based on distributed optimization theory that are executed by each individual node on an abstract representation of the radio hardware.

As network utilization keeps increasing, it is essential to have mechanisms to better schedule traffic in the network. Using content-based resource allocation allows to deliver a fine- grained scheduling and to monitor not only the instantaneous link utilization but also the backlog that is already scheduled onto a link in the future. We propose to use a manifest prior to a session to inform the session manager of the requested bandwidth. We propose to make that information available to the scheduler in the data center context. We have implemented our scheme in a testbed and demonstrate a significant benefit for a data center use case.

It is well known that electromagnetic radio-frequency (RF) waves that are the basis of most commercial wireless technologies are largely unsuitable to interconnect deeply implanted medical devices. RF waves are in fact absorbed by aqueous biological tissues and prone to malicious jamming attacks or to environmental interference from pervaslvely deployed RF communication systems; moreover, they pose a potential safety hazard when exposure of tissues is prolonged and at high power. While existing wireless technologies can satisfy the requirements of some specific applications, the root challenge of enabling networked intra-body miniaturized sensors and actuators that communicate through body tissues is largely unaddressed. Considering these limitations, this article proposes a high data rate ultrasonic communication scheme for wireless intra-body networks. The proposed scheme can enable various applications that require high sampling rates such as neural data recording or monitoring of the digestive tract through endoscopic pills. The proposed scheme is based on Orthogonal Frequency-Division Multiplexing (OFDM), which is proven to be robust against frequency-selective channels with relatively long delay spreads like the intra-body ultrasonic channel. The proposed scheme is implemented in a prototype ultrasonic software-radio and demonstrated to achieve data rates up to 28.12 Mbit/s through synthetic phantoms mimicking the ultrasonic propagation characteristics of biological tissues.

In this paper we design, implement, and experimentally evaluate a wireless software-defined radio platform for cognitive channelization in the presence of narrowband or wideband primary stations. Cognitive channelization is achieved by jointly optimizing the transmission power and the waveform channel of the secondary users. The process of joint resource allocation requires no a-priori knowledge of the transmission characteristics of the primary user and maximizes the signal-to- interference-plus-noise ratio (SINR) at the output of the secondary receiver. This is achieved by designing waveforms that span the whole continuum of available/device-accessible spectrum, while satisfying a peak power constraint for the secondary users and an interference temperature (IT) constraint for the primary users. We build a four-node software-defined radio testbed and experimentally demonstrate in an indoor laboratory environment the theoretical concepts of all-spectrum cognitive channelization in terms of pre-detection SINR and bit-error-rate (BER) at both primary and secondary receivers.

Existing commercial wireless systems are mostly hardware-based, and rely on closed and inflexible designs and architectures. Moreover, despite recent significant algorithmic developments in cross-layer network adaptation and resource allocation, existing network architectures are unable to incorporate most of these advancements. While software-defined radio (SDR) was envisioned as a new paradigm promising radical runtime adaptation through all layers of the networking protocol stack, the reality of the state-of-the-art in wireless networking practice is far from having fulfilled such promise of fast and intelligent reconfigurability and adaptability. Networking research based on the “software-defined radio” paradigm has suffered almost invariably from the lack of adequate and coherently designed abstractions to (i) define networking protocols and their cross-layer interactions across all layers of the protocol stack; (ii) define decision-making algorithms to control such interactions. To address this need, we introduce RcUBe (Real-time Re-configurable Radio), a novel architectural radio framework based on abstractions that offer real-time reconfigurability and optimization capabilities at the PHY, MAC, and network layers of the protocol stack. Unlike state-of-the-art solutions, RcUBe offers a structured methodology at variable levels of abstraction to accommodate implementations of a wide range of network architectures and protocols and complex decision-making in a modular, platform-independent way. RcUBe provides these features through a design structured into four distinct, but interacting planes, namely decision, control, data, and register plane. The broad capabilities of the proposed framework are demonstrated on a network level software-defined radio setup through a range of experiments where RcUBe is used to implement various reconfigurable functionalities of a wireless system at the PHY, MAC, and network layer.