The rapid evolution of wireless technologies has intensified interest in open and fully programmable radio access networks for whole-stack research, innovation, and evaluation of emerging solutions. Large-scale wireless living labs, such as ARA, equipped with real-world infrastructure play a vital role in this evolution by enabling researchers to prototype and evaluate advanced algorithms for next-generation wireless systems in outdoor and over-the-air environments benefiting from real-world fidelity and end-to-end programmability. However, at the core of this innovation is the performance in terms of coverage and reliability of these wireless living labs. For instance, interfacing power amplifiers and low noise amplifiers with software-defined radios (SDRs) for experimenting outdoors introduces issues in random access procedure—a process crucial in establishing connectivity between user equipment (UE) and the core network in 5G and 6G systems. Therefore, to ensure seamless connectivity and reliable communications in open-source 5G software stacks such as OpenAirInterface (OAI), we propose a slot-based approach to the 5G random access procedure leveraging full downlink (DL) and uplink (UL) slots instead of using special or mixed slots. We highlight how this approach achieves reliable 5G connectivity over 1 mile—the longest communication range that has been achieved so far in real-world settings using open-source 5G software stacks and the Universal Software Radio Peripheral (USRP) SDRs. We also demonstrate that, in a highly obstructed environment such as an industrial setting, we can increase the probability of a successful random access procedure to 90%–100% when we use at least 9 OFDM symbols to transmit msg2 and msg3.

Wireless innovation can significantly benefit from having access to real-world, over-the-air (OTA) living labs for open-source prototyping and field evaluation of emerging, state-of-the-art solutions. However, the existing open-source 5G testbeds are either confined to controlled indoor environments, or they use commercial-off-the-shelf (COTS) user equipment (UEs) only without supporting software-defined-radio (SDR) UEs, thus lacking real-world fidelity or end-to-end programmability from UEs to gNBs and core networks. To fill the gap, we develop and deploy AraSDR that, as an integral element of the ARA Platform for Advanced Wireless Research (PAWR) on rural broadband, serves as a first-of-its-kind outdoor living lab supporting end-to-end, fully-programmable 5G experiments with SDR UEs and base stations (BSes) in real-world rural settings. AraSDR deploys in agriculture farms and rural cities NI N320 and B210 as the BS and UE SDRs respectively, and it employs low-cost, performant custom RF front-ends with power amplifiers (PAs) and low-noise amplifiers (LNAs) to boost the transmit and receive signals for extended cellular coverage. To enable real-world SDR-based experiments with open-source 5G stand-alone (SA) TDD cellular operations, we address the challenges of reliable control signaling, precision timing of the transmission/reception mode of RF front-ends, as well as transmission and reception gain control. We develop the software control framework to support remote experiments with streamlined workflows and to enable container-based experiment portability and reproducibility. Using OpenAirInterface (OAI) as an example open-source 5G software platform, we demonstrate the capability of AraSDR in supporting real-world, OTA 5G experiments.

ARA is an at-scale Platform for Advanced Wireless Research (PAWR), specifically tailored to the unique community, application, and economic context of rural regions. It features the first-of-its-kind real-world implementation of long-distance, high-capacity wireless backhaul and access systems spanning over 30 km in diameter. Leveraging both software-defined radios and programmable Commercial Off-The-Shelf (COTS) systems, ARA orchestrates the wireless resources alongside the networking and compute resources for enabling end-to-end experiments involving user equipment, base stations, edge computing, and cloud infrastructure. Such an integration facilitates the coevolution of rural-focused wireless innovation and applications, while helping to advance the frontiers of advanced Next-G wireless systems such as Open RAN. As of summer 2024, ARA is publicly accessible with 7 base stations (BSes) and over 30 user equipment (UEs). In this demo, we share advanced wireless research experiments enabled by ARA, involving MU-MIMO in TV White Space (TVWS) bands, long-range mmWave and microwave backhaul communications, and open-source 5G NR protocol stacks such as srsRAN and OpenAirInterface (OAI).

Time synchronization is a critical component in network operation and management, and it is also required by Ultra-Reliable, Low-Latency Communications (URLLC) in next-generation wireless systems such as those of 5G, 6G, and Open RAN. In this context, we design and implement AraSync as an end-to-end time synchronization system in the ARA wireless living lab to enable advanced wireless experiments and applications involving stringent time constraints. We make use of Precision Time Protocol (PTP) at different levels to achieve synchronization accuracy in the order of nanoseconds. Along with fiber networks, AraSync enables time synchronization across the AraHaul wireless x-haul network consisting of long-range, high-capacity mmWave and microwave links. In this paper, we present the detailed design and implementation of AraSync, including its hardware and software components and the PTP network topology. Further, we experimentally characterize the performance of AraSync from spatial and temporal dimensions. Our measurement and analysis of the clock offset and mean path delay show the impact of the wireless channel and weather conditions on the PTP synchronization accuracy.

As the Platform for Advanced Wireless Research (PAWR) in rural broadband, the ARA wireless living lab features the deployment of first-of-its-kind wireless access and backhaul platforms in real-world agriculture and rural settings, and preliminary experiments have demonstrated very promising results, e.g., up to 3.2 Gbps wireless access throughput and more than 10 Gbps throughput across a wireless backhaul link of over 10 km. ARA is expected to be publicly released for broad community use starting in September 2023. Through this demo, we plan to share, for the first time, with the wireless research community the transformative research experiments enabled by ARA. To stimulate discussion and community participation, we will demonstrate a few example experiments ranging from MU-MIMO in TV White Space (TVWS) bands to long-range mmWave and microwave backhaul communications, as well as open-source 5G NR protocol stacks such as srsRAN and OpenAirInterface.

Internet of Things (IoT) refers to the concept of enabling Internet connectivity and associated services to nontraditional computers formed by integrating essential computing and communication capability to physical things for everyday usage. Security and privacy are two of the major challenges in IoT. The essential security requirements of IoT cannot be ensured by the existing security frameworks due to the constraints in CPU, memory, and energy resources of the IoT devices. Also, the centralized security architectures are not suitable for IoT because they are subjected to single point of attacks. Defending against targeted attacks on centralized resources is expensive. Therefore, the security architecture for IoT needs to be decentralized and designed to meet the limitations in resources. Blockchain is a decentralized security framework suitable for a variety of applications. However, blockchain in its original form is not suitable for IoT, due to its high-computational complexity and low scalability. In this article, we propose a sliding window blockchain (SWBC) architecture that modifies the traditional blockchain architecture to suit IoT applications. The proposed SWBC uses previous $(n-1)$ blocks to form the next block hash with limited difficulty in proof-of-work (PoW). The performance of SWBC is analyzed on a real-time data stream generated from a smart home testbed. The results show that the proposed blockchain architecture increases security and minimizes memory overhead while consuming fewer resources.

A novel framework is proposed for software defined wireless mesh networks involving mobile switches and controllers operating under in-band control in order to self-configure depending on the network dynamics. Besides the addition/removal of nodes (including switches and controllers) to/from the network in real-time, the problem becomes more challenging for switches to select an appropriate controller from multiple physical controllers. Therefore, first we design a resource discovery scheme to address the dynamic addition and removal of nodes with a software defined optimized link state routing (SD-OLSR) protocol. Apart from resource discovery, SD-OLSR captures the network dynamism and provides a global network view to the controller. Further, two controller handoff schemes, controller-initiated handoff (CIH) and switch-initiated handoff (SIH), are designed for switches to efficiently handover to a suitable controller. The framework and handoff schemes are tested using a software defined wireless mesh network testbed involving mobile switches and controllers operating under in-band control. The results show that SIH performs better in terms of SDN control overhead and PacketIn-FlowMod delay, while CIH outperforms SIH in terms of the number of handoffs and controller handoff time. A fair trade-off between the number of handoffs and the desired performance metric can be achieved by tuning the handoff threshold in both CIH and SIH schemes. As an added benefit, our framework provides better load sharing among the controllers in terms of flow-rule requests.

A novel framework, Medium-Term Disruption Tolerant Software Defined Network (MDT-SDN), is proposed to handle medium-term disruptions of the order 10 seconds to 6 minutes. Such medium-term disruptions are crucial for the next generation wireless networks that use TCP/IP protocol stack, where the existing disruption tolerant approaches may under-perform due to resource constraints. MDT-SDN enables network control with an additional STORE action which exploits the nodes' memory for buffering packets within the TCP/IP stack during link disruptions and forwards them as the links become alive. First, we model the network with medium-term disruptions using temporal graphs and design an Earliest Arrival Path with Minimal Storage Time (EAPMST) controller algorithm to demonstrate the MDT-SDN framework. The framework is realized in a software defined wireless mesh network testbed, using in-band control, involving mobile nodes with three mobility models: (i) stationary nodes, (ii) group mobility, and (iii) random mobility. Experimental results with four application protocols justify the efficacy of MDT-SDN in providing storage control and additional performance benefits. MDT-SDN along with EAPMST improves the throughput beyond 25% with random mobility model and is capable of carrying packets and maintaining sessions during medium-term disruptions using the existing TCP/IP stack. The use of EAPMST reduces packets' buffering time by 24.45% in group mobility while the buffering time increases in random mobility by 5.82%. However, EAPMST significantly reduces the buffer occupancy by 60.28% and 44.49% for group and random mobility, respectively.

The task of rescue and information gathering has been a major challenge in disaster-prone areas such as shanty towns, where a high density of population are served by poor infrastructure. Inefficient planning becomes a major problem for cities, especially in developing and least developed countries. In this paper, we address the problem of information gathering from a shanty town using mobile data collecting agents (MDCs) assuming neither location map nor communication infrastructure are available. Considering the heterogeneity in the types of roads and MDCs, we define five hybrid mobility models for information gathering: (i) Path Type with Restricted Movement, (ii) Path Type with Wait, (iii) Repetitive Highway with Restricted Movement, (iv) Repetitive Highway with Wait, and (v) Repetitive Highway with Nearest Point. In addition, we define two handoff protocols, Deposit Data handoff and Receive Data handoff, for the MDCs to transfer the gathered information to the Depot. For analyzing the performance, we simulate the mobility models using Urban DTN simulator with the map of shanty town Dharavi, India. The results show that the proposed mobility models provide delivery ratio beyond 50% and Repetitive Highway with Nearest Point being the highest with 74%, with reduced inter-meeting time.

To investigate reported emergency incidents and provide better situational awareness during an emergency response effort in a shanty town, we envision the use of volunteers with networked sensing devices employed as Mobile Data Collectors (MDCs). These MDCs are heterogeneous depending upon the type of roads they can access. They gather information about events reported dynamically at random and relay it to central command center. We consider the problem of minimizing the Travel Time of such heterogeneous volunteer MDCs and maximizing the gathering of event data before its expiry time. We model this problem as a Dynamic Vehicle Routing Problem with Time Windows (DVRPTW), which reduces to a Combinatorial Optimization Problem and is NP-Hard to solve. In this paper, we developed two algorithms, Minimum Deviated Walk and Ortho Walk, to dynamically route or reroute the path of these MDCs to capture the data efficiently. We tested the effectiveness of these algorithms with three different classes of MDCs on simulated non- deterministic random sets of events applied to a real road map of Dharavi, a shanty town in Mumbai, India. We show that both these algorithms are capable of capturing 20% more data than a naive algorithm as well as more than 90% of the events generated within a specified time.