Connection management is an important problem for any wireless network to ensure smooth and well-balanced operation throughout. Traditional methods for connection management (specifically user-cell association) consider sub-optimal and greedy solutions such as connection of each user to a cell with maximum receive power. However, network performance can be improved by leveraging machine learning (ML) and artificial intelligence (AI) based solutions. The next generation software defined 5G networks defined by the Open Radio Access Network (O-RAN) alliance facilitates the inclusion of ML/AI based solutions for various network problems. In this paper, we consider intelligent connection management based on the O-RAN network architecture to optimize user association and load balancing in the network. We formulate connection management as a combinatorial graph optimization problem. We propose a deep reinforcement learning (DRL) solution that uses the underlying graph to learn the weights of the graph neural networks (GNN) for optimal user-cell association. We consider three candidate objective functions: sum user throughput, cell coverage, and load balancing. Our results show up to 10% gain in throughput, 45-140% gain cell coverage, 20-45% gain in load balancing depending on network deployment configurations compared to baseline greedy techniques.

Ultra-reliable, low-latency communication (URLLC) is being developed to support critical control applications over wireless networks. Exploiting spatial diversity through relays is a promising technique for achieving the stringent requirements of URLLC, but coordinating relays reliably and with low overhead is a challenge. Adaptive relay selection techniques have been proposed as a way to simplify implementation while still achieving the requirements of URLLC. Identifying good relays with low overhead and high confidence is critical for such adaptive relay selection techniques.Channel dynamics must be taken into account by adaptive relay selection algorithms because channel quality may degrade in the time it takes to estimate the relay's channel and schedule a transmission. Spatial channel dynamics are well studied in many settings such as RADAR and the fast-fading wireless channels, but less so in the URLLC context where rare events neglected in other models may be important. In this work, we perform measurements to validate channel models in the slow fading regime of interest. We compare measurements to Jakes's model and discuss the appropriateness of Jakes's model for URLLC relay selection. This is further applied to demonstrate that easily implementable relay selection techniques perform well in practical settings.Polynomial interpolation and neural-net-based algorithms were evaluated as channel prediction algorithms. These techniques perform orders of magnitude better than relay selection on average (nominal) SNR.

Recent work in networked systems has shown that using aerial imagery for farm monitoring can enable precision agriculture by lowering the cost and reducing the overhead of large scale sensor deployment. However, acquiring aerial imagery requires a drone, which has high capital and operational costs, often beyond the reach of farmers in the developing world. In this paper, we present TYE (Tethered eYE), an inexpensive platform for aerial imagery. It consists of a tethered helium balloon with a custom mount that can hold a smartphone (or a camera) with a battery pack. The balloon can be carried using a tether by a person or a vehicle. We incorporate various techniques to increase the operational time of the system, and to provide actionable insights even with unstable imagery. We develop path-planning algorithms and use that to develop an interactive mobile phone application that provides the user instant feedback to guide users to efficiently traverse large areas of land. We use computer vision algorithms to stitch orthomosaics by effectively countering wind-induced motion of the camera. We have used TYE for aerial imaging of agricultural land for over a year, and envision it as a low-cost aerial imaging platform for similar applications.

Interactive, immersive, and other timing-critical applications demand ultra-reliable low-latency communication (URLLC). To build wireless communication systems that can support these applications, understanding the relevant characteristics of the wireless medium is paramount. Although wireless channel characteristics and dynamics have been extensively studied, it is important to revisit these concepts in the context of the strict demands of low-latency and ultra-high reliability. In this paper, we bring a modeling approach from robust control to wireless communication-the wireless channel characteristics are given a nominal model around which we allow for some quantified uncertainty. We propose certain key URLLC-relevant parameters along which the model uncertainty is to be bounded. To validate the nominal model of the spatially independent quasi-static Rayleigh fading, we take an in-depth look at the spatial and temporal correlations based on Jakes' model. We find that although the Rayleigh fading process is band-limited, the quasi-static assumption is not safe for relay selection even well within a single coherence time. We also find that under reasonable conditions, the spatial correlation of channels provide a fading distribution that is not too far off from an independent spatial fading model. In addition, we look at the impact of these channel models on cooperative communication-based systems. We find that while spatial-diversity-based techniques are necessary to combat the adverse effects of fading, time-diversity-based techniques are necessary to be robust against unmodeled errors. Robust URLLC systems need to operate with both an adequate SNR margin and a time margin through repetitions.

Ultra-reliable, low-latency wireless communication is essential to enable critical and interactive applications. The cooperative communication schemes for such ultra-reliable communication must harvest multi-user diversity to achieve their specifications. The underlying low-latency space-time codes for a large number of users (> 10) place burdens on practical implementations due to the large number of simultaneous relays they must use. To address this, we propose an adaptive relay selection technique that selects a small set of good relays, instead of using every available radio to relay. Using our simple relay-selection schemes, we can support a network with 30 nodes requiring system failure probability under 10 -9and 2ms latency with only 3 simultaneously active relays per message. In contrast, in the absence of adaptive relay selection, we must rely on 13 relays to achieve the same reliability. To arrive at such relay selection schemes, we revisit the fading dynamics of wireless channels in the context of ultra-high reliability. Contrary to what has been claimed in the literature, we find that standard Rayleigh fading processes are not bandlimited. However, these fading processes are fairly predictable on the short time scales of the regime of interest.

High-performance industrial automation systems rely on tens of simultaneously active sensors and actuators and have stringent communication latency and reliability requirements. Current wireless technologies, such as Wi-Fi, Bluetooth, and LTE are unable to meet these requirements, forcing the use of wired communication in industrial control systems. This paper introduces a wireless communication protocol that capitalizes on multiuser diversity and cooperative communication to achieve the ultra-reliability with a low-latency constraint. Our protocol is analyzed using the communication-theoretic delay-limitedcapacity framework and compared with baseline schemes that primarily exploit frequency diversity. For a scenario inspired by an industrial printing application with 30 nodes in the control loop, 20-B messages transmitted between pairs of nodes and a cycle time of 2 ms, an idealized protocol can achieve a cycle failure probability (probability that any packet in a cycle is not successfully delivered) lower than 10-9with nominal SNR below 5 dB in a 20-MHz wide channel.

Cooperative communication to extract multi-user diversity and network coding are two ideas for improving wireless protocols. These ideas can be exploited to design protocols for low-latency high-reliability communication for control. Given the high-performance constraints for this communication, it is critical, to understand how sensitive such protocols are to modeling assumptions. We examine the impact of channel reciprocity, quasi-static fading, and the spatial independence of channel fades in this paper. This paper uses simple models to explore the performance sensitivity to assumptions. It turns out that wireless network-coding is moderately sensitive to channel reciprocity and non-reciprocity costs about 2dB SNR. The loss of the quasi-static fading assumption has a similar cost for the network coding based protocol but has a negligible effect on the protocol that doesn't use network coding. The real sensitivity of cooperative communication protocols is to the spatial independence assumptions. Capping the amount of independence to a small number degrades performance but perhaps more surprisingly, a simple Gilbert-Elliott-inspired model shows that having a random amount of independence can also severely impact performance.

The Internet of Things (IoT) envisions simultaneous sensing and actuation of numerous wirelessly connected devices. Emerging human-in-the-loop applications demand low-latency high-reliability communication protocols, paralleling the requirements for high-performance industrial control. This paper introduces a wireless communication protocol based on network coding that in conjunction with cooperative communication techniques builds the necessary diversity to achieve the target reliability. The proposed protocol, XOR-CoW, is analyzed by using a communication theoretic delay-limited-capacity framework and compared to different realizations of previously proposed protocols without network coding. The results show that as the network size or payload increases, XOR-CoW gains advantage in minimum SNR to achieve the target latency. For a scenario inspired by an industrial printing application with 30 nodes in the control loop, total information throughput of 4.8 Mb/s, 20MHz of bandwidth and cycle time under 2 ms, the protocol can robustly achieve a system probability of error better than 10-9with a nominal SNR less than 2 dB with Rayleigh fading.

The Internet of Things envisions not only sensing but also actuation of numerous wirelessly connected devices. Seamless control with humans in the loop requires latencies on the order of a millisecond with very high reliabilities, paralleling the requirements for high-performance industrial control. Today's practical wireless systems cannot meet these reliability and latency requirements, forcing the use of wired systems. This paper introduces a wireless communication protocol, dubbed “Occupy CoW,” based on cooperative communication among nodes in the network to build the diversity necessary for the target reliability. Simultaneous retransmission by many relays achieves this without significantly decreasing throughput or increasing latency. The protocol is analyzed using the communication theoretic delay-limited-capacity framework and compared to baseline schemes that primarily exploit frequency diversity. In particular, we develop a novel “diversity meter” designed to measure “effective diversity” in the non-asymptotic regime. For a scenario inspired by an industrial printing application with 30 nodes in the control loop, total information throughput of 4.8 Mb/s, and cycle time under 2 ms, the protocol can robustly achieve a system probability of error better than 10−9with nominal SNR below 5 dB.

Consider two remote nodes having binary sequences X and Y, respectively. Y is an edited version of X, where the editing involves random deletions, insertions, and substitutions, possibly in bursts. The goal is for the node with Y to reconstruct X with minimal exchange of information over a noiseless link. The communication is measured in terms of both the total number of bits exchanged and the number of interactive rounds of communication. This paper focuses on the setting where the number of edits is o(n/log n), where n is the length of X. We first consider the case where the edits are a mixture of insertions and deletions (indels), and propose an interactive synchronization algorithm with near-optimal communication rate and average computational complexity of O(n) arithmetic operations. The algorithm uses interaction to efficiently split the source sequence into substrings containing exactly one deletion or insertion. Each of these substrings is then synchronized using an optimal one-way algorithm based on the single-deletion correcting channel codes of Varshamov and Tenengolts. We then build on this synchronization algorithm in three different ways. First, it is modified to work with a single round of interaction. The reduction in the number of rounds comes at the expense of higher communication, which is quantified. Next, we present an extension to the practically important case where the insertions and deletions may occur in (potentially large) bursts. Finally, we show how to synchronize the sources to within a target Hamming distance. This feature can be used to differentiate between substitution and indel edits. In addition to theoretical performance bounds, we provide several validating simulation results for the proposed algorithms.

We consider multicast flow problems where either all of the nodes or only a subset of the nodes may be in session. Traffic from each node in the session has to be sent to every other node in the session. If the session does not consist of all the nodes, the remaining nodes act as relays. The nodes are connected by undirected edges whose capacities are independent and identically distributed random variables. We study the asymptotics of the capacity region (with network coding) in the limit of a large number of nodes, and show that the normalized sum rate converges to a constant almost surely. We then provide a decentralized push-pull algorithm that asymptotically achieves this normalized sum rate.