Internet of Bio-Nano Things: A review of applications, enabling technologies and key challenges

Internet of Bio-Nano Things (IoBNT) is envisioned to be a heterogeneous network of nanoscale and biological devices, so called Bio-Nano Things (BNTs), communicating via non-conventional means, e.g., molecular communications (MC), in non-conventional environments, e.g., inside human body. The main objective of this emerging networking framework is to enable direct and seamless interaction with biological systems for accurate sensing and control of their dynamics in real time. This close interaction between bio and cyber domains with unprecedentedly high spatio-temporal resolution is expected to open up vast opportunities to devise novel applications, especially in healthcare area, such as intrabody continuous health monitoring. There are, however, substantial challenges to be overcome if the enormous potential of the IoBNT is to be realized. These range from developing feasible nanocommunication and energy harvesting techniques for BNTs to handling the big data generated by IoBNT. In this survey, we attempt to provide a comprehensive overview of the IoBNT framework along with its main components and applications. An investigation of key technological challenges is presented together with a detailed review of the state-of-the-art approaches and a discussion of future research directions.

Low complexity full duplex MIMO systems: Analog canceler architectures, beamforming design, and future directions

The hardware complexity of the analog Self-Interference (SI) canceler in conventional full duplex Multiple Input Multiple Output (MIMO) designs mostly scales with the number of transmit and receive antennas, thus exploiting the benefits of analog cancellation becomes impractical for full duplex MIMO transceivers, even for a moderate number of antennas. In this paper, we provide an overview of two recent hardware architectures for the analog canceler comprising of reduced number of cancellation elements, compared to the state of the art, and simple multiplexers for efficient signal routing among the transceiver radio-frequency chains. The one architecture is based on analog taps and the other on AUXiliary (AUX) Transmitters (TXs). In contrast to the available analog cancellation architectures, the values for each tap or each AUX TX and the configuration of the multiplexers are jointly designed with the digital transceiver beamforming filters according to desired performance objectives. We present a general optimization framework for the joint design of analog SI cancellation and digital beamforming, and detail an example algorithmic solution for the sum-rate optimization objective. Our representative computer simulation results demonstrate the superiority, both in terms of hardware complexity and achievable performance, of the presented low complexity full duplex MIMO schemes over the relative available ones in the literature. We conclude the paper with a discussion on recent simultaneous transmit and receive operations capitalizing on the presented architectures, and provide a list of open challenges and research directions for future FD MIMO communication systems, as well as their promising applications.

Infrastructure sharing model to connect the unconnected in rural areas

One of the major problems the telecommunication industry faces in providing connectivity to the unconnected, particularly in rural and remote areas, is the lack of infrastructure in these areas. Indeed, deploying a network in an isolated area can be more expensive for an operator than in an urban area, while the return on investment is not possible. This is the primary cause of the coverage divide. To remedy this, in this work, we propose a techno-economic analysis of infrastructure sharing. First, we develop a mathematical model of the overall cost of extending a mobile network in rural areas. Different scenarios involving infrastructure sharing at varying levels of deployment are then presented. Then, using the models proposed in each scenario, we make a case study to deduce the most economically advantageous scenario for operators to extend their networks to remote areas. This case involves the sharing of passive infrastructure and also the sharing of active resources in a cloud-RAN. Based on the proposed model, our simulation results show that while passive sharing is beneficial, active sharing using cloud-RAN as technology increases this benefit. This work also indicates and highlights the technical constraints to be respected in the sharing for this scenario.

Ensuring reliable connectivity to cellular-connected UAVs with up-tilted antennas and interference coordination

To integrate unmanned aerial vehicles (UAVs) in future large-scale deployments, a new wireless communication paradigm, namely, the cellular-connected UAV has recently attracted interest. However, the line-of-sight dominant air-to-ground channels along with the antenna pattern of the cellular ground base stations (GBSs) introduce critical interference issues in cellular-connected UAV communications. In particular, the complex antenna pattern and the ground reflection (GR) from the down-tilted antennas create both coverage holes and patchy coverage for the UAVs in the sky, which leads to unreliable connectivity from the underlying cellular network. To overcome these challenges, in this paper, we propose a new cellular architecture that employs an extra set of co-channel antennas oriented towards the sky to support UAVs on top of the existing down-tilted antennas for ground user equipment (GUE). To model the GR stemming from the down-tilted antennas, we propose a path-loss model, which takes both antenna radiation pattern and configuration into account. Next, we formulate an optimization problem to maximize the minimum signal-to-interference ratio (SIR) of the UAVs by tuning the up-tilt (UT) angles of the up-tilted antennas. Since this is an NP-hard problem, we propose a genetic algorithm (GA) based heuristic method to optimize the UT angles of these antennas. After obtaining the optimal UT angles, we integrate the 3GPP Release-10 specified enhanced inter-cell interference coordination (eICIC) to reduce the interference stemming from the down-tilted antennas. Our simulation results based on the hexagonal cell layout show that the proposed interference mitigation method can ensure higher minimum SIRs for the UAVs over baseline methods while creating minimal impact on the SIR of GUEs.

Doors in the sky: Detection, localization and classification of aerial vehicles using laser mesh

Stealth technology and Unmanned Aerial Vehicles (UAVs) are expected to dominate current and future aerial warfare. The radar systems at their maximum operating ranges, however, are not always able to detect stealth and small UAVs mainly due to their small radar cross sections and/or low altitudes. In this paper, a novel technique as an alternative to radar technology is proposed. The proposed approach is based on creating a mesh structure of laser beams initiated from aerial platforms towards the ground. The laser mesh acts as a virtual net in the sky. Any aerial vehicle disrupting the path of the laser beams are detected and subsequently localized and tracked. As an additional feature, steering of the beams can be used for increased coverage and improved localization and classification performance. A database of different types of aerial vehicles is created artificially based on Gaussian distributions. The database is used to develop several Machine Learning (ML) models using different algorithms to classify a target. Overall, we demonstrated through simulations that our proposed model achieves simultaneous detection, classification, localization, and tracking of a target.

Equal-gain combining with interference mitigation for molecular type hopping assisted molecular shift keying systems

In multiple access molecular diffusive communications, many nano-machines exchange information and fuse data through a common Diffusive Molecular Communication (DMC) channel. Hence, there is Multiple-Access Interference (MAI), which should be sufficiently mitigated so as to achieve reliable communications. In this paper, we propose a novel low-complexity detection scheme, namely Equal-Gain Combining with Interference Mitigation (EGC-IM), for signal detection in the Molecular Type Hopping assisted Molecular Shift Keying (MTH-MoSK) DMC systems. By removing a number of entries from each row of the detection matrix formed during detection, the EGC-IM scheme shows its potential to significantly mitigate MAI and hence, outperform the conventional EGC scheme. Furthermore, the EGC-IM scheme has lower complexity than the conventional EGC scheme and therefore, it is beneficial for practical implementation.

ARPA: An autonomous renderer placement algorithm in distributed multimedia fog networks with delay guarantees

Multimedia cloud computing has emerged as a popular paradigm for the support of delay-intolerable immersive multimedia applications with high-end three-dimensional rendering. To that end, fog computing offers distributed computational offloading solutions, by positioning rendering servers in close proximity to end users promising in this way continuous service provision, that is otherwise not easily attainable under the strictly centralized cloud-only model. Yet, in order to alleviate the multimedia providers from unnecessary capital expenditure, a strategic placement approach of the servers at the fog layer must be implemented, that can effectively cope both with the network dynamics and the overall imposed deployment cost, and still adhere to the delay bounds set forth by the multimedia application. In this paper, we formally formulate the problem as a facility location problem using constrained optimization over a finite time horizon. We then theoretically analyze the minimum acceptable conditions necessary for a decentralized location of the servers, utilizing solely local information around their immediate neighborhood, that iteratively leads to better solutions. Based on the analysis, we propose a distributed algorithm, namely the Autonomous Renderer Placement Algorithm (ARPA), to address it. ARPA employs localized service relocation to shift the placement according to simple rules that designate elastic migration, replication, and complementary consolidation of the underlying renderers. Simulation results under diversified deployment scenarios, as well as trace-driven comparisons against other approaches, testify to ARPA's accountability in obeying the delay limits and fast converge in finite time slots to a placement solution that both outperforms the baseline alternatives and is close to the optimal one, rendering it suitable for scaling up and down to meet the current demands of the offered multimedia applications.

A resource management survey for mission-critical and time-critical applications in multiaccess edge computing

Multiaccess Edge Computing (MEC) brings additional computing power in proximity of mobile users, reducing latency, saving energy and alleviating the network's bandwidth. This proximity is beneficial, especially for mission-critical applications where each second matters, such as disaster management or military operations. Moreover, it enables MEC resources embedded on mobile units like drones or robots that are flexible to be deployed for mission-critical applications. However, the MEC servers are capacity-limited and thus need an acute management of their resources. The mobile resources also need a smart deployment scheme to deliver their services efficiently. In this survey, we review mission-critical applications, resource allocation and deployment of mobile resources techniques in the context of the MEC. First, we introduce the technical specifics and uses of MEC in mission-critical applications to highlight their needs and requirements. Then, we discuss the resource allocation schemes for MEC and assess their fit depending on the application needs. In the same fashion, we finally review the deployment of MEC mobile resources. We believe this work could serve as a helping hand to design efficient MEC resource management schemes that respond to challenging environments such as mission-critical applications.

Hierarchical beam alignment in SU-MIMO terahertz communications

Single-Carrier Frequency Division Multiple Access (SC-FDMA) is a promising technique for high data rate indoor Terahertz (THz) communications in future beyond 5G systems. In an indoor propagation scenario, the Line-Of-Sight (LOS) component may be blocked by the obstacles. Thus, efficient THz SC-FDMA communications require a fast and reliable Beam Alignment (BA) method for both LOS and Non-Line-Of-Sight (NLOS) scenarios. In this paper, we first adopt the hierarchical discrete Fourier transform codebook for LOS BA, and introduce the hierarchical k-means codebook for NLOS BA to improve the beamforming gain. Simulation results illustrate that the hierarchical DFT codebook and the hierarchical k-means codebook can achieve the beamforming gain close to that of the maximum ratio transmission in LOS and NLOS cases, respectively. Based on these two codebooks, we propose a Multi-Armed Bandit (MAB) algorithm named Hierarchical Beam Alignment (HBA) for single-user SC-FDMA THz systems to reduce the BA latency. HBA utilizes a hierarchical structure in the adopted codebook and prior knowledge regarding the noise power to speed up the BA process. Both theoretical analysis and simulation results indicate that the proposed BA method converges to the optimal beam with high probability for both the hierarchical DFT codebook and the hierarchical k-means codebook in the LOS and NLOS scenarios, respectively. The latency introduced by HBA is significantly lower when compared to an exhaustive search method and other MAB-based methods.

Self-configuring asynchronous sleeping in heterogeneous networks

Nowadays, the heterogeneous wireless nano-network topology becomes a need for diverse applications based on heterogeneous networks composed of regions of different node densities. In Wireless Nano-networks (WNNs), nodes are of nano-metric size and can be potentially dense in terms of neighbouring nodes. Nano-nodes have limited resources in terms of processing, energy and memory capabilities. In nano-network(s), even in a communication range limited to tens of centimeters, thousands of neighbours can be found. We proposed a fine-grained duty-cycling method (sleeping mechanism), appropriate to nanonodes, which aims to reduce the number of receptions seen by a node during data packet routing. The present study reveals the usefulness of implementing the sleeping mechanism in heterogeneous networks, as well as configuring a dynamic awaken duration for nodes based on a density estimation algorithm. We also proposed an algorithm that helps in increasing the reliability of the packet received by the destination node.