The physical random access channel (PRACH) is used in the uplink of cellular systems for initial access requests from the users. It is very hard to achieve low latency by implementing conventional ...methods in 5G. The performance of the system degrades when multiple users try to access the PRACH receiver with the same preamble signature, resulting in a collision of request signals and dual peak occurrence. In this paper, we used two machine learning classification technique models with signals samples as big data to obtain the best proactive approach. First, we implemented three supervised learning algorithms, Decision Tree Classification (DTC), naïve bayes (NB), and K-nearest neighbor (KNN) to classify the outcome based on two classes, labeled as 'peak' and 'false peak'. For the second approach, we constructed a Bagged Tree Ensembler, using multiple learners which contributes to the reduction of the variance of DTC and comparing their asymptotes. The comparison shows that Ensembler method proves to be a better proactive approach for the stated problem.
The potential role of bottom-up Synthetic Cells (SCs) in the Internet of Bio-Nano Things (IoBNT) is discussed. In particular, this perspective paper focuses on the growing interest in networks of ...biological and/or artificial objects at the micro- and nanoscale (cells and subcellular parts, microelectrodes, microvessels, etc.), whereby communication takes place in an unconventional manner, i.e., via chemical signaling. The resulting "molecular communication" (MC) scenario paves the way to the development of innovative technologies that have the potential to impact biotechnology, nanomedicine, and related fields. The scenario that relies on the interconnection of natural and artificial entities is briefly introduced, highlighting how Synthetic Biology (SB) plays a central role. SB allows the construction of various types of SCs that can be designed, tailored, and programmed according to specific predefined requirements. In particular, "bottom-up" SCs are briefly described by commenting on the principles of their design and fabrication and their features (in particular, the capacity to exchange chemicals with other SCs or with natural biological cells). Although bottom-up SCs still have low complexity and thus basic functionalities, here, we introduce their potential role in the IoBNT. This perspective paper aims to stimulate interest in and discussion on the presented topics. The article also includes commentaries on MC, semantic information, minimal cognition, wetware neuromorphic engineering, and chemical social robotics, with the specific potential they can bring to the IoBNT.
In this Perspective article we intend to focus on the opportunity of modelling Shannon information and/or “semantic” information in the field originated by the convergence of bottom-up synthetic ...biology (in particular, the construction of “synthetic cells”) and the engineering approaches to molecular communication. In particular we will argue that the emerging technology of synthetic cell fabrication will allow novel opportunities to study nano-scale communication and manipulation of information in unprecedented manner. More specifically, we will discuss the possibility of enquiring on the transfer and manipulation of information in the chemical domain, and interpreting such a dynamics according to Shannon or to MacKay-Bateson (“semantic” information).
Unmanned aerial vehicle (UAV)-assisted networks ensure agile and flexible solutions based on the inherent attributes of mobility and altitude adaptation. These features render them suitable for ...emergency search and rescue operations. Emergency networks (ENs) differ from conventional networks. They often encounter nodes with vital information, i.e., critical nodes (CNs). The efficacy of search and rescue operations highly depends on the eminent coverage of critical nodes to retrieve crucial data. In a UAV-assisted EN, the information delivery from these critical nodes can be ensured through quality-of-service (QoS) guarantees, such as capacity and age of information (AoI). In this work, optimized UAV placement for critical nodes in emergency networks is studied. Two different optimization problems, namely capacity maximization and age of information minimization, are formulated based on the nature of node criticality. Capacity maximization provides general QoS enhancement for critical nodes, whereas AoI is focused on nodes carrying critical information. Simulations carried out in this paper aim to find the optimal placement for each problem based on a two-step approach. At first, the disaster region is partitioned based on CNs' aggregation. Reinforcement learning (RL) is then applied to observe optimal placement. Finally, network coverage over optimal UAV(s) placement is studied for two scenarios, i.e., network-centric and user-centric. In addition to providing coverage to critical nodes, the proposed scheme also ensures maximum coverage for all on-scene available devices (OSAs).
We have studied the interference caused by amplitude and phase distortions induced by rain in ultra-wideband communication systems designed for using amplitude modulation in GeoSurf future satellite ...constellations. The results concern radio links simulated with the synthetic storm technique at Spino d’Adda (Italy), Madrid (Spain) and Tampa (Florida), which are sites located in different climatic regions. The conclusions are (a) the three sites, although in different climatic zones, are practically indistinguishable; (b) the channel signal-to-noise ratio can be increased or decreased by interference with equal probability. Channel theoretical capacity loss, even in the worst case, is very limited and rain, therefore, does not cause significant linear distortions in ultra-wideband channels at millimeter waves; therefore, these channels could be used at millimeter waves.
In scenarios, like critical public safety communication networks, On-Scene Available (OSA) user equipment (UE) may be only partially connected with the network infrastructure, e.g., due to physical ...damages or on-purpose deactivation by the authorities. In this work, we consider multi-hop Device-to-Device (D2D) communication in a hybrid infrastructure where OSA UEs connect to each other in a seamless manner in order to disseminate critical information to a deployed command center. The challenge that we address is to simultaneously keep the OSA UEs alive as long as possible and send the critical information to a final destination (e.g., a command center) as rapidly as possible, while considering the heterogeneous characteristics of the OSA UEs. We propose a dynamic adaptation approach based on machine learning to improve a joint energy-spectral efficiency (ESE). We apply a Q-learning scheme in a hybrid fashion (partially distributed and centralized) in learner agents (distributed OSA UEs) and scheduler agents (remote radio heads or RRHs), for which the next hop selection and RRH selection algorithms are proposed. Our simulation results show that the proposed dynamic adaptation approach outperforms the baseline system by approximately 67% in terms of joint energy-spectral efficiency, wherein the energy efficiency of the OSA UEs benefit from a gain of approximately 30%. Finally, the results show also that our proposed framework with C-RAN reduces latency by approximately 50% w.r.t. the baseline.
In an event of a disaster, the connectivity of on-scene available User Equipment (UE) to the first responders is important because of the unavailability of conventional networks. Therefore, in this ...paper, considering the deployment of both the Unmanned Aerial Vehicle (UAV) and Mobile Command Center (MCC), we investigate end to end connectivity of UEs to the MCC in terms of the outage. Specifically, various disaster aware clustering schemes are proposed that utilize the UAV and MCC position for the association. These schemes include multiple degrees of freedom to manage intra-cluster distances along with the flexibility to restructure the clusters. In addition, we assume the provision of simultaneous wireless information and power transfer (SWIPT) at Cluster Heads (CHs) through the UAV and MCC. The results show that the association of a UE to MCC or UAV prior to clustering can be optimized to achieve better performance. Without SWIPT at CH, the minimum distance metric to the UAV provides less outage. However, with SWIPT a weighted compromise between intra-cluster distance and CH distance to the UAV achieves less outage. We applied our proposed methods on a real man-made disaster scenario layout and determined their efficacy.
Within many chemical and biological systems, both synthetic and natural, communication via chemical messengers is widely viewed as a key feature. Often known as
such communication has been a concern ...in the fields of synthetic biologists, nanotechnologists, communications engineers, and philosophers of science. However, interactions between these fields are currently limited. Nevertheless, the fact that the same basic phenomenon is studied by all of these fields raises the question of whether there are unexploited interdisciplinary synergies. In this paper, we summarize the perspectives of each field on molecular communications, highlight potential synergies, discuss ongoing challenges to exploit these synergies, and present future perspectives for interdisciplinary efforts in this area.
The fundamental issue for Beyond fifth Generation (B5G) is providing a pervasive connection to heterogeneous and various devices in smart environments. Therefore, Drones play a vital role in the B5G, ...allowing for wireless broadcast and high-speed communications. In addition, the drone offers several advantages compared to fixed terrestrial communications, including flexible deployment, robust Line of Sight (LoS) connections, and more design degrees of freedom due to controlled mobility. Drones can provide reliable and high data rate connectivity to users irrespective of their location. However, atmospheric disturbances impact the signal quality between drones and users and degrade the system performance. Considering practical implementation, the location of drones makes the drone–user communication susceptible to several environmental disturbances. In this paper, we evaluate the performance of drone-user connectivity during atmospheric disturbances. Further, a Machine Learning (ML)-assisted algorithm is proposed to adapt to a modulation technique that offers optimal performance during atmospheric disturbances. The results show that, with the algorithm, the system switches to a lower order modulation scheme during higher rain rate and provides reliable communication with optimized data rate and error performance.
Device-to-device communication, as provided by the third generation partnership project standardization, can play a vital role in designing a reliable pervasive public safety network, which allows ...the user equipment (UEs) to communicate directly with each other in emergency situations. In this paper, we analyze the performance of direct discovery, one of the features introduced by proximity services. This is examined in heterogeneous environments using the OpenAirInterface open-source software and USRP hardware platform. The experimental results highlight the suitable values for different gains and frequencies of the UEs for performing reliable baseline direct discovery in out-of-coverage scenarios. We evaluate the performance of direct discovery in terms of reliability and maximum range in outdoor and indoor scenarios. Furthermore, we propose a context-aware energy-efficient heuristic algorithm for direct discovery with the aim of extending the network lifetime in emergency scenarios. This heuristic yields significant improvements in UE lifetime (20-52%) and reduces redundant transmissions of discovery messages compared to the baseline approach.
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