Cognitive radio architecture for massive internet of things services with dynamic spectrum access

En esta investigación se propone una arquitectura cognitiva para servicios masivos de Internet de las cosas sobre Huecos Espectrales en Televisión. La propuesta seleccionó la banda de frecuencia de TVWS como la mejor para enfrentar el reto de escasez de espectro radioeléctrico para servicios masivos de IoT. La arquitectura provee la lista de canales disponibles a dispositivos IoT y tiene restricciones de Calidad de servicio (QoS). Definimos un mecanismo de acceso novedoso que se basa en políticas regulatorias al interactuar con TVWS Geolocation Base de datos (GLDB) a través del Protocolo de acceso a espacios en blanco (PAWS) para proporcionar la lista de canales disponibles para dispositivos IoT. Con respecto a restricciones de QoS, exploramos diferentes tipos de implementaciones y referencias áreas de cobertura considerando un modelo de probabilidad de pérdida de paquetes. Además, la investigación describe el proceso de optimización para obtener la máxima área de servicio mientras se mantiene una probabilidad de interrupción por debajo de un objetivo dado. Además, aplicamos un mecanismo de macro-diversidad para mejorar la probabilidad de pérdida de paquetes con respecto a nuestra propuesta y una topología con un solo dispositivo maestro. Podemos evidenciar que la probabilidad promedio de pérdida de paquetes es reducido en 26% cuando la carga es igual al 80% en nuestra propuesta.IMT AtlantiqueUniversidad Santo TomásCEA-IoT , Pontificia Universidad JaverianaThis research proposes a novel cognitive radio architecture for massive Internet of Things (IoT) services over TV White Spaces (TVWS). The proposal considers TVWS as suitable frequency bands for facing the limited spectrum problem for massive IoT services. The architecture provides the available list of channels to IoT devices, and its access mechanisms have Quality of Service (QoS) constrains. We define a novel access mechanism that is based on regulatory policies by interacting with TVWS Geolocation Database (GLDB) through the Protocol to Access White-Space (PAWS) for providing the available list of channels to IoT devices. Regarding QoS constraints, we explore different types of deployments and reference coverage areas considering a packet loss probability model. In addition, the research describes the optimization process to obtain the maximum service area while maintaining an outage probability below a given objective. Moreover, we applied a macro-diversity mechanism for improving the packet loss probability with respect to our proposal and one Master Device (MD) topology. We can evidence that the average packet loss probability is reduced in 26% when the load is equal to 80% in our proposal.Doctor en IngenieríaDoctoradohttps://orcid.org/0000-0002-9579-678Xhttps://scholar.google.es/citations?user=-VX8bMEAAAAJ&hl=eshttp://scienti.colciencias.gov.co:8081/cvlac/visualizador/generarCurriculoCv.do?cod_rh=000084496

Spectrum Cost Optimization for Cognitive Radio Transmission over TV White Spaces Using Artificial Neural Networks

In this paper, the use of TV White Spaces (TVWS) by small cognitive radio wireless network operators (SCWNOs) is considered in order to support the growing demands for IoT applications in smart grid and smart cities. In order to support the wide range of services and applications that are being offered by SCWNOS, spectrum leasing could be considered as an alternative solution to achieve improved Quality of Service (QoS). We consider a situation whereby in order to satisfy the QoS requirements, SCWNOs can decide to lease a certain part of the TVWS spectrum that is referred to as high priority TVWS channel (HPC) for a certain period and pay a fee depending on the duration of HPC spectrum usage. We develop an Artificial Neural Networks (ANN) based online algorithm to determine the optimal transmission decision per time slot that would minimise the overall HPC leasing cost of the SCWNOs while satisfying the QoS constraints. The simulations results shows that our proposed ANN based online algorithms outperforms the Lyapunov based online algorithm while its performance is very close to the optimal offline solution with 99% accuracy

Cooperative cognitive network slicing virtualization for smart IoT applications

This paper proposes the cooperative cognitive net-work slicing virtualization solution for smart Internet of things (IoT) applications. To this end, we deploy virtualized small base stations (vSBSs) in SDR devices that offer network-slicing virtualization option. The proposed virtualized solution relies on Fed4Fire wireless experimental platform. In particular, we assume that multiple IoT devices can have access to different vSBSs, which coordinate their resources in a cooperative manner using machine learning (ML). To this end, a proactive resource management is deployed in the unlicensed band, where a cooperative solution is facilitated using the licensed band. The cooperative network slicing is managed and orchestrated using small cell virtualization offered by the Fed4Fire. Experimental trials are carried out for certain number of users and results are obtained that highlight the benefit of employing cooperative cognitive network slicing in future virtualized wireless networks

A cyber-enabled mission-critical system for post-flood response:Exploiting TV white space as network backhaul links

A crucial problem in post-flood recovery actions is the ability to rapidly establish communication and collaboration among rescuers to conduct timely and effective search and rescue (SAR) mission given disrupted telecommunication infrastructure to support the service. Aimed at providing such proximity service (ProSe) for mission-critical data exchange in the post-flood environment, the majority of existing solutions rely heavily upon ad-hoc networking approaches, which suffer from restricted communication range and the limited scope of interaction. As an effort to broaden the ProSe coverage and expand integrated global-local information exchange in the post-flood SAR activities, this paper proposes a novel network architecture in the form of a cyber-enabled mission-critical system (CEMCS) for acquiring and communicating post-flood emergency data by exploiting TV white space spectrum as network backhaul links. The primary method of developing the proposed system builds upon a layered architecture of wireless local, regional and wide-area communications, and incorporates collaborative network components among these layers. The desirable functionalities of CEMCS are showcased through formulation and the development of an efficient global search strategy exploiting a wide range of collaboration among network agents. The simulation results demonstrate the capability of CEMCS to provide ProSe in the post-flood scenarios as reflected by reliable network performance (e.g., packet delivery ratio nearing 80%-90%) and the optimality of efficient search algorithm

Comprehensive survey on quality of service provisioning approaches in cognitive radio networks : part one

Much interest in Cognitive Radio Networks (CRNs) has been raised recently by enabling unlicensed (secondary) users to utilize the unused portions of the licensed spectrum. CRN utilization of residual spectrum bands of Primary (licensed) Networks (PNs) must avoid harmful interference to the users of PNs and other overlapping CRNs. The coexisting of CRNs depends on four components: Spectrum Sensing, Spectrum Decision, Spectrum Sharing, and Spectrum Mobility. Various approaches have been proposed to improve Quality of Service (QoS) provisioning in CRNs within fluctuating spectrum availability. However, CRN implementation poses many technical challenges due to a sporadic usage of licensed spectrum bands, which will be increased after deploying CRNs. Unlike traditional surveys of CRNs, this paper addresses QoS provisioning approaches of CRN components and provides an up-to-date comprehensive survey of the recent improvement in these approaches. Major features of the open research challenges of each approach are investigated. Due to the extensive nature of the topic, this paper is the first part of the survey which investigates QoS approaches on spectrum sensing and decision components respectively. The remaining approaches of spectrum sharing and mobility components will be investigated in the next part

Opportunistic Spectrum Utilization for Vehicular Communication Networks

Recently, vehicular networks (VANETs), has become the key technology of the next-generation intelligent transportation systems (ITS). By incorporating wireless communication and networking capabilities into automobiles, information can be efficiently and reliably disseminated among vehicles, road side units, and infrastructure, which enables a number of novel applications enhancing the road safety and providing the drivers/passengers with an information-rich environment. With the development of mobile Internet, people want to enjoy the Internet access in vehicles just as anywhere else. This fact, along with the soaring number of connected vehicles and the emerging data-craving applications and services, has led to a problem of spectrum scarcity, as the current spectrum bands for VANETs are difficult to accommodate the increasing mobile data demands. In this thesis, we aim to solve this problem by utilizing extra spectrum bands, which are not originally allocated for vehicular communications. In this case, the spectrum usage is based on an opportunistic manner, where the spectrum is not available if the primary system is active, or the vehicle is outside the service coverage due to the high mobility. We will analyze the features of such opportunistic spectrum, and design efficient protocols to utilize the spectrum for VANETs. Firstly, the application of cognitive radio technologies in VANETs, termed CR-VANETs, is proposed and analyzed. In CR-VANETs, the channel availability is severely affected by the street patterns and the mobility features of vehicles. Therefore, we theoretically analyze the channel availability in urban scenario, and obtain its statistics. Based on the knowledge of channel availability, an efficient channel access scheme for CR-VANETs is then designed and evaluated. Secondly, using WiFi to deliver mobile data, named WiFi offloading, is employed to deliver the mobile data on the road, in order to relieve the burden of the cellular networks, and provide vehicular users with a cost-effective data pipe. Using queueing theory, we analyze the offloading performance with respect to the vehicle mobility model and the users' QoS preferences. Thirdly, we employ device-to-device (D2D) communications in VANETs to further improve the spectrum efficiency. In a vehicular D2D (V-D2D) underlaying cellular network, proximate vehicles can directly communicate with each other with a relatively small transmit power, rather than traversing the base station. Therefore, many current transmissions can co-exist on one spectrum resource block. By utilizing the spatial diversity, the spectrum utilization is greatly enhanced. We study the performance of the V-D2D underlaying cellular network, considering the vehicle mobility and the street pattern. We also investigate the impact of the preference of D2D/cellular mode on the interference and network throughput, and obtain the theoretical results. In summary, the analysis and schemes developed in this thesis are useful to understand the future VANETs with heterogeneous access technologies, and provide important guidelines for designing and deploying such networks

Spectrum Sharing, Latency, and Security in 5G Networks with Application to IoT and Smart Grid

The surge of mobile devices, such as smartphones, and tables, demands additional capacity. On the other hand, Internet-of-Things (IoT) and smart grid, which connects numerous sensors, devices, and machines require ubiquitous connectivity and data security. Additionally, some use cases, such as automated manufacturing process, automated transportation, and smart grid, require latency as low as 1 ms, and reliability as high as 99.99\%. To enhance throughput and support massive connectivity, sharing of the unlicensed spectrum (3.5 GHz, 5GHz, and mmWave) is a potential solution. On the other hand, to address the latency, drastic changes in the network architecture is required. The fifth generation (5G) cellular networks will embrace the spectrum sharing and network architecture modifications to address the throughput enhancement, massive connectivity, and low latency. To utilize the unlicensed spectrum, we propose a fixed duty cycle based coexistence of LTE and WiFi, in which the duty cycle of LTE transmission can be adjusted based on the amount of data. In the second approach, a multi-arm bandit learning based coexistence of LTE and WiFi has been developed. The duty cycle of transmission and downlink power are adapted through the exploration and exploitation. This approach improves the aggregated capacity by 33\%, along with cell edge and energy efficiency enhancement. We also investigate the performance of LTE and ZigBee coexistence using smart grid as a scenario. In case of low latency, we summarize the existing works into three domains in the context of 5G networks: core, radio and caching networks. Along with this, fundamental constraints for achieving low latency are identified followed by a general overview of exemplary 5G networks. Besides that, a loop-free, low latency and local-decision based routing protocol is derived in the context of smart grid. This approach ensures low latency and reliable data communication for stationary devices. To address data security in wireless communication, we introduce a geo-location based data encryption, along with node authentication by k-nearest neighbor algorithm. In the second approach, node authentication by the support vector machine, along with public-private key management, is proposed. Both approaches ensure data security without increasing the packet overhead compared to the existing approaches

Conventional And Cognitive Radio Based Disaster Response Networks, A Comparative Study

The need for the deployment of reliable and efficient telecommunication systems in extreme emergency scenarios such as disaster response networks imposes a set of emerging unusual communication and routing challenges and obstacles that questions the performance of existing traditional and commercial telecommunication systems and networks in such scenarios, the revolution of telecommunication and networks industry witnessed the development of enormous telecommunication and networking services and systems that shaped their implementations in various domains of applications , in this paper, we study most of these communication standards in terms of their pros and cons, we also analyze the potentials of these standards in for Disaster Response networks in comparison with Cognitive Radio technology that has distinct capabilities and functionalities that enabled such a technology to be highly applicable for such harsh and unexpected scenario

White Paper for Research Beyond 5G

The documents considers both research in the scope of evolutions of the 5G systems (for the period around 2025) and some alternative/longer term views (with later outcomes, or leading to substantial different design choices). This document reflects on four main system areas: fundamental theory and technology, radio and spectrum management; system design; and alternative concepts. The result of this exercise can be broken in two different strands: one focused in the evolution of technologies that are already ongoing development for 5G systems, but that will remain research areas in the future (with “more challenging” requirements and specifications); the other, highlighting technologies that are not really considered for deployment today, or that will be essential for addressing problems that are currently non-existing, but will become apparent when 5G systems begin their widespread deployment