Secure Cloud Controlled Software Defined Radio Network For Bandwidth Allocation

The purpose of this research is to investigate the impact of mobility of wireless devices for opportunistic spectrum access and communications using National Instrument Universal Software Radio Peripherals devices. The overall system utilizes software defined radio networks for frequency allocation, cloud connectivity to maintain up-to-date information, and moving target defense as a security mechanism. Each USRP device sends its geolocation to query the spectrum database for idle channels. The cloud cluster was designed for complex data storage and allocation using a smart load balancer to offer ultra-security to users. This project also explores the advantages of data protection and security through moving target defense. To achieve this, the system would use an array of antennas to split the data into different parts and transmit them across separate antennas. This research provides the design to each of the mentioned projects for the implementation of a fully developed system

A baseband wireless spectrum hypervisor for multiplexing concurrent OFDM signals

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the current ones. This situation calls for novel ways to increase the spectral efficiency. Therefore, in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, i.e., the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The proposed architecture is a non-intrusive and highly optimized wireless hypervisor that multiplexes the signals of several different and concurrent multi-carrier-based radio access technologies with numerologies that are multiple integers of one another, which are also referred in our work as radio access technologies with correlated numerology. For example, the proposed architecture can multiplex the signals of several Wi-Fi access points, several LTE base stations, several WiMAX base stations, etc. As it able to multiplex the signals of radio access technologies with correlated numerology, it can, for instance, multiplex the signals of LTE, 5G-NR and NB-IoT base stations. It abstracts a radio frequency front-end into a configurable number of virtual RF front ends, making it possible for such different technologies to share the same RF front-end and consequently reduce the costs and increasing the spectral efficiency by employing densification, once several networks share the same infrastructure or by dynamically accessing free chunks of spectrum. Therefore, the main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers

Design, Analysis, Implementation and Evaluation of Real-time Opportunistic Spectrum Access in Cloud-based Cognitive Radio Networks

Opportunistic spectrum access in cognitive radio network is proposed for remediation of spectrum under-utilization caused by exclusive licensing for service providers that are intermittently utilizing spectrum at any given geolocation and time. The unlicensed secondary users (SUs) rely on opportunistic spectrum access to maximize spectrum utilization by sensing/identifying the idle bands without causing harmful interference to licensed primary users (PUs). In this thesis, Real-time Opportunistic Spectrum Access in Cloud-based Cognitive Radio Networks (ROAR) architecture is presented where cloud computing is used for processing and storage of idle channels. Software-defined radios (SDRs) are used as SUs and PUs that identify, report, analyze and utilize the available idle channels. The SUs in ROAR architecture query the spectrum geolocation database for idle channels and use them opportunistically. The testbed for ROAR architecture is designed, analyzed, implemented and evaluated for efficient and plausible opportunistic communication between SUs

A comparative investigation on performance and which is the preferred methodology for spectrum management; geo-location spectrum database or spetrum sensing

A Research Report submitted to the Faculty of Engineering and the Built Environment, University of Witwatersrand, in the partial fulfilment of the requirements for the degree of Master of Science in Engineering Johannesburg, 2015.Due to the enormous demand for multimedia services which relies hugely on the availability of spectrum, service providers and technologist are devising a means or method which is able to fully satisfy these growing demands. The availability of spectrum to meet these demands has been a lingering issue for the past couple of years. Many would have it tagged as spectrum scarcity but really the main problem is not how scarce the spectrum is but how efficiently allocated to use is the spectrum. Once such inefficiency is tackled effectively, then we are a step closer in meeting the enormous demands for uninterrupted services. However, to do so, there are techniques or methodologies being developed to aid in the efficient management of spectrum. In this research project, two methodologies were considered and the efficiency of these methodologies in the areas of spectrum management. The Geo-location Spectrum Database (GLSD) which is the most adopted technique and the Cognitive radio spectrum sensing technique are currently the available techniques in place. The TV whitespaces (TVWS) was explored using both techniques and certain comparison based on performances; implementation, practicability, cost and flexibility were used as an evaluation parameter in arriving at a conclusion. After accessing both methodologies, conclusions were deduced on the preferred methodology and how its use would efficiently solve the issues encountered in spectrum managemen

High-Fidelity Spectrum Characterization with Low-Cost Sensors

With the increasing use of wireless technologies, we see a heavy use of the spectrum at certain frequencies whereas it is underutilized at other frequencies. We need to utilize the currently underutilized spectrum. Hence, a paradigm called Dynamic Spectrum Access arises. Dynamic Spectrum Access looks for opportunity to utilize this underutilized spectrum by allowing devices to opportunistically access spectrum that is not actively used. DSA, however, requires spectrum sensing and spectrum characterization across time, space, and frequency for opportunistic devices to know where to operate. Spectrum sensing is the process of collecting power level traces from the radio-frequency spectrum, whereas spectrum characterization determines how many transmitters occupy a given spectrum and what are their temporal and frequency characteristics. Traditional spectrum sensing and characterization is performed with expensive sensors, which renders the task economically-infeasible. Our project introduces a low-cost alternative, which is more mobile and cost efficient. A typical issue with low cost sensors is that the scans from the low-cost sensor are of lower quality compared to scans from a higher-cost alternative. In this end, we compare the characterizations of the spectrum from the low cost sensor to the high-cost sensor across time, frequency, and space. We conduct granularity, sensitivity,transmitter pattern, and mobility experiments to compare the scans of the two sensors in different scenarios. We analyze the two characterizations from the two sensors in a controlled setting to see if the scans of the two are comparable. From the mobility and granularity experiments, we observe that scans from the low-cost sensors are comparable to the scans from the high-cost sensors. However, as expected, we do see lower sensitivity in the low-cost sensor. Comparing the two scans will help us form a better picture of the kind of ii infrastructure we can build using the two sensors that is both economically feasible and can give us high-fidelity scans

Coordinated Dynamic Spectrum Management of LTE-U and Wi-Fi Networks

This paper investigates the co-existence of Wi-Fi and LTE in emerging unlicensed frequency bands which are intended to accommodate multiple radio access technologies. Wi-Fi and LTE are the two most prominent access technologies being deployed today, motivating further study of the inter-system interference arising in such shared spectrum scenarios as well as possible techniques for enabling improved co-existence. An analytical model for evaluating the baseline performance of co-existing Wi-Fi and LTE is developed and used to obtain baseline performance measures. The results show that both Wi-Fi and LTE networks cause significant interference to each other and that the degradation is dependent on a number of factors such as power levels and physical topology. The model-based results are partially validated via experimental evaluations using USRP based SDR platforms on the ORBIT testbed. Further, inter-network coordination with logically centralized radio resource management across Wi-Fi and LTE systems is proposed as a possible solution for improved co-existence. Numerical results are presented showing significant gains in both Wi-Fi and LTE performance with the proposed inter-network coordination approach.Comment: Accepted paper at IEEE DySPAN 201

D22.1 Definition of EuWIn@CNIT/Bologna testbed interfaces and preliminary plan of activities

Preprin

Cognitive Radio Connectivity for Railway Transportation Networks

Reliable wireless networks for high speed trains require a significant amount of data communications for enabling safety features such as train collision avoidance and railway management. Cognitive radio integrates heterogeneous wireless networks that will be deployed in order to achieve intelligent communications in future railway systems. One of the primary technical challenges in achieving reliable communications for railways is the handling of high mobility environments involving trains, which includes significant Doppler shifts in the transmission as well as severe fading scenarios that makes it difficult to estimate wireless spectrum utilization. This thesis has two primary contributions: (1) The creation of a Heterogeneous Cooperative Spectrum Sensing (CSS) prototype system, and (2) the derivation of a Long Term Evolution for Railways (LTE-R) system performance analysis. The Heterogeneous CSS prototype system was implemented using Software-Defined Radios (SDRs) possessing different radio configurations. Both soft and hard-data fusion schemes were used in order to compare the signal source detection performance in real-time fading scenarios. For future smart railways, one proposed solution for enabling greater connectivity is to access underutilized spectrum as a secondary user via the dynamic spectrum access (DSA) paradigm. Since it will be challenging to obtain an accurate estimate of incumbent users via a single-sensor system within a real-world fading environment, the proposed cooperative spectrum sensing approach is employed instead since it can mitigate the effects of multipath and shadowing by utilizing the spatial and temporal diversity of a multiple radio network. Regarding the LTE-R contribution of this thesis, the performance analysis of high speed trains (HSTs) in tunnel environments would provide valuable insights with respect to the smart railway systems operating in high mobility scenarios in drastically impaired channels

Implementation Issues of Adaptive Energy Detection in Heterogeneous Wireless Networks

Abstract Spectrum sensing (SS) enables the coexistence of non-coordinated heterogeneous wireless systems operating in the same band. Due to its computational simplicity, energy detection (ED) technique has been widespread employed in SS applications; nonetheless, the conventional ED may be unreliable under environmental impairments, justifying the use of ED-based variants. Assessing ED algorithms from theoretical and simulation viewpoints relies on several assumptions and simplifications which, eventually, lead to conclusions that do not necessarily meet the requirements imposed by real propagation environments. This work addresses those problems by dealing with practical implementation issues of adaptive least mean square (LMS)-based ED algorithms. The paper proposes a new adaptive ED algorithm that uses a variable step-size guaranteeing the LMS convergence in time-varying environments. Several implementation guidelines are provided and, additionally, an empirical assessment and validation with a software defined radio-based hardware is carried out. Experimental results show good performance in terms of probabilities of detection (P-d > 0.9) and false alarm (P-f similar to 0.05) in a range of low signal-to-noise ratios around [4, 1] dB, in both single-node and cooperative modes. The proposed sensing methodology enables a seamless monitoring of the radio electromagnetic spectrum in order to provide band occupancy information for an efficient usage among several wireless communications systems.This work has been financially supported in part by the Spanish Ministry of Economy and Competitiveness under Project 5G-NewBROs (TEC2015-66153-P MINECO/FEDER, UE), and in part by the Basque Government (IT-683-13 and ELKARTEK program under BID3A3 and BID3ABI projects) and the European Regional Development Fund, ERDF