Energy detection based cooperative spectrum sensing system for emergency networks

During emergencies, a number of rescue teams come to the field and setup their own radio communication systems. If the deployed communication setup does not coordinate among themselves properly, they may interfere with each other when using the same RF channels known as co-channel interference. Spectrum sensing is the most important and complex job for cognitive radios. Cooperation among cognitive radio nodes is needed to enhance the sensing performance. In this paper, we present an experimental study of this solution. A Software Defined Radio comprising of GNU Radio and USRP were used to capture the signal samples to build a database profile of the spectrum condition. MATLAB communications toolbox was used to analyze the data and examine the spectrum pertaining to the condition in emergency networks. The benefits of cooperative spectrum sensing in avoiding co-channel interference during emergency situations are illustrated. Cooperation among cognitive spectrum sensing nodes operating at the same frequency improves the probability of detection, and the overall efficiency of the system. Results show that the cooperative sensing scheme outperforms the individual sensing approach. It can increases the probability of detection relative to the collected samples as the key performance indicator

Energy-detection based spectrum sensing for cognitive radio on a real-time SDR platform

There has been an increase in wireless applications due to the technology boom; consequently raising the level of radio spectrum demand. However, spectrum is a limited resource and cannot be infinitely subdivided to accommodate every application. At the same time, emerging wireless applications require a lot of bandwidth for operation, and have seen exponential growth in their bandwidth usage in recent years. The current spectrum allocation technique, proposed by the Federal Communications Commission (FCC) is a fixed allocation technique. This is inefficient as the spectrum is vacant during times when the primary user is not using the spectrum. This strain on the current available bandwidth has revealed signs of an upcoming spectrum crunch; hence the need to find a solution that satisfies the increasing spectrum demand, without compromising the performance of the applications. This work leverages on cognitive radio technology as a potential solution to the spectrum usage challenge. Cognitive radios have the ability to sense the spectrum and determine the presence or absence of the primary user in a particular subcarrier band. When the spectrum is vacant, a cognitive radio (secondary user) can opportunistically occupy the radio spectrum, optimizing the radio frequency band. The effectiveness of the cognitive radio is determined by the performance of the sensing techniques. Known spectrum-sensing techniques are reviewed, which include energy detection, entropy detection, matched-filter detection, and cyclostationary detection. In this dissertation, the energy sensing technique is examined. A real-time energy detector is developed on the Software-Defined Radio (SDR) testbed that is built with Universal Software Radio Peripheral (USRP) devices, and on the GNU Radio software platform. The noise floor of the system is first analysed to determine the detection threshold, which is obtained using the empirical cumulative distribution method. Simulations are carried out using MATrix LABoratory (MATLAB) to set a benchmark. In both simulations and the SDR development platform, an Orthogonal Frequency Division Multiplexing (OFDM) signal with Quadrature Phase Shift Keying (QPSK) modulation is generated and used as the test signal

Building accurate radio environment maps from multi-fidelity spectrum sensing data

In cognitive wireless networks, active monitoring of the wireless environment is often performed through advanced spectrum sensing and network sniffing. This leads to a set of spatially distributed measurements which are collected from different sensing devices. Nowadays, several interpolation methods (e.g., Kriging) are available and can be used to combine these measurements into a single globally accurate radio environment map that covers a certain geographical area. However, the calibration of multi-fidelity measurements from heterogeneous sensing devices, and the integration into a map is a challenging problem. In this paper, the auto-regressive co-Kriging model is proposed as a novel solution. The algorithm is applied to model measurements which are collected in a heterogeneous wireless testbed environment, and the effectiveness of the new methodology is validated

Preliminary investigation of the practicality of an industrial training for engineering technology program-industries view

One of the important aspects of Engineering Technology (ET) program is the students must be able to apply a significant hands-on job throughout the program. Apart from laboratory work carried out at the university, the industrial training components can also contribute a significant practical work to enhance the skills of the students. In this study, the difference between ET and Engineering program is distinguished by proposing longer periods of industrial training in ET program. However, the effectiveness of longer periods of training must be investigated in order to find out whether this framework has to be retained for future training. For this, the university has structured the industrial training by imposing the students to undergo two (2) months training during the third (3rd) semester of year two (2), another two (2) months during the third (3rd) semester of year three (3) and finally, six (6) months during the last semester of fourth (4th) year (i.e. final semester). An interview has been conducted with two industrial panels to find out the effectiveness of the proposed training. A few suggestions and ideas given by both panels were considered for the development for industrial training syllabus in ET program

Real-Time Implementation of Spectrum Sensing Techniques in Cognitive Radios

Wireless communication requirements of higher sampling frequencies and bandwidth are ever increasing. For this purpose, exploitation of underutilized spectrum bands was one the challenging research targets. Cognitive Radio (CR) is a promising solution to overcome the “limited bandwidth” issue. Software defined radio (SDR) is the enabler of CR. The aim of the thesis is to adopt the vacant TV channels for secondary users. Spectrum sensing prototype has been proposed to detect TV white space (TVWS). The prototype has been developed using Universal Software Radio Peripheral (USRP) and examined to sense TVWS in the real time world. The conducting analysis of obtained measurements showed the state of unoccupied spectrum bands in the UHF band ranges from 500 MHz to 698 MHz in the urban area ofWindsor, Ontario, Canada. Two different spectrum sensing techniques namely, the energy detector, and pilot-tone detector were employed to get the result with minimum computational complexity. Experiments show that the presence of incumbent users can be easily detected using the spectrum sensing techniques mentioned in the thesis. The experimental results have demonstrated the validity of the proposed prototyp

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

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