Implementation of Spectrum-Sensing for Cognitive Radio Using USRP with GNU Radio and a Cloud Server (original) (raw)
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A spectrum sensing approaches in cognitive radio network by using cloud computing environment
Bulletin of Electrical Engineering and Informatics, 2022
A spectrum agreement has failed to meet the demands of new applications due to the fixed spectrum allocation (FSA) concept. But current efforts are targeted towards the utilization of cognitive radio as a way of addressing the issue of resources deficiency. The number of radio spectrum users keeps increasing daily owing to the advancement in technology in all aspects of life; even the licensed band users are currently demanding for extension of their radio spectrum and to balance the congestion in radio spectrum, some users may have to be placed on other bands. This article focused on voids detection (via spectrum sensing) in radio spectrum and secondary user assignment in cloud computing. Spectrum sensing was approached in two was in this study-underlay and interweave spectrum allocation. Both approaches are evaluated using certain performance metrics, such as throughput enhancement and queuing time minimization.
Experimental Spectrum Sensing Measurements using USRP Software Radio Platform and GNU-Radio
Proceedings of the 9th International Conference on Cognitive Radio Oriented Wireless Networks, 2014
In cognitive radio, the secondary users are able to sense the spectral environment and use this information to opportunistically access the licensed spectrum in the absence of the primary users. In this paper, we present an experimental study that evaluates the performance of two different spectrum sensing techniques to detect primary user signals in real environment. The considered spectrum sensing techniques are: sequential energy and cyclosationary feature based detectors. An Universal Software Radio Peripheral platform with GNU-Radio is employed for implementation purpose. We analyzed the performances of both spectrum sensing methods by measuring the detection probabilities as a function of SNR for a given false alarm probability. As predicted theoretically, experimental measurements show that the cyclostationnary feature detector performs better than the sequential energy detector. However sequential energy detector can be used for reduction of sensing time in the presence of strong signals.
Energy detection sensing based on GNU radio and USRP: An analysis study
2009
Cognitive radio wireless networks are an emerging communication paradigm to effectively address spectrum scarcity challenge. Spectrum sensing plays a paramount role in cognitive radio, which is widely agreed to be the most promising method for alleviating the symptom of RF spectral scarcity. Dynamic access of unused spectrum via a cognitive radio asks for flexible radio circuits that can work at an arbitrary radio frequency. In this paper, we analyze the performance of spectrum sensing on GNU Radio system with USRP. We investigating spectrum scarcity and proposed the algorithm that performed and measuring the energy of Rx signal in a fixed bandwidth, W, over an observation time window, T. The results presented that it can detected of primary user signal over the fixed bandwidth which occupied the spectrum.
Spectrum sensing measurement using GNU radio & USRP software radio platform
2011
Spectrum utilization can be significantly improved by adopting cognitive radio (CR) technology. Such radios are able to sense the spectral environment and use this information to opportunistically provide wireless links that meet the user communications requirements optimally. To achieve the goal of cognitive radio, it is a fundamental requirement that the cognitive user (CU) performs spectrum sensing to detect the presence of the primary user (PU) signal before a spectrum is accessed as to avoid harmful interference. Therefore, two probabilities are of interest; the probability of detection, P d and the probability of false alarm, P fa. In this paper, we investigate sensing performance implemented on real-time testbed of GNU Radio and USRP Software Defined Radio (SDR) communication platform operating at 2.48 GHz with a bandwidth of 4 MHz. Energy detector utilizing 1024 FFT bin is the sensing mechanism used in the experimental setup. The acquired experimental results of P d and P fa are duly analyzed and verified to be comparable to the curve of the theoretical framework for line-of-sight indoor environment. It is observed that at a target P fa of 5%, the optimal decision threshold for PU detection is-39 dB. The plot of measured number of samples needed for a desired P d for various received signal levels, representing various signal-to-noise (SNR) conditions, is also included. At SNR of 0 dB and a target Quality of Service (QoS) set at P d of 90%, it is found out that the required sensing time for our GNU Radio USRP based CR system is equal to 31.59ms.
Spectrum Sensing Measurement using GNU Radio and USRP Software Radio Platform
2011
Spectrum utilization can be significantly improved by adopting cognitive radio (CR) technology. Such radios are able to sense the spectral environment and use this information to opportunistically provide wireless links that meet the user communications requirements optimally. To achieve the goal of cognitive radio, it is a fundamental requirement that the cognitive user (CU) performs spectrum sensing to detect the presence of the primary user (PU) signal before a spectrum is accessed as to avoid harmful interference. Therefore, two probabilities are of interest; the probability of detection, P d and the probability of false alarm, P fa. In this paper, we investigate sensing performance implemented on real-time testbed of GNU Radio and USRP Software Defined Radio (SDR) communication platform operating at 2.48 GHz with a bandwidth of 4 MHz. Energy detector utilizing 1024 FFT bin is the sensing mechanism used in the experimental setup. The acquired experimental results of P d and P fa are duly analyzed and verified to be comparable to the curve of the theoretical framework for line-of-sight indoor environment. It is observed that at a target P fa of 5%, the optimal decision threshold for PU detection is-39 dB. The plot of measured number of samples needed for a desired P d for various received signal levels, representing various signal-to-noise (SNR) conditions, is also included. At SNR of 0 dB and a target Quality of Service (QoS) set at P d of 90%, it is found out that the required sensing time for our GNU Radio USRP based CR system is equal to 31.59ms.
2016
The paper describes a centralized cooperative spectrum sensing system, implemented on Universal Software Radio Peripheral (USRP) hardware platforms driven by the Genuinely Not Unix (GNU) Radio software. Spectrum sensing is realized by energy detection and a new block of energy detector with uncertainty is developed using GNU Radio out-of-tree implementation. A centralized scheme for cooperative spectrum sensing is applied and a hard global decision is taken in a fusion center which collects the local decisions from secondary users, selects those of them which will be taken for global decision estimation and performs classical decision fusion logic, such as AND, OR, MAJORITY rules. Based on measured data, the probabilities of detection for different Signal-to-noise ratios (SNRs) are built for each secondary user and for different scenarios of cooperative sensing.
Performance Comparison of Energy Detection Based Spectrum Sensing for Cognitive Radio Networks
2015
With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the policy of fixed spectrum assignment produces a bottleneck for more efficient spectrum utilization, such that a great portion of the licensed spectrum is severely under-utilized. So the concept of cognitive radio was introduced to address this issue.The inefficient usage of the limited spectrum necessitates the development of dynamic spectrum access techniques, where users who have no spectrum licenses, also known as secondary users, are allowed to use the temporarily unused licensed spectrum. For this purpose we have to know the presence or absence of primary users for spectrum usage. So spectrums sensing is one of the major requirements of cognitive radio.Many spectrum sensing techniques have been developed to sense the presence or absence of a licensed user. This paper evaluates the performance of the energy detection based sp...
International Journal of Electrical and Computer Engineering (IJECE), 2017
This paper presents the performance evaluation of the Energy Detector technique, which is one of the most popular Spectrum Sensing (SS) technique for Cognitive Radio (CR). SS is the ability to detect the presence of a Primary User (PU) (i.e. licensed user) in order to allow a Secondary User (SU) (i.e unlicensed user) to access PU's frequency band using CR, so that the available frequency bands can be used efficiently. We used for implementation an Universal Software Radio Peripheral (USRP), which is the most used Software Defined Radio (SDR) device for research in wireless communications. Experimental measurements show that the Energy Detector can obtain good performances in low Signal to Noise Ratio (SNR) values. Furthermore, computer simulations using MATLAB are closer to those of USRP measurements.
Energy-detection based spectrum sensing for cognitive radio on a real-time SDR platform
2016
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. The results obtained show that the real-time energy detector can detect signals with low Signal-to-Noise Ratios (SNRs) down to-8 dB at desired values of probability of detection (! "# ≥ 0.9), and probability of false vi alarm# #! *+ ≤ 0.1# at a sample size of 2048. This satisfies the IEEE 802.22 WRAN standard for TV band sensing. An energy spectrum sensing SDR testbed is successfully built and tested as proof of concept. This work leaves a testbed for other reaserchers in the COMMED Research Group that can be used for wireless communication experimentation. In addition, the USRP configuration and Out-of-Tree (OOT) module implementation method using GNU Radio Companion (GRC) is clearly documented. vii Acknowledgements To God, who saw the future before I could even fathom it. Who made me in His image and likeness, His mind becoming my mind. For the grace He so lavished during the course of this work, I am forever grateful. My sincere gratitude goes to my supervisor Professor Mqhele E. Dlodlo, for the unwavering support, encouragement and patience that saw me through the completion of my Masters degree. Thank you for believing in me. Many thanks to Michael Dickens from Ettus Research. Thank you for the technical support and encouragement in the development of the testbed. My heartfelt gratitude goes to Dr Sesham Srinu of the University of Cape Town. Thank you for your time and assistance in the conceptualization of the work. To the COMMED Research Group of the University of Cape Town, I am sincerely grateful for each one of you. You all played a significant role in the completion of this work. I am sincerely grateful. Special thanks goes to Frederick Kumi, Lerato Mahopi, Henry Ohize and Nixon Thuo Ng'ethe, thank you for being dependable. To Valerie Chiriseri, thank you for being God's outstretched arm. To my friends who became family Bashangwanye Magwape, Lusanda Gwayi and Theophilus Dzingai. Thank you for all the support. To mum, dad and my siblings, I would not have asked to be born in another family! Thank you a million for your relentless love and support. Lastly, special thanks goes to my sponsors the National Research Fund (NRF). Thank you for the investment, the future of Africa is indeed bright! viii Table of Contents Declaration .
Energy Detection Based Spectrum Sensing In Cognitive Radio Network
International Journal of MC Square Scientific Research, 2013
Cognitive radio (CR) is the enabling system for sustaining dynamic spectrum admittance: the policy that addresses the spectrum shortage difficulty that is encountered in many countries. The spectrum sensing trouble has gained new features with cognitive radio networks. Radio spectrum is the most expensive reserve in wireless communication. The cognitive radio and cognitive based networking are transforming the fixed spectrum allocation based communication systems in to dynamic spectrum allocation. Cognitive radios are smart devices with ability to detect environmental situations and can change its factors according to the necessity to get the optimized performance at the individual nodes or at network level Thus, CR is widely regarded as one of the most talented technologies for future wireless communications.