Spectrum sensing through software defined radio

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Fully Distributed Cooperative Spectrum Sensing for Cognitive Radio Networks

Cognitive radio networks (CRN) sense spectrum occupancy and manage themselves to operate in unused bands without disturbing licensed users. The detection capability of a radio system can be enhanced if the sensing process is performed jointly by a group of nodes so that the effects of wireless fading and shadowing can be minimized. However, taking a collaborative approach poses new security threats to the system as nodes can report false sensing data to force a wrong decision. Providing security to the sensing process is also complex, as it usually involves introducing limitations to the CRN applications. The most common limitation is the need for a static trusted node that is able to authenticate and merge the reports of all CRN nodes. This paper overcomes this limitation by presenting a protocol that is suitable for fully distributed scenarios, where there is no static trusted node.

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselvesto operate in unused bands without disturbing licensed users. The detection capability of aradio system can be enhanced if the sensing process is performed jointly by a group of nodesso that the effects of wireless fading and shadowing can be minimized. However, taking acollaborative approach poses new security threats to the system as nodes can report falsesensing data to reach a wrong decision. This paper makes a review of secure cooperativespectrum sensing in cognitive radio networks. The main objective of these protocols is toprovide an accurate resolution about the availability of some spectrum channels, ensuring thecontribution from incapable users as well as malicious ones is discarded. Issues, advantagesand disadvantages of such protocols are investigated and summarized.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Spectrum sensing su piattaforma software defined radio: Implementazione e test su stick dvb-t

Spectrum sensing su piattaforma software defined radio: Implementazione e test su stick dvb-t

Compressed sensing based cyclic feature spectrum sensing for cognitive radios

Spectrum sensing is currently one of the most challenging design problems in cognitive radio. A robust spectrum sensing technique is important in allowing implementation of a practical dynamic spectrum access in noisy and interference uncertain environments. In addition, it is desired to minimize the sensing time, while meeting the stringent cognitive radio application requirements. To cope with this challenge, cyclic spectrum sensing techniques have been proposed. However, such techniques require very high sampling rates in the wideband regime and thus are costly in hardware implementation and power consumption. In this thesis the concept of compressed sensing is applied to circumvent this problem by utilizing the sparsity of the two-dimensional cyclic spectrum. Compressive sampling is used to reduce the sampling rate and a recovery method is developed for re- constructing the sparse cyclic spectrum from the compressed samples. The reconstruction solution used, exploits the sparsity structure in the two-dimensional cyclic spectrum do-main which is different from conventional compressed sensing techniques for vector-form sparse signals. The entire wideband cyclic spectrum is reconstructed from sub-Nyquist-rate samples for simultaneous detection of multiple signal sources. After the cyclic spectrum recovery two methods are proposed to make spectral occupancy decisions from the recovered cyclic spectrum: a band-by-band multi-cycle detector which works for all modulation schemes, and a fast and simple thresholding method that works for Binary Phase Shift Keying (BPSK) signals only. In addition a method for recovering the power spectrum of stationary signals is developed as a special case. Simulation results demonstrate that the proposed spectrum sensing algorithms can significantly reduce sampling rate without sacrifcing performance. The robustness of the algorithms to the noise uncertainty of the wireless channel is also shown.

Achievable rates and outage probability of cognitive radio with dynamic frequency hopping under imperfect spectrum sensing

In this study, the authors propose simple methods to evaluate the achievable rates and outage probability of a cognitive radio (CR) link that takes into account the imperfectness of spectrum sensing. In the considered system, the CR transmitter and receiver correlatively sense and dynamically exploit the spectrum pool via dynamic frequency hopping. Under imperfect spectrum sensing, false-alarm and miss-detection occur which cause impulsive interference emerged from collisions due to the simultaneous spectrum access of primary and cognitive users. That makes it very challenging to evaluate the achievable rates. By first examining the static link where the channel is assumed to be constant over time, they show that the achievable rate using a Gaussian input can be calculated accurately through a simple series representation. In the second part of this study, they extend the calculation of the achievable rate to wireless fading environments. To take into account the effect of fading, they introduce a piece-wise linear curve fitting-based method to approximate the instantaneous achievable rate curve as a combination of linear segments. It is then demonstrated that the ergodic achievable rate in fast fading and the outage probability in slow fading can be calculated to achieve any given accuracy level.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

A Secure and Anonymous Cooperative Sensing Protocol for Cognitive Radio Networks

Spectrum is an essential resource for the provision of mobile services. In order to control and delimit its use, governmental agencies set up regulatory policies. Unfortunately, such policies have led to a deficiency of spectrum as only few frequency bands are left unlicensed, and these are used for the majority of new emerging wireless applications. One promising way to alleviate the spectrum shortage problem is adopting a spectrum sharing paradigm in which frequency bands are used opportunistically. Cognitive radio is the key technology to enable this shift of paradigm.Cognitive radio networks are self-organized systems in which devices cooperate to use those spectrum ranges that are not occupied by licensed users. They carry out spectrum sensing in order to detect vacant channels that can be used for communication. Even though spectrum sensing is an active area of research, an important issue remains unsolved: the secure authentication of sensing reports. Not providing security enables the input of false data in the system thus empowering false results. This paper presents a distributed protocol based on wireless physical layer security, symmetric cryptography and one-way functions that allows determining a final sensing decision from multiple sources in a quick and secure way, as well as it preserves users¿ privacy.

A Secure Cooperative Sensing Protocol for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancyand manage themselves to operate in unused bands without disturbing licensed users. Spectrum sensing is more accurate if jointly performed by several reliable nodes. Even though cooperative sensing is an active area of research, the secureauthentication of local sensing reports remains unsolved, thus empowering false results. This paper presents a distributed protocol based on digital signatures and hash functions, and ananalysis of its security features. The system allows determining a final sensing decision from multiple sources in a quick and secure way.

Cognitive radio applications for enhanced spectrum efficiency

The aim of this thesis is the study of techniques for efficient management and use of the spectrum based on cognitive radio technology. The ability of cognitive radio technologies to adapt to the real-time conditions of its operating environment, offers the potential for more flexible use of the available spectrum. In this context, the international interest is particularly focused on the “white spaces” in the UHF band of digital terrestrial television. Spectrum sensing and geo-location database have been considered in order to obtain information on the electromagnetic environment. Different methodologies have been considered in order to investigate spectral resources potentially available for the white space devices in the TV band. The adopted methodologies are based on the geo-location database approach used either in autonomous operation or in combination with sensing techniques. A novel and computationally efficient methodology for the calculation of the maximum permitted white space device EIRP is then proposed. The methodology is suitable for implementation in TV white space databases. Different Italian scenarios are analyzed in order to identify both the available spectrum and the white space device emission limits. Finally two different applications of cognitive radio technology are considered. The first considered application is the emergency management. The attention is focused on the consideration of both cognitive and autonomic networking approaches when deploying an emergency management system. The cognitive technology is then considered in applications related to satellite systems. In particular a hybrid cognitive satellite-terrestrial is introduced and an analysis of coexistence between terrestrial and satellite networks by considering a cognitive approach is performed.

Approccio combinato geo-location database e sensing per individuare i livelli di potenza trasmissibili da white space device

La Cognitive Radio è un dispositivo in grado di reagire ai cambiamenti dell’ambiente radio in cui opera, modificando autonomamente e dinamicamente i propri parametri funzionali tra cui la frequenza, la potenza di trasmissione e la modulazione. Il principio di base di questi dispositivi è l’accesso dinamico alle risorse radio potenzialmente non utilizzate, con cui utenti non in possesso di licenze possono sfruttare le frequenze che in un determinato spazio temporale non vengono usate, preoccupandosi di non interferire con gli utenti che hanno privilegi su quella parte di spettro. Devono quindi essere individuati i cosiddetti “spectrum holes” o “white spaces”, parti di spettro assegnate ma non utilizzate, dai quali prendono il nome i dispositivi.Uno dei modi per individuare gli “Spectrum holes” per una Cognitive Radio consiste nel cercare di captare il segnale destinato agli utenti primari; questa tecnica è nota con il nome di Spectrum Sensing e consente di ottenere essenzialmente una misura all’interno del canale considerato al fine di determinare la presenza o meno di un servizio protetto. La tecnica di sensing impiegata da un WSD che opera autonomamente non è però molto efficiente in quanto non garantisce una buona protezione ai ricevitori DTT che usano lo stesso canale sul quale il WSD intende trasmettere.A livello europeo la soluzione che è stata ritenuta più affidabile per evitare le interferenze sui ricevitori DTT è rappresentata dall’uso di un geo-location database che opera in collaborazione con il dispositivo cognitivo.Lo scopo di questa tesi è quello di presentare un algoritmo che permette di combinare i due approcci di geo-location database e Sensing per definire i livelli di potenza trasmissibile da un WSD.