Exploiting the pilot pattern orthogonality of ofdma signals for the estimation of base stations number of antennas

International audienceIn a recent work, we proposed a GLR test dedicated to the identification of OFDM systems. In the present paper, we show that the proposed technique can be extended for the estimation of the number of antennas used by a base station. This extension is made possible thanks to the orthogonality property that exhibit the pilot pattern associated to the different antennas. Thanks to a multihypothesis testing we show that the number of transmitting antennas is estimated using only one antenna at the receiver and without any knowledge of the pilot sequence

Enhanced Spectrum Sensing for Cognitive Cellular Systems

This dissertation aims at improving spectrum sensing algorithms in order to effectively apply them to cellular systems. In wireless communications, cellular systems occupy a significant part of the spectrum. The spectrum usage for cellular systems are rapidly expanding due to the increasing demand for wireless services in our society. This results in radio frequency spectrum scarcity. Cellular systems can effectively handle this issue through cognitive mechanisms for spectrum utilization. Spectrum sensing plays the first stage of cognitive cycles for the adaptation to radio environments. This dissertation focuses on maximizing the reliability of spectrum sensing to satisfy regulation requirements with respect to high spectrum sensing performance and an acceptable error rate. To overcome these challenges, characteristics of noise and manmade signals are exploited for spectrum sensing. Moreover, this dissertation considers system constraints, the compatibility with the current and the trends of future generations. Newly proposed and existing algorithms were evaluated in simulations in the context of cellular systems. Based on a prototype of cognitive cellular systems (CCSs), the proposed algorithms were assessed in realistic scenarios. These algorithms can be applied to CCSs for the awareness of desired signals in licensed and unlicensed bands. For orthogonal frequency-division multiplexing (OFDM) signals, this dissertation exploits the characteristics of pilot patterns and preambles for new algorithms. The new algorithms outperform the existing ones, which also utilize pilot patterns. Additionally, the new algorithms can work with short observation durations, which is not possible with the existing algorithms. The Digital Video Broadcasting - Terrestrial (DVB-T) standard is taken as an example application for the algorithms. The algorithms can also be developed for filter bank multicarrier (FBMC) signals, which are a potential candidate for multiplexing techniques in the next cellular generations. The experimental results give insights for the reliability of the algorithms, taking system constraints v into account. Another new sensing algorithm, based on a preamble, is proposed for the DVBT2 standard, which is the second generation of of DVB system. DVB-T2 systems have been deployed in worldwide regions. This algorithm can detect DVB-T2 signals in a very short observation interval, which is helpful for the in-band sensing mode, to protect primary users (in nearly real-time) from the secondary transmission. An enhanced spectrum sensing algorithm based on cyclostationary signatures is proposed to detect desired signals in very low signal-to-noise ratios (SNRs). This algorithm can be developed to detect the single-carrier frequency division multiple access (SC-FDMA) signal, which is adopted for the uplink of long-term evolution (LTE) systems. This detector substantially outperforms the existing detection algorithms with the marginal complexity of some scalar multiplications. The test statistics are explicitly formulated in mathematical formulas, which were not presented in the previous work. The formulas and simulation results provide a useful strategy for cyclostationarity-based detection with different modulation types. For multiband spectrum sensing, an effective scheme is proposed not only to detect but also to classify LTE signals in multiple channels in a wide frequency range. To the best of our knowledge, no scheme had previously been described to perform the sensing tasks. The scheme is reliable and flexible for implementation, and there is almost no performance degradation caused by the scheme compared to single-channel spectrum sensing. The multiband sensing scheme was experimentally assessed in scenarios where the existing infrastructures are interrupted to provide mobile communications. The proposed algorithms and scheme facilitate cognitive capabilities to be applied to real cellular communications. This enables the significantly improved spectrum utilization of CCSs

Towards versatile and robust spectrum sensing in cognitive radio

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Blind Demodulation of Pass Band OFDMA Signals and Jamming Battle Damage Assessment Utilizing Link Adaptation

This research focuses on blind demodulation of a pass band OFDMA signal so that jamming effectiveness can be assessed; referred to in this research as BDA. The research extends, modifies and collates work within literature to perform a new method of blindly demodulating of a passband OFDMA signal, which exhibits properties of the 802.16 Wireless MAN OFDMA standard, and presents a novel method for performing BDA via observation of SC LA. Blind demodulation is achieved by estimating the carrier frequency, sampling rate, pulse shaping filter roll off factor, synchronization parameters and CFO. The blind demodulator\u27s performance in AWGN and a perfect channel is evaluated where it improves using a greater number OFDMA DL symbols and increased CP length. Performance in a channel with a single multi-path interferer is also evaluated where the blind demodulator\u27s performance is degraded. BDA is achieved via observing SC LA modulation behavior of the blindly demodulated signal between successive OFDMA DL sub frames in two scenarios. The first is where modulation signaling can be used to observe change of SC modulation. The second assumes modulation signaling is not available and the SC\u27s modulation must be classified. Classification of SC modulation is performed using sixth-order cumulants where performance increases with the number of OFDMA symbols. The SC modulation classi er is susceptible to the CFO caused by blind demodulation. In a perfect channel it is shown that SC modulation can be classified using a variety of OFDMA DL sub frame lengths in symbols. The SC modulation classifier experienced degraded performance in a multi-path channel and it is recommended that it is extended to perform channel equalization in future work

Detection of OFDM Signals Using Pilot Tones and Applications to Spectrum Sensing for Cognitive Radio Systems

Nowadays there are an increasing number of wireless devices which support wireless networking and the need for higher data rate communication is increasing rabidly. As more and more systems go wireless, approaching technologies will face spectral crowding and existence of wireless devices will be an important issue. Because of the limited bandwidth availability, accepting the request for higher capacity and data rates is a challenging task, demanding advanced technologies that can offers new methods of using the available radio spectrum. Cognitive radio introduces a key solution to the spectral increasing issue by presenting the opportunistic usage of spectrum that is not heavily occupied by licensed users. It is a latest idea in wireless communications systems which objective to have more adaptive and aware communication devices which can make better use of available natural resources. Cognitive radio appears to be an attractive solution to the spectral congestion problem by introducing the notion of opportunistic spectrum use. Cognitive radios can operate as a secondary systems on top of existence system which are called primary (or licensed) systems. In this case, secondary (cognitive) users need to detect the unused spectrum in order to be able to access it. Because of its many advantages, orthogonal frequency division multiplexing (OFDM) has been successfully used in numerous wireless standards and technologies. It\u27s shown that OFDM will play an important role in realizing the cognitive radio concept as well by providing a proven, scalable, and adaptive technology for air interface. Researches show that OFDM technique is considered as a candidate for cognitive radio systems. The objective of this dissertation is to explore detecting of OFDM modulated signals using pilot tones information. Specifically we applying Time-Domain Symbol Cross-Correlation (TDSC) method in the confect of actual 4G wireless standards such as WIMAX and LTE. This detection is only based upon the knowledge of pilot structures without knowledge of received signal so that, it can be performed on every portion of the received signal. The approach induces Cross-Correlation between pilots subcarriers and exploits the deterministic and periodic characteristics of pilot mapping in the time frequency domain

Opportunistic Access in Frequency Hopping Cognitive Radio Networks

Researchers in the area of cognitive radio often investigate the utility of dynamic spectrum access as a means to make more efficient use of the radio frequency spectrum. Many studies have been conducted to find ways in which a secondary user can occupy spectrum licensed to a primary user in a manner which does not disrupt the primary user\u27s performance. This research investigates the use of opportunistic access in a frequency hopping radio to mitigate the interference caused by other transmitters in a contentious environment such as the unlicensed 2.4 GHz region. Additionally, this work demonstrates how dynamic spectrum access techniques can be used not only to prevent interfering with other users but also improve the robustness of a communication system

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 TecnologiaA change in paradigm when it comes to controlling radio transmissions is in course. Tasks usually executed in an exclusive class of hardware systems are increasingly controlled by software systems. A deep change to the software domain is foreseeable, creating a true Software Defined Radio. At the same time this change occurs, the radioelectric spectrum is almost completely licensed. However, the spectrum is rarely used to its full extent over time, enabling its opportunistic use while the licensed devices do not communicate. This is a part of the notion of Cognitive Radio, a new kind of radio capable of using the spectrum in an opportunistic way. These two new paradigms in radio access can be combined to produce a exible and reliable radio, overcoming the issues with radioelectric spectrum scarcity. This dissertation starts an exploration in this area by combining these two paradigms through the use of an Energy Detector implemented in a Universal Software Radio Peripheral device and using the GNURadio suite. The performance of such a system is tested by calculating the Probabilities of Detection and False Alarm in real scenarios and comparing them to the expected theoretical values. A method for defining thresholds for narrowband signals is also tested based on works in Information Theory concepts, i.e.,the Akaike Information Criteria and the Minimum Description Length. The results are tested for a real transmission using two USRP platforms communicating with each other,one acting as the licensed user and the other acting as the secondary, opportunistic user. Finally, we highlight the technological work developed in this dissertation, which may support future research works through the use of the developed scripts, allowing a faster method to test algorithms with different parameterization

Wideband Spectrum Sensing for Dynamic Spectrum Sharing

The proliferation of wireless devices grows exponentially, demanding more and more data communication capacity over wireless links. Radio spectrum is a scarce resource, and traditional wireless networks deployed by Mobile Network Operators (MNO) are based on an exclusive spectrum band allocation. However, underutilization of some licensed bands in time and geographic domains has been reported, especially in rural areas or areas away from high population density zones. This coexistence of increasingly high data communication needs and spectrum underutilization is an incomprehensible scenario. A more rational and efficient use of the spectrum is the possibility of Licensed Users (known as Primary Users – PU) to lease the spectrum, when not in use, to Unlicensed Users (known as Secondary Users – SU), or allowing the SU to opportunistically use the spectrum after sensing and verifying that the PU is idle. In this latter case, the SU must stop transmitting when the PU becomes active. This thesis addresses the spectrum sensing task, which is essential to provide dynamic spectrum sharing between PUs and SUs. We show that the Spectral Correlation Function (SCF) and the Spectral Coherence Function (SCoF) can provide a robust signal detection algorithm by exploiting the cyclostationary characteristics of the data communication signal. We enhance the most used algorithm to compute de SCF - the FAM (FFT Accumulation Method) algorithm – to efficiently compute the SCF in a local/zoomed region of the support ( ; ) plane (frequency/cycle frequency plane). This will provide the quick identification of spectral bands in use by PUs or free, in a wideband sampling scenario. Further, the characterization of the probability density of the estimates of the SCF and SCoF when only noise is present, using the FAM algorithm, will allow the definition of an adaptive threshold to develop a blind (with respect to the noise statistics) Constant False Alarm Rate (CFAR) detector (using the SCoF) and also a CFAR and a Constant Detection Rate (CDR) detector when that characterization is used to obtain an estimate of the background noise variance (using the SCF).A proliferação de dispositivos sem fios cresce de forma exponencial, exigindo cada vez mais capacidade de comunicação de dados através de ligações sem fios. O espectro radioelétrico é um recurso escasso, e as redes sem fios tradicionais implantadas pelos Operadores de Redes Móveis baseiam-se numa atribuição exclusiva de bandas do espectro. No entanto, tem sido relatada a subutilização de algumas bandas licenciadas quer ao longo do tempo, quer na sua localização geográfica, especialmente em áreas rurais, e em áreas longe de zonas de elevada densidade populacional. A coexistência da necessidade cada vez maior de comunicação de dados, e a subutilização do espectro é um cenário incompreensível. Uma utilização mais racional e eficiente do espectro pressupõe a possibilidade dos Utilizadores Licenciados (conhecidos como Utilizadores Primários – Primary Users - PU) alugarem o espectro, quando este não está a ser utilizado, a Utilizadores Não Licenciados (conhecidos como Utilizadores Secundários – Secondary Users - SU), ou permitir ao SU utilizar oportunisticamente o espectro após a deteção e verificação de que o PU está inativo. Neste último caso, o SU deverá parar de transmitir quando o PU ficar ativo. Nesta tese é abordada a tarefa de deteção espectral, que é essencial para proporcionar a partilha dinâmica do espectro entre PUs e SUs. Mostra-se que a Função de Correlação Espectral (Spectral Correlation Function - SCF) e a Função de Coerência Espectral (Spectral Coherence Function - SCoF) permitem o desenvolvimento de um algoritmo robusto de deteção de sinal, explorando as características ciclo-estacionárias dos sinais de comunicação de dados. Propõe-se uma melhoria ao algoritmo mais utilizado para cálculo da SCF – o método FAM (FFT Accumulation Method) - para permitir o cálculo mais eficiente da SCF numa região local/ampliada do plano de suporte / (plano de frequência/frequência de ciclo). Esta melhoria permite a identificação rápida de bandas espectrais em uso por PUs ou livres, num cenário de amostragem de banda larga. Adicionalmente, é feita a caracterização da densidade de probabilidade das estimativas da SCF e SCoF quando apenas o ruído está presente, o que permite a definição de um limiar adaptativo, para desenvolver um detetor de Taxa de Falso Alarme Constante (Constant False Alarm Rate – CFAR) sem conhecimento do ruído de fundo (usando a SCoF) e também um detetor CFAR e Taxa de Deteção Constante (Constant Detection Rate – CDR), quando se utiliza aquela caracterização para obter uma estimativa da variância do ruído de fundo (usando a SCF)

Robust spectrum sensing techniques for cognitive radio networks

Cognitive radio is a promising technology that improves the spectral utilisation by allowing unlicensed secondary users to access underutilised frequency bands in an opportunistic manner. This task can be carried out through spectrum sensing: the secondary user monitors the presence of primary users over the radio spectrum periodically to avoid harmful interference to the licensed service. Traditional energy based sensing methods assume the value of noise power as prior knowledge. They suffer from the noise uncertainty problem as even a mild noise level mismatch will lead to significant performance loss. Hence, developing an efficient robust detection method is important. In this thesis, a novel sensing technique using the F-test is proposed. By assuming a multiple antenna assisted receiver, this detector uses the F-statistic as the test statistic which offers absolute robustness against the noise variance uncertainty. In addition, since the channel state information (CSI) is required to be known, the impact of CSI uncertainty is also discussed. Results show the F-test based sensing method performs better than the energy detector and has a constant false alarm probability, independent of the accuracy of the CSI estimate. Another main topic of this thesis is to address the sensing problem for non-Gaussian noise. Most of the current sensing techniques consider Gaussian noise as implied by the central limit theorem (CLT) and it offers mathematical tractability. However, it sometimes fails to model the noise in practical wireless communication systems, which often shows a non-Gaussian heavy-tailed behaviour. In this thesis, several sensing algorithms are proposed for non-Gaussian noise. Firstly, a non-parametric eigenvalue based detector is developed by exploiting the eigenstructure of the sample covariance matrix. This detector is blind as no information about the noise, signal and channel is required. In addition, the conventional energy detector and the aforementioned F-test based detector are generalised to non-Gaussian noise, which require the noise power and CSI to be known, respectively. A major concern of these detection methods is to control the false alarm probability. Although the test statistics are easy to evaluate, the corresponding null distributions are difficult to obtain as they depend on the noise type which may be unknown and non-Gaussian. In this thesis, we apply the powerful bootstrap technique to overcome this difficulty. The key idea is to reuse the data through resampling instead of repeating the experiment a large number of times. By using the nonparametric bootstrap approach to estimate the null distribution of the test statistic, the assumptions on the data model are minimised and no large sample assumption is invoked. In addition, for the F-statistic based method, we also propose a degrees-of-freedom modification approach for null distribution approximation. This method assumes a known noise kurtosis and yields closed form solutions. Simulation results show that in non-Gaussian noise, all the three detectors maintain the desired false alarm probability by using the proposed algorithms. The F-statistic based detector performs the best, e.g., to obtain a 90% detection probability in Laplacian noise, it provides a 2.5 dB and 4 dB signal-to-noise ratio (SNR) gain compared with the eigenvalue based detector and the energy based detector, respectively