Spectrum sensing for cognitive radios: Algorithms, performance, and limitations

Inefficient use of radio spectrum is becoming a serious problem as more and more wireless systems are being developed to operate in crowded spectrum bands. Cognitive radio offers a novel solution to overcome the underutilization problem by allowing secondary usage of the spectrum resources along with high reliable communication. Spectrum sensing is a key enabler for cognitive radios. It identifies idle spectrum and provides awareness regarding the radio environment which are essential for the efficient secondary use of the spectrum and coexistence of different wireless systems. The focus of this thesis is on the local and cooperative spectrum sensing algorithms. Local sensing algorithms are proposed for detecting orthogonal frequency division multiplexing (OFDM) based primary user (PU) transmissions using their autocorrelation property. The proposed autocorrelation detectors are simple and computationally efficient. Later, the algorithms are extended to the case of cooperative sensing where multiple secondary users (SUs) collaborate to detect a PU transmission. For cooperation, each SU sends a local decision statistic such as log-likelihood ratio (LLR) to the fusion center (FC) which makes a final decision. Cooperative sensing algorithms are also proposed using sequential and censoring methods. Sequential detection minimizes the average detection time while censoring scheme improves the energy efficiency. The performances of the proposed algorithms are studied through rigorous theoretical analyses and extensive simulations. The distributions of the decision statistics at the SU and the test statistic at the FC are established conditioned on either hypothesis. Later, the effects of quantization and reporting channel errors are considered. Main aim in studying the effects of quantization and channel errors on the cooperative sensing is to provide a framework for the designers to choose the operating values of the number of quantization bits and the target bit error probability (BEP) for the reporting channel such that the performance loss caused by these non-idealities is negligible. Later a performance limitation in the form of BEP wall is established for the cooperative sensing schemes in the presence of reporting channel errors. The BEP wall phenomenon is important as it provides the feasible values for the reporting channel BEP used for designing communication schemes between the SUs and the FC

LMPIT-inspired Tests for Detecting a Cyclostationary Signal in Noise with Spatio-Temporal Structure

In spectrum sensing for cognitive radio, the presence of a primary user can be detected by making use of the cyclostationarity property of digital communication signals. For the general scenario of a cyclostationary signal in temporally colored and spatially correlated noise, it has previously been shown that an asymptotic generalized likelihood ratio test (GLRT) and locally most powerful invariant test (LMPIT) exist. In this paper, we derive detectors for the presence of a cyclostationary signal in various scenarios with structured noise. In particular, we consider noise that is temporally white and/or spatially uncorrelated. Detectors that make use of this additional information about the noise process have enhanced performance. We have previously derived GLRTs for these specific scenarios; here, we examine the existence of LMPITs. We show that these exist only for detecting the presence of a cyclostationary signal in spatially uncorrelated noise. For white noise, an LMPIT does not exist. Instead, we propose tests that approximate the LMPIT, and they are shown to perform well in simulations. Finally, if the noise structure is not known in advance, we also present hypothesis tests using our framework

Spectrum sensing for cognitive radio and radar systems

The use of the radio frequency spectrum is increasing at a rapid rate. Reliable and efficient operation in a crowded radio spectrum requires innovative solutions and techniques. Future wireless communication and radar systems should be aware of their surrounding radio environment in order to have the ability to adapt their operation to the effective situation. Spectrum sensing techniques such as detection, waveform recognition, and specific emitter identification are key sources of information for characterizing the surrounding radio environment and extracting valuable information, and consequently adjusting transceiver parameters for facilitating flexible, efficient, and reliable operation. In this thesis, spectrum sensing algorithms for cognitive radios and radar intercept receivers are proposed. Single-user and collaborative cyclostationarity-based detection algorithms are proposed: Multicycle detectors and robust nonparametric spatial sign cyclic correlation based fixed sample size and sequential detectors are proposed. Asymptotic distributions of the test statistics under the null hypothesis are established. A censoring scheme in which only informative test statistics are transmitted to the fusion center is proposed for collaborative detection. The proposed detectors and methods have the following benefits: employing cyclostationarity enables distinction among different systems, collaboration mitigates the effects of shadowing and multipath fading, using multiple strong cyclic frequencies improves the performance, robust detection provides reliable performance in heavy-tailed non-Gaussian noise, sequential detection reduces the average detection time, and censoring improves energy efficiency. In addition, a radar waveform recognition system for classifying common pulse compression waveforms is developed. The proposed supervised classification system classifies an intercepted radar pulse to one of eight different classes based on the pulse compression waveform: linear frequency modulation, Costas frequency codes, binary codes, as well as Frank, P1, P2, P3, and P4 polyphase codes. A robust M-estimation based method for radar emitter identification is proposed as well. A common modulation profile from a group of intercepted pulses is estimated and used for identifying the radar emitter. The M-estimation based approach provides robustness against preprocessing errors and deviations from the assumed noise model

Beyond Massive-MIMO: The Potential of Data-Transmission with Large Intelligent Surfaces

In this paper, we consider the potential of data-transmission in a system with a massive number of radiating and sensing elements, thought of as a contiguous surface of electromagnetically active material. We refer to this as a large intelligent surface (LIS). The "LIS" is a newly proposed concept, which conceptually goes beyond contemporary massive MIMO technology, that arises from our vision of a future where man-made structures are electronically active with integrated electronics and wireless communication making the entire environment "intelligent". We consider capacities of single-antenna autonomous terminals communicating to the LIS where the entire surface is used as a receiving antenna array. Under the condition that the surface-area is sufficiently large, the received signal after a matched-filtering (MF) operation can be closely approximated by a sinc-function-like intersymbol interference (ISI) channel. We analyze the capacity per square meter (m^2) deployed surface, \hat{C}, that is achievable for a fixed transmit power per volume-unit, \hat{P}. Moreover, we also show that the number of independent signal dimensions per m deployed surface is 2/\lambda for one-dimensional terminal-deployment, and \pi/\lambda^2 per m^2 for two and three dimensional terminal-deployments. Lastly, we consider implementations of the LIS in the form of a grid of conventional antenna elements and show that, the sampling lattice that minimizes the surface-area of the LIS and simultaneously obtains one signal space dimension for every spent antenna is the hexagonal lattice. We extensively discuss the design of the state-of-the-art low-complexity channel shortening (CS) demodulator for data-transmission with the LIS.Comment: Submitted to IEEE Trans. on Signal Process., 30 pages, 12 figure

Lens antenna arrays: an efficient framework for sparse-aware large-MIMO communications

The recent increase in the demand for higher data transmission rates in wireless communications has entailed many implementation issues that can only be resolved by going through a full paradigm shift. Making use of the millimetric spectrum bands is a very attractive solution to the shortage of radio resources but, to garner all their potential, new techniques must be developed. Most of them are contained in the Massive Multiple Input Multiple Output (M-MIMO) framework: the idea of using very large antenna arrays for cellular communications. In this thesis, we propose the usage of Lens Antenna Arrays (LAA) to avoid the unbearable power and infrastructure costs posed by traditional M-MIMO architectures. This novel communication system exploits the angular-dependent power focusing capabilities of an electromagnetic lens to discern between waves with different angles of arrival and departure, without explicit signal processing. The work presented in this document motivates the use of LAAs in mmWave communications, studies some of their mathematical properties and proposes their application in noncoherent schemes. Numerical results validate the performance of this novel kind of systems and confirm their strengths in both multi-user and block fading settings. LAAs that use noncoherent methods appear to be very suitable for vehicular communications and densely populated cellular networks.En los últimos tiempos, el incremento en la demanda de mayor velocidad de transmisión de datos en redes de comunicación inalámbricas ha conllevado varios problemas de implementación que solo se podrán resolver a través de un cambio total de paradigma. Utilizar bandas milimétricas del espectro es una solución muy atractiva a la escasez de recursos de radio pero, para poder extraer todo su potencial, es necesario desarrollar nuevas técnicas. La mayor parte de éstas pasa por la infraestructura Massive Multiple Input Multiple Output (M-MIMO): la idea de usar matrices de antenas muy grandes para comunicaciones celulares. En esta tesis, proponemos el uso de matrices de antenas con lente, o Lens Antenna Arrays (LAA), para evitar los inasumibles costes energéticos y de instalación propios de las arquitecturas M-MIMO tradicionales. Este novedoso sistema de comunicaciones explota las capacidades de concentración de energía con dependencia angular de las lentes electromagnéticas para distinguir entre ondas con distintas direcciones de llegada y de salida, sin procesado de la señal explícito. El trabajo presentado en este documento motiva el uso de los LAAs en comunicaciones en bandas milimétricas (mmWave), estudia varias propiedades matemáticas y propone su aplicación en esquemas no coherentes. Resultados numéricos validan su ejecución y confirman sus fortalezas en entornos multiusuario y con desvanecimiento en bloque. Los LAAs que utilizan métodos no coherentes parecen ser idóneos para comunicaciones vehiculares y para redes celulares altamente pobladas.En els darrers temps, l'increment en la demanda de major velocitat de transmissió de dades en xarxes de comunicació inalàmbriques ha comportat diversos problemes d'implementació que tan sols es podran resoldre a través d'un canvi total de paradigma. Utilitzar les bandes mil·limètriques de l'espectre és una solució molt atractiva a l'escassetat de recursos de ràdio però, per tal d'extreure'n tot el seu potencial, és necessari desenvolupar noves tècniques. La majoria d'aquestes passa per la infraestructura Massive Multiple Input Multiple Output (M-MIMO): la idea d'utilitzar matrius d'antenes molt grans per a comunicacions cel·lulars. En aquesta tesi, proposem l'ús de matrius d'antenes amb lent, o Lens Antenna Arrays (LAA), per tal d'evitar els inassumibles costos energètics i d'instal·lació propis d'arquitectures M-MIMO tradicionals. Aquest innovador sistema de comunicacions explota les capacitats de concentració d'energia amb dependència angular de les lents electromagnètiques per tal de distingir entre ones amb diferents direccions d'arribada i de sortida, sense processament de senyal explícit. El treball presentat en aquest document motiva l'ús dels LAAs per comunicacions en bandes mil·limètriques (mmWave), n'estudia diverses propietats matemàtiques i proposa la seva aplicació en esquemes no coherents. Resultats numèrics en validen l'execució i confirmen les seves fortaleses en entorns multi-usuari i amb esvaïment en bloc. Els LAAs que utilitzen mètodes no coherents semblen ser idonis per a comunicacions vehiculars i per a xarxes cel·lulars altament poblades

Performance Analysis and Mitigation Techniques for I/Q-Corrupted OFDM Systems

Orthogonal Frequency Division Multiplexing (OFDM) has become a widely adopted modulation technique in modern communications systems due to its multipath resilience and low implementation complexity. The direct conversion architecture is a popular candidate for low-cost, low-power, fully integrated transceiver designs. One of the inevitable problems associated with analog signal processing in direct conversion involves the mismatches in the gain and phases of In-phase (I) and Quadrature-phase (Q) branches. Ideally, the I and Q branches of the quadrature mixer will have perfectly matched gains and are orthogonal in phase. Due to imperfect implementation of the electronics, so called I/Q imbalance emerges and creates interference between subcarriers which are symmetrically apart from the central subcarrier. With practical imbalance levels, basic transceivers fail to maintain the sufficient image rejection, which in turn can cause interference with the desired transmission. Such an I/Q distortion degrades the systems performance if left uncompensated. Moreover, the coexistence of I/Q imbalance and other analog RF imperfections with digital baseband and higher layer functionalities such as multiantenna transmission and radio resource management, reduce the probability of successful transmission. Therefore, mitigation of I/Q imbalance is an essential substance in designing and implementing modern communications systems, while meeting required performance targets and quality of service. This thesis considers techniques to compensate and mitigate I/Q imbalance, when combined with channel estimation, multiantenna transmission, transmission power control, adaptive modulation and multiuser scheduling. The awareness of the quantitative relationship between transceiver parameters and system parameters is crucial in designing and dimensioning of modern communications systems. For this purpose, analytical models to evaluate the performance of an I/Q distorted system are considered

Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications

Antenna array technology enables the directional transmission and reception of wireless signals for communication, localization, and sensing purposes. The signal processing algorithms that underpin it began to be developed several decades ago [1], but it was with the deployment of 5G wireless mobile networks that the technology became mainstream [2]. The number of antenna elements in the arrays of 5G base stations (BSs) and user devices can be measured on the order of hundreds and tens, respectively. As networks shift toward using higher-frequency bands, more antennas fit into a given aperture. For communication purposes, the arrays are harnessed to form beams in desired directions to improve the signal-to-noise ratio (SNR) and multiplex data signals in the spatial domain (to one or multiple devices) and to suppress interference by spatial filtering [2]. For localization purposes, these arrays are employed to maintain the SNR when operating across wider bandwidths, for angle-of-arrival estimation, and to separate multiple sources and scatterers [3]. The practical use of these features requires that each antenna array is equipped with well-designed signal processing algorithms

SPECTRUM SENSING AND COOPERATION IN COGNITIVE-OFDM BASED WIRELESS COMMUNICATIONS NETWORKS

The world has witnessed the development of many wireless systems and applications. In addition to the large number of existing devices, such development of new and advanced wireless systems increases rapidly the demand for more radio spectrum. The radio spectrum is a limited natural resource; however, it has been observed that it is not efficiently utilized. Consequently, different dynamic spectrum access techniques have been proposed as solutions for such an inefficient use of the spectrum. Cognitive Radio (CR) is a promising intelligent technology that can identify the unoccupied portions of spectrum and opportunistically uses those portions with satisfyingly high capacity and low interference to the primary users (i.e., licensed users). The CR can be distinguished from the classical radio systems mainly by its awareness about its surrounding radio frequency environment. The spectrum sensing task is the main key for such awareness. Due to many advantages, Orthogonal Frequency Division Multiplexing system (OFDM) has been proposed as a potential candidate for the CR‟s physical layer. Additionally, the Fast Fourier Transform (FFT) in an OFDM receiver supports the performance of a wide band spectrum analysis. Multitaper spectrum estimation method (MTM) is a non-coherent promising spectrum sensing technique. It tolerates problems related to bad biasing and large variance of power estimates. This thesis focuses, generally, on the local, multi antenna based, and global cooperative spectrum sensing techniques at physical layer in OFDM-based CR systems. It starts with an investigation on the performance of using MTM and MTM with singular value decomposition in CR networks using simulation. The Optimal MTM parameters are then found. The optimal MTM based detector theoretical formulae are derived. Different optimal and suboptimal multi antenna based spectrum sensing techniques are proposed to improve the local spectrum sensing performance. Finally, a new concept of cooperative spectrum sensing is introduced, and new strategies are proposed to optimize the hard cooperative spectrum sensing in CR networks. The MTM performance is controlled by the half time bandwidth product and number of tapers. In this thesis, such parameters have been optimized using Monte Carlo simulation. The binary hypothesis test, here, is developed to ensure that the effect of choosing optimum MTM parameters is based upon performance evaluation. The results show how these optimal parameters give the highest performance with minimum complexity when MTM is used locally at CR. The optimal MTM based detector has been derived using Neyman-Pearson criterion. That includes probabilities of detection, false alarm and misses detection approximate derivations in different wireless environments. The threshold and number of sensed samples controlling is based on this theoretical work. In order to improve the local spectrum sensing performance at each CR, in the CR network, multi antenna spectrum sensing techniques are proposed using MTM and MTM with singular value decomposition in this thesis. The statistical theoretical formulae of the proposed techniques are derived including the different probabilities. ii The proposed techniques include optimal, that requires prior information about the primary user signal, and two suboptimal multi antenna spectrum sensing techniques having similar performances with different computation complexity; these do not need prior information about the primary user signalling. The work here includes derivations for the periodogram multi antenna case. Finally, in hard cooperative spectrum sensing, the cooperation optimization is necessary to improve the overall performance, and/or minimize the number of data to be sent to the main CR-base station. In this thesis, a new optimization method based on optimizing the number of locally sensed samples at each CR is proposed with two different strategies. Furthermore, the different factors that affect the hard cooperative spectrum sensing optimization are investigated and analysed and a new cooperation scheme in spectrum sensing, the master node, is proposed.Ministry of Interior-Kingdom of Saudi Arabi

Effect and compensation of colored timing jitter in pulsed UWB system

Master'sMASTER OF ENGINEERIN