Spectrum Sensing Techniqes in Cognitive Radio: Cyclostationary Method

Cognitive Radios promise to be a major shift in wireless communications based on developing a novel approach which attempt to reduce spectrum scarcity that growing up in the past and waited to increase in the future. Since formulating stages for increasing interest in wireless application proves to be extremely challenging, it is growing rapidly. Initially this growth leads to huge demand for the radio spectrum. The novelty of this approach needs to optimize the spectrum utilization and find the efficient way for sharing the radio frequencies through spectrum sensing process. Spectrum sensing is one of the most significant tasks that allow cognitive radio functionality to implement and one of the most challenging tasks. A main challenge in sensing process arises from the fact that, detecting signals with a very low SNR in back ground of noise or severely masked by interference in specific time based on high reliability. This thesis describes the fundamental cognitive radio system aspect based on design and implementation by connecting between the theoretical and practical issue. Efficient method for sensing and detecting are studied and discussed through two fast methods of computing the spectral correlation density function, the FFT Accumulation Method and the Strip Spectral Correlation Algorithm. Several simulations have been performed to show the ability and performance of studied algorithms.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Enhanced Spectrum Sensing Techniques for Cognitive Radio Systems

Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources. Considering the limited radio spectrum, supporting the demand for higher capacity and higher data rates is a challenging task that requires innovative technologies capable of providing new ways of exploiting the available radio spectrum. Cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems, has received increasing attention and is considered a promising solution to the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Spectrum sensing, which enables CRs to identify spectral holes, is a critical component in CR technology. Furthermore, improving the efficiency of the radio spectrum use through spectrum sensing and dynamic spectrum access (DSA) is one of the emerging trends. In this thesis, we focus on enhanced spectrum sensing techniques that provide performance gains with reduced computational complexity for realistic waveforms considering radio frequency (RF) impairments, such as noise uncertainty and power amplifier (PA) non-linearities. The first area of study is efficient energy detection (ED) methods for spectrum sensing under non-flat spectral characteristics, which deals with relatively simple methods for improving the detection performance. In realistic communication scenarios, the spectrum of the primary user (PU) is non-flat due to non-ideal frequency responses of the devices and frequency selective channel conditions. Weighting process with fast Fourier transform (FFT) and analysis filter bank (AFB) based multi-band sensing techniques are proposed for overcoming the challenge of non-flat characteristics. Furthermore, a sliding window based spectrum sensing approach is addressed to detect a re-appearing PU that is absent in one time and present in other time. Finally, the area under the receiver operating characteristics curve (AUC) is considered as a single-parameter performance metric and is derived for all the considered scenarios. The second area of study is reduced complexity energy and eigenvalue based spectrum sensing techniques utilizing frequency selectivity. More specifically, novel spectrum sensing techniques, which have relatively low computational complexity and are capable of providing accurate and robust performance in low signal-to-noise ratio (SNR) with noise uncertainty, as well as in the presence of frequency selectivity, are proposed. Closed-form expressions are derived for the corresponding probability of false alarm and probability of detection under frequency selectivity due the primary signal spectrum and/or the transmission channel. The offered results indicate that the proposed methods provide quite significant saving in complexity, e.g., 78% reduction in the studied example case, whereas their detection performance is improved both in the low SNR and under noise uncertainty. Finally, a new combined spectrum sensing and resource allocation approach for multicarrier radio systems is proposed. The main contribution of this study is the evaluation of the CR performance when using wideband spectrum sensing methods in combination with water-filling and power interference (PI) based resource allocation algorithms in realistic CR scenarios. Different waveforms, such as cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM), enhanced orthogonal frequency division multiplexing (E-OFDM) and filter bank based multicarrier (FBMC), are considered with PA nonlinearity type RF impairments to see the effects of spectral leakage on the spectrum sensing and resource allocation performance. It is shown that AFB based spectrum sensing techniques and FBMC waveforms with excellent spectral containment properties have clearly better performance compared to the traditional FFT based spectrum sensing techniques with the CP-OFDM. Overall, the investigations in this thesis provide novel spectrum sensing techniques for overcoming the challenge of noise uncertainty with reduced computational complexity. The proposed methods are evaluated under realistic signal models

Evaluation of Overlay/underlay Waveform via SD-SMSE Framework for Enhancing Spectrum Efficiency

Recent studies have suggested that spectrum congestion is mainly due to the inefficient use of spectrum rather than its unavailability. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) are two terminologies which are used in the context of improved spectrum efficiency and usage. The DSA concept has been around for quite some time while the advent of CR has created a paradigm shift in wireless communications and instigated a change in FCC policy towards spectrum regulations. DSA can be broadly categorized as using a 1) Dynamic Exclusive Use Model, 2) Spectrum Commons or Open sharing model or 3) Hierarchical Access model. The hierarchical access model envisions primary licensed bands, to be opened up for secondary users, while inducing a minimum acceptable interference to primary users. Spectrum overlay and spectrum underlay technologies fall within the hierarchical model, and allow primary and secondary users to coexist while improving spectrum efficiency. Spectrum overlay in conjunction with the present CR model considers only the unused (white) spectral regions while in spectrum underlay the underused (gray) spectral regions are utilized. The underlay approach is similar to ultra wide band (UWB) and spread spectrum (SS) techniques utilize much wider spectrum and operate below the noise floor of primary users. Software defined radio (SDR) is considered a key CR enabling technology. Spectrally modulated, Spectrally encoded (SMSE) multi-carrier signals such as Orthogonal Frequency Domain Multiplexing (OFDM) and Multi-carrier Code Division Multiple Access (MCCDMA) are hailed as candidate CR waveforms. The SMSE structure supports and is well-suited for SDR based CR applications. This work began by developing a general soft decision (SD) CR framework, based on a previously developed SMSE framework that combines benefits of both the overlay and underlay techniques to improve spectrum efficiency and maximizing the channel capacity. The resultant SD-SMSE framework provides a user with considerable flexibility to choose overlay, underlay or hybrid overlay/underlay waveform depending on the scenario, situation or need. Overlay/Underlay SD-SMSE framework flexibility is demonstrated by applying it to a family of SMSE modulated signals such as OFDM, MCCDMA, Carrier Interferometry (CI) MCCDMA and Transform Domain Communication System (TDCS). Based on simulation results, a performance analysis of Overlay, Underlay and hybrid Overlay/Underlay waveforms are presented. Finally, the benefits of combining overlay/underlay techniques to improve spectrum efficiency and maximize channel capacity are addressed

Hybrid Spectrum Sensing Method for Cognitive Radio

With exponential rise in the internet applications and wireless communications, higher and efficient data transfer rates are required. Hence proper and effective spectrum is the need of the hour, As spectrum demand increases there are limited number of bands available to send and receive the data. Optimizing the use of these bands efficiently is one of the tedious tasks. Various techniques are used to send the data at same time, but for that we have to know which bands are free before sending the data. For this purpose various spectrum sensing approaches came with variety of solutions. In this paper the sensing problem is tackled with the use of hybrid spectrum sensing method, This new networking paradox uses the Centralized concept of spectrum sensing and creates one of the most trusted spectrums sensing mechanism. This proposed technique is simulated using MATLAB software.This paper also provides comparative study of various spectrum sensing methodologie

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

High Performance Local Oscillator Design for Next Generation Wireless Communication

Local Oscillator (LO) is an essential building block in modern wireless radios. In modern wireless radios, LO often serves as a reference of the carrier signal to modulate or demod- ulate the outgoing or incoming data. The LO signal should be a clean and stable source, such that the frequency or timing information of the carrier reference can be well-defined. However, as radio architecture evolves, the importance of LO path design has become much more important than before. Of late, many radio architecture innovations have exploited sophisticated LO generation schemes to meet the ever-increasing demands of wireless radio performances. The focus of this thesis is to address challenges in the LO path design for next-generation high performance wireless radios. These challenges include (1) Congested spectrum at low radio frequency (RF) below 5GHz (2) Continuing miniaturization of integrated wireless radio, and (3) Fiber-fast (>10Gb/s) mm-wave wireless communication. The thesis begins with a brief introduction of the aforementioned challenges followed by a discussion of the opportunities projected to overcome these challenges. To address the challenge of congested spectrum at frequency below 5GHz, novel ra- dio architectures such as cognitive radio, software-defined radio, and full-duplex radio have drawn significant research interest. Cognitive radio is a radio architecture that opportunisti- cally utilize the unused spectrum in an environment to maximize spectrum usage efficiency. Energy-efficient spectrum sensing is the key to implementing cognitive radio. To enable energy-efficient spectrum sensing, a fast-hopping frequency synthesizer is an essential build- ing block to swiftly sweep the carrier frequency of the radio across the available spectrum. Chapter 2 of this thesis further highlights the challenges and trade-offs of the current LO gen- eration scheme for possible use in sweeping LO-based spectrum analysis. It follows by intro- duction of the proposed fast-hopping LO architecture, its implementation and measurement results of the validated prototype. Chapter 3 proposes an embedded phase-shifting LO-path design for wideband RF self-interference cancellation for full-duplex radio. It demonstrates a synergistic design between the LO path and signal to perform self-interference cancellation. To address the challenge of continuing miniaturization of integrated wireless radio, ring oscillator-based frequency synthesizer is an attractive candidate due to its compactness. Chapter 4 discussed the difficulty associated with implementing a Phase-Locked Loop (PLL) with ultra-small form-factor. It further proposes the concept sub-sampling PLL with time- based loop filter to address these challenges. A 65nm CMOS prototype and its measurement result are presented for validation of the concept. In shifting from RF to mm-wave frequencies, the performance of wireless communication links is boosted by significant bandwidth and data-rate expansion. However, the demand for data-rate improvement is out-pacing the innovation of radio architectures. A >10Gb/s mm-wave wireless communication at 60GHz is required by emerging applications such as virtual-reality (VR) headsets, inter-rack data transmission at data center, and Ultra-High- Definition (UHD) TV home entertainment systems. Channel-bonding is considered to be a promising technique for achieving >10Gb/s wireless communication at 60GHz. Chapter 5 discusses the fundamental radio implementation challenges associated with channel-bonding for 60GHz wireless communication and the pros and cons of prior arts that attempted to address these challenges. It is followed by a discussion of the proposed 60GHz channel- bonding receiver, which utilizes only a single PLL and enables both contiguous and non- contiguous channel-bonding schemes. Finally, Chapter 6 presents the conclusion of this thesis