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

A Multitaper-Random Demodulator Model for Narrowband Compressive Spectral Estimation

The random demodulator (RD) is a compressive sensing (CS) system for acquiring and recovering bandlimited sparse signals, which are approximated by multi-tones. Signal recovery employs the discrete Fourier transform based periodogram, though due to bias and variance constraints, it is an inconsistent spectral estimator. This paper presents a Multitaper RD (MT-RD) architecture for compressive spectrum estimation, which exploits the inherent advantage of the MT spectral estimation method from the spectral leakage perspective. Experimental results for sparse, narrowband signals corroborate that the MT-RD model enhances sparsity so affording superior CS performance compared with the original RD system in terms of both lower power spectrum leakage and improved input noise robustness

Adaptive Coded Modulation Classification and Spectrum Sensing for Cognitive Radio Systems. Adaptive Coded Modulation Techniques for Cognitive Radio Using Kalman Filter and Interacting Multiple Model Methods

The current and future trends of modern wireless communication systems place heavy demands on fast data transmissions in order to satisfy end users’ requirements anytime, anywhere. Such demands are obvious in recent applications such as smart phones, long term evolution (LTE), 4 & 5 Generations (4G & 5G), and worldwide interoperability for microwave access (WiMAX) platforms, where robust coding and modulations are essential especially in streaming on-line video material, social media and gaming. This eventually resulted in extreme exhaustion imposed on the frequency spectrum as a rare natural resource due to stagnation in current spectrum management policies. Since its advent in the late 1990s, cognitive radio (CR) has been conceived as an enabling technology aiming at the efficient utilisation of frequency spectrum that can lead to potential direct spectrum access (DSA) management. This is mainly attributed to its internal capabilities inherited from the concept of software defined radio (SDR) to sniff its surroundings, learn and adapt its operational parameters accordingly. CR systems (CRs) may commonly comprise one or all of the following core engines that characterise their architectures; namely, adaptive coded modulation (ACM), automatic modulation classification (AMC) and spectrum sensing (SS). Motivated by the above challenges, this programme of research is primarily aimed at the design and development of new paradigms to help improve the adaptability of CRs and thereby achieve the desirable signal processing tasks at the physical layer of the above core engines. Approximate modelling of Rayleigh and finite state Markov channels (FSMC) with a new concept borrowed from econometric studies have been approached. Then insightful channel estimation by using Kalman filter (KF) augmented with interacting multiple model (IMM) has been examined for the purpose of robust adaptability, which is applied for the first time in wireless communication systems. Such new IMM-KF combination has been facilitated in the feedback channel between wireless transmitter and receiver to adjust the transmitted power, by using a water-filling (WF) technique, and constellation pattern and rate in the ACM algorithm. The AMC has also benefited from such IMM-KF integration to boost the performance against conventional parametric estimation methods such as maximum likelihood estimate (MLE) for channel interrogation and the estimated parameters of both inserted into the ML classification algorithm. Expectation-maximisation (EM) has been applied to examine unknown transmitted modulation sequences and channel parameters in tandem. Finally, the non-parametric multitaper method (MTM) has been thoroughly examined for spectrum estimation (SE) and SS, by relying on Neyman-Pearson (NP) detection principle for hypothesis test, to allow licensed primary users (PUs) to coexist with opportunistic unlicensed secondary users (SUs) in the same frequency bands of interest without harmful effects. The performance of the above newly suggested paradigms have been simulated and assessed under various transmission settings and revealed substantial improvements

A Cognitive Radio Compressive Sensing Framework

With the proliferation of wireless devices and services, allied with further significant predicted growth, there is an ever increasing demand for higher transmission rates. This is especially challenging given the limited availability of radio spectrum, and is further exacerbated by a rigid licensing regulatory regime. Spectrum however, is largely underutilized and this has prompted regulators to promote the concept of opportunistic spectrum access. This allows unlicensed secondary users to use bands which are licensed to primary users, but are currently unoccupied, so leading to more efficient spectrum utilization. A potentially attractive solution to this spectrum underutilisation problem is cognitive radio (CR) technology, which enables the identification and usage of vacant bands by continuously sensing the radio environment, though CR enforces stringent timing requirements and high sampling rates. Compressive sensing (CS) has emerged as a novel sampling paradigm, which provides the theoretical basis to resolve some of these issues, especially for signals exhibiting sparsity in some domain. For CR-related signals however, existing CS architectures such as the random demodulator and compressive multiplexer have limitations in regard to the signal types used, spectrum estimation methods applied, spectral band classification and a dependence on Fourier domain based sparsity. This thesis presents a new generic CS framework which addresses these issues by specifically embracing three original scientific contributions: i) seamless embedding of the concept of precolouring into existing CS architectures to enhance signal sparsity for CR-related digital modulation schemes; ii) integration of the multitaper spectral estimator to improve sparsity in CR narrowband modulation schemes; and iii) exploiting sparsity in an alternative, non-Fourier (Walsh-Hadamard) domain to expand the applicable CR-related modulation schemes. Critical analysis reveals the new CS framework provides a consistently superior and robust solution for the recovery of an extensive set of currently employed CR-type signals encountered in wireless communication standards. Significantly, the generic and portable nature of the framework affords the opportunity for further extensions into other CS architectures and sparsity domains

Removing non-stationary noise in spectrum sensing using matrix factorization

Spectrum sensing is key to many applications like dynamicspectrum access (DSA) systems or telecom regulators who need to measure utilization of frequency bands. The International Telecommunication Union (ITU) recommends a 10 dB threshold above the noise to decide whether a channel is occupied or not. However, radio frequency (RF) receiver front-ends are non-ideal. This means that the obtained data is distorted with noise and imperfections from the analog front-end. As part of the front-end the automatic gain control (AGC) circuitry mainly affects the sensing performance as strong adjacent signals lift the noise level. To enhance the performance of spectrum sensing significantly we focus in this article on techniques to remove the noise caused by the AGC from the sensing data. In order to do this we have applied matrix factorization techniques, i.e., SVD (singular value decomposition) and NMF (non-negative matrix factorization), which enables signal space analysis. In addition, we use live measurement results to verify the performance and to remove the effects of the AGC from the sensing data using above mentioned techniques, i.e., applied on block-wise available spectrum data. In this article it is shown that the occupancy in the industrial, scientific and medical (ISM) band, obtained by using energy detection (ITU recommended threshold), can be an overestimation of spectrum usage by 60%

Adaptive and autonomous protocol for spectrum identification and coordination in ad hoc cognitive radio network

The decentralised structure of wireless Ad hoc networks makes them most appropriate for quick and easy deployment in military and emergency situations. Consequently, in this thesis, special interest is given to this form of network. Cognitive Radio (CR) is defined as a radio, capable of identifying its spectral environment and able to optimally adjust its transmission parameters to achieve interference free communication channel. In a CR system, Dynamic Spectrum Access (DSA) is made feasible. CR has been proposed as a candidate solution to the challenge of spectrum scarcity. CR works to solve this challenge by providing DSA to unlicensed (secondary) users. The introduction of this new and efficient spectrum management technique, the DSA, has however, opened up some challenges in this wireless Ad hoc Network of interest; the Cognitive Radio Ad Hoc Network (CRAHN). These challenges, which form the specific focus of this thesis are as follows: First, the poor performance of the existing spectrum sensing techniques in low Signal to Noise Ratio (SNR) conditions. Secondly the lack of a central coordination entity for spectrum allocation and information exchange in the CRAHN. Lastly, the existing Medium Access Control (MAC) Protocol such as the 802.11 was designed for both homogeneous spectrum usage and static spectrum allocation technique. Consequently, this thesis addresses these challenges by first developing an algorithm comprising of the Wavelet-based Scale Space Filtering (WSSF) algorithm and the Otsu's multi-threshold algorithm to form an Adaptive and Autonomous WaveletBased Scale Space Filter (AWSSF) for Primary User (PU) sensing in CR. These combined algorithms produced an enhanced algorithm that improves detection in low SNR conditions when compared to the performance of EDs and other spectrum sensing techniques in the literature. Therefore, the AWSSF met the performance requirement of the IEEE 802.22 standard as compared to other approaches and thus considered viable for application in CR. Next, a new approach for the selection of control channel in CRAHN environment using the Ant Colony System (ACS) was proposed. The algorithm reduces the complex objective of selecting control channel from an overtly large spectrum space,to a path finding problem in a graph. We use pheromone trails, proportional to channel reward, which are computed based on received signal strength and channel availability, to guide the construction of selection scheme. Simulation results revealed ACS as a feasible solution for optimal dynamic control channel selection. Finally, a new channel hopping algorithm for the selection of a control channel in CRAHN was presented. This adopted the use of the bio-mimicry concept to develop a swarm intelligence based mechanism. This mechanism guides nodes to select a common control channel within a bounded time for the purpose of establishing communication. Closed form expressions for the upper bound of the time to rendezvous (TTR) and Expected TTR (ETTR) on a common control channel were derived for various network scenarios. The algorithm further provides improved performance in comparison to the Jump-Stay and Enhanced Jump-Stay Rendezvous Algorithms. We also provided simulation results to validate our claim of improved TTR. Based on the results obtained, it was concluded that the proposed system contributes positively to the ongoing research in CRAHN

Journal of Telecommunications and Information Technology

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A Cognitive TV White Space Access Framework

Given the current boom in applications and services for mobile devices, data traffic is rapidly expanding, with the consequence that increasing spectrum capacity is being mandated. Following the switchover from analogue to digital platforms, Television White Space (TVWS) affords a fertile opportunity to supplement existing licensed spectrum to ease this scarcity. There are however, a number of obstacles to wide-scale TVWS adoption, including the accurate detection of primary users (PU), the hidden node problem and bandwidth availability for unlicensed secondary users (SU). Regulatory and industry bodies have sought to address some of these issues using a static database for spectrum access decisions, though this involves manual maintenance and accuracy can be compromised due to a lack of real-time information. While the new IEEE802.11af wireless local area network (WLAN) standard attempts to resolve some SU access issues, there remain many challenges, such as the critical asymmetry between mobile and base station power resources. This thesis presents a new cognitive TVWS access framework encompassing a real-time sensing paradigm for TVWS deployment that uses a spectrum-efficient scheme to uphold quality-of-service (QoS) for both PU and SU. A novel dynamic spectrum allocation (DSA) model has been formulated allied with a resilient interference management system which exploits the unique way digital terrestrial TV channels are allocated in different geographical areas. A margin strategy has been framed to support efficient TVWS channel reuse, with an exclusion zone established to overcome the hidden node problem, while an innovative routing algorithm using cross-layer information, both extends coverage capacity and maximises QoS provision by ensuring a more balanced resource allocation. Critical evaluation of the new access framework confirms that significant QoS improvements for SU are achieved compared to existing TVWS techniques. It importantly embodies a generic, practical, resource-efficient solution for TVWS deployment, which is compliant with current PU regulatory requirements

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters