Survey on spectrum sensing techniques in cognitive radio networks

Empowered by the cognitive radio technology, and motivated by the sporadic channel utilization, both spatially and temporally, dynamic spectrum access networks (also referred to as cognitive radio networks and next generation wireless networks) have emerged as a solution to improve spectrum utilization and provide more flexibility to wireless communication. A cognitive radio network is composed of wireless users, referred to as secondary users, which are allowed to use a given licensed spectrum band as long as there are no primary, licensed, users occupying this band in their vicinity. This restricted spectrum access strategy leads to heterogeneity in channel availability among secondary users. Heterogeneity in channel availability forms a significant source of performance degradation for cognitive radio networks, and poses a great challenge on protocol design. In this dissertation, we propose spectrum allocation algorithms that take this heterogeneity property and its effect on the network performance into consideration. The spectrum allocation solutions proposed in this dissertation address three major objectives in cognitive radio mesh networks. The first objective is maximizing the network coverage, in terms of the total number of served clients, and at the same time simplifying the communication coordination function. To address this objective, we proposed a received based channel allocation strategy that alleviates the need for a common control channel, thus simplifying the coordination function, and at the same time maximizes the number of clients served with link reliability guarantees. We show the superiority of the proposed allocation strategy over other existing strategies. The second objective is improving the multicast throughput to compensate for the performance degradation caused by the heterogeneity in channel availability. We proposed a

Energy harvesting (EH), which refers to replenishing energy from the environment, is demonstrated to be a promising approach in reducing the operational expenses (OPEX) and increasing the network lifetime of emerging wireless communication technologies by eliminating the need for frequent battery replacing or recharging of wireless devices. Among various ambient energy sources, the focus of this dissertation is on wireless power transfer (WPT) considering the unique characteristic of radio frequency (RF) signals; that is, they inherently carry both information and energy. A particularly interesting scenario arises when sources support simultaneous wireless information and power transfer (SWIPT) to provide a remote, controllable, and on-demand energy source. In this context, one of the promising deployment approaches is SWIPT-enabled cognitive radio networks (CRNs), which offer significant gains in terms of spectral and energy efficiencies. One of the practical scenarios of RF-powered CRN is deploying a number of distributed cognitive sensor nodes, equipped with RF EH modules, to sense a specific area and send the sensed data to an access point while coexisting with a primary licensed network. However, exploiting the full potentials of SWIPT-enabled CRNs is subject to carefully aligning the requirements of the EH unlicensed secondary receivers (SRs) with those of the legitimate primary receivers (PRs). In light of this, the first contribution of this thesis focuses on investigating the problem of beamforming for the downlink of multi-user multiple-input single-output (MU-MISO) CRNs. With the objective of minimising the transmission power of the secondary base station (SBS), optimal and suboptimal solutions for the formulated optimisation problem are provided by jointly optimising the transmit beamforming vector at the SBS and adjusting the parameters of the energy harvesters at the SRs. It is shown that the obtained solutions are efficient in meeting the EH and quality-of-service (QoS) requirements of the SRs and the levels of interference accepted by the PRs. Apart from SWIPT-enabled CRNs, relay-assisted SWIPT networks are envisioned to be a promising framework offering extended coverage, diversity gains, and enhanced energy efficiency. In this case, the relay network itself can benefit from the relayed transmissions in terms of saving energy, and the harvested energy can be used to charge relay nodes and extend their lifetime as compensation for their role of data forwarding. Nonetheless, a concrete performance analysis on the impact of the involved system parameters such as, the energy conversion efficiency and the location of the EH relay terminal, on the trade-off between the achievable information transfer efficiency and the harvested energy level is crucial for the successful implementation of SWIPT in this context. This inspired the research work in the next two contributions with the main focus on developing novel comprehensive analytical frameworks for the investigation and evaluation of SWIPT relaying systems. Specifically, the second contribution is dedicated to examining the application of noncoherent modulation, which is recognised as an energy efficient modulation scheme for SWIPT, due to its ability to eliminate the need of instantaneous channel state information (CSI) estimation/tracking. Through adopting a moments-based approach, novel expressions are derived for the outage probability, achievable throughput, and average symbol error rate (ASER) of dual-hop SWIPT relaying systems. Furthermore, new asymptotic analytical results are derived for the high SNR regime and are then utilised to analytically quantify the achievable diversity order. The proposed mathematical tools are demonstrated to be an accurate and efficient means by which one can conduct a thorough analysis on the system performance without the burden of Monte Carlo simulations. Finally, the third contribution focuses on SWIPT relaying systems operating in the presence of impulsive non-Gaussian noise, which is typical in several practical scenarios. Several studies show sufficient evidences that impulse man-made noise is encountered in various metropolitan, indoor, and underwater wireless applications. Examples of these sources include automotive ignition, electronic devices, household appliances, medical equipment, and industrial equipment. To characterise the behavior of the system performance under this type of noise, an efficient analytical framework is developed where novel closed-form xpressions for the pairwise error probability (PEP) are derived for two relaying schemes, namely, blind relaying and CSI-assisted relaying, employed under two assumptions imposed on the deployed EH process; namely, instantaneous EH (IEH) and average EH (AEH). Apart from being accurate, the derived expressions are shown to be efficient in quantifying the diversity order of the system and providing a comprehensive study on the impact of the severity of impulsive noise on the behavior of the system.

Analysis of mobility impact on interference in cognitive radio networks

In the recent years Cognitive Radio (CR) technology imposed itself like a very good solution to the increasing spectrum utilization. This technology proposes the development of a new radio type - a cognitive radio - endowed with intelligence that shall sense, share, and use the spectrum opportunities (SOP) of the preexisting wireless networks, that is the channels that are not used by the licensed users. A new routing algorithm for CR networks (CRN): IPSAG - IP Spectrum Aware Geographic based Routing Protocol is presented in the paper. As suggested by the name, the IP hop-by-hop, the geographic, and the spectrum aware routing concepts were used together in the protocol's design. The dynamism and flexibility, characteristic to both CR and IP networks, made us compare the CR concept with the IP concept (a wireless versus wired flexible environment comparison); thus we assumed the IP routing approach for CRN. The proposed strategy is based on hop-by-hop routing, local decisions being taken by nodes according to both local information (CR node's neighborhood) and global information (the entire topology of CRN), channels availability, and destination location.

Currently, the wireless communication technology has noticed explosive expansion in its demand and it is increasing rapidly whereasdue to their wide range of applications and uses, Wireless Sensor Networks (WSNs) have attracted the attentions of the academic community in various offline and online applications. These networks are deployed in the unattended and harsh environment due to which maintaining the network lifetime becomes a challenging task. The energy consumption in these networks is a challenging task which needs to be addressed for increased network lifetime. Moreover, the conventional wireless communication standards are utilizing the radio spectrum. Currently, the spectrum is very limited and excessive exploitation creating overburdening on the network. Thus efficient spectrum allocation is also becoming a tedious task. Nowadays, Cognitive Radio (CR) has appeared to be a viable way out to efficiently utilize the available spectrum. According to this CR concept, cognitive radio technology helps to opportunistically and dynamically access the spectrum bands which improve the utilization of radio spectrum resources.Several techniques have been presented to deal with the issue but these techniques suffer from various issues such as uncertain energy harvesting and resource (channel) allocation which becomes a critical issue for these networks. To overcome these problems, the workproposes a novel approachcalled ?Fuzzy?_Q-EACWSNR (an energy aware cognitive wireless sensor network routing) scheme which minimizes the energy consumption by using reinforcement based Q-learning scheme for packet forwarding in cognitive enabled wireless sensor nodes.This novel scheme considers the optimal cluster formulation, cluster head selection, spectrum sensing and allocation.The experimental study reported thenoteworthy improvement in the communication performance by evaluating and comparing the performance with EACRP, ESAC andOptimum distance based clustering in terms of network throughput, average packet delay, and energy consumption.

The fifth Generation (5G) of wireless communication standards and Cognitive radio (CR) are believed to be the solution for present day data intensive applications. The 5G wireless networks are expected to provide higher data transfer rates, ubiquitous connectivity, low end-to-end latency, much higher system capacity and improved energy efficiency. Cognitive radio network (CRN) offers dynamic spectrum sharing to achieve higher spectrum efficiencies as required in 5G architecture. Present report encompasses concise information about mobile cellular system, 5G requirements, 5G enabling technologies and cognitive radio paradigm for 5G heterogeneous multi-tier networks.

ABSTRACTThe rapid expansion of the Internet of Things (IoT) and the increasing demand for wireless communication have intensified the need for efficient spectrum management in cognitive radio networks (CRNs). Traditional approaches to spectrum sensing and allocation often operate in isolation or rely on static methods, which fail to address the dynamic and evolving nature of modern wireless environments. As IoT devices proliferate and spectrum resources become increasingly congested, there is a pressing need for more adaptive and efficient spectrum management solutions. Our approach addresses this need by offering an adaptive framework that responds to the changing spectrum landscape, thereby optimizing spectrum usage and reducing interference. This research suggests improved NN joint spectrum sensing for CR‐IoTNet (INJSS‐CR). This approach leverages cognitive radio (CR) technology to enhance spectrum utilization and mitigate the impact of spectrum shortages. CR technology enables secondary users (SUs) to detect and access unused spectrum through spectrum sensing. Within the CR‐IoTNet framework, joint spectrum sensing and allocation are performed to serve SU‐IoT devices via an interference‐free channel (IFC). The system comprises multiple primary user base stations (PU‐BSs) and SU devices functioning as IoT smart objects. Additionally, we integrate an improved neural network (INN) to adapt to dynamic network conditions and monitor primary user (PU) spectrum utilization using a comprehensive multiclass (J × 8) − D feature set. This combination of advanced techniques and CR technology aims to optimize spectrum management and support the growing IoT ecosystem. In particular, the INJSS‐CR obtained the greatest accuracy of 0.9492 at a training rate of 80%.

Cognitive radio technologies enable users to opportunistically access unused licensed spectrum and are viewed as a promising way to deal with the current spectrum crisis. Over the last 15 years, cognitive radio technologies have been extensively studied from algorithmic design to practical implementation. One pressing and fundamental problem is how to integrate cognitive radios into current wireless networks to enhance network capacity and improve users’ experience. Unfortunately, existing solutions to cognitive radio networks (CRNs) suffer from many practical design issues. To foster further research activities in this direction, we attempt to provide a tutorial for CRN architecture design. Noticing that an effective architecture for CRNs is still lacking, in this tutorial, we systematically summarize the principles for CRN architecture design and present a novel flexible network architecture, termed cognitive capacity harvesting network (CCHN), to elaborate on how a CRN architecture can be designed. Unlike existing architectures, we introduce a new network entity, called secondary service provider, and deploy cognitive radio capability enabled routers, called cognitive radio routers, in order to effectively and efficiently manage resource harvesting and mobile traffic while enabling users without cognitive radios to access and enjoy CCHN services. Our analysis shows that our CCHN aligns well to industrial standardization activities and hence provides a viable approach to implementing future CRNs. We hope that our proposed design approach opens a new venue to future CRN research.

During the last decade, Cognitive Radio (CR) has become a popular research topic. The availability of radio spectrum is in shortage, and CR technology can solve the problem by enabling dynamic spectrum access. This innovative technology has been used to manage the radio spectrum since it was introduced. These developments have led to rapid advances in this research field. A review of recent advances in Spectrum Sensing (SS) is presented in this paper, from its origins to its present state. A CR network has been found to be a highly effective and intelligent technology. Frequency spectrum is a bounded natural resource and an essential component of wireless communication networks. We explored CR in this paper and its various phases. Different definitions of CR are then presented from various institutions. Many different types of communications systems use CR techniques. It is anticipated that they will improve commercial and military data services, as well as increase the use of underutilized radio frequencies. In this paper, CR standards have been discussed, as well as its applications in various areas.

As the proliferation of wireless handheld devices such as smart phones and tablets grow exponentially, new technologies have to be adopted to efficiently use the radio frequency spectrum. Cognitive Radio(CR) network offers a promising solution to improve spectrum utilization and efficiency by harnessing the available spectrum resources in real-time. However, participants in the CR network can comprise of malicious adversaries who adopt dishonest and non-cooperative strategies to attack the network. In our research, we focus on a critical attack on the CR network: Primary User Emulation (PUE). In a PUE attack, the malicious adversary violates spectrum sharing etiquette by impersonating the primary user at the expense of other unselfish secondary users. To thwart such an attack, we present a strategy to authenticate the primary user, which involves collaborative learning among CR users.

Cognitive radio (CR) technology is designed to improve reliability in communication between users through efficient and dynamic spectrum exploitation. CRs address the problems in spectrum allocation and channel access and improve the rate of radio resource utilization. The flexibility of the CR networks (CRN) and communication medium exposes it to a variety of threats; primary user emulation attack (PUEA) is a malicious and denial-of-service kind of adversary that defaces CRN performance. This manuscript proposes an adaptive learning-based attack detection in CRN for detecting and mitigating PUEA by analyzing the received power of the transmitter. The learning process endorses some beneficial features by distinguishing low spectrum legitimate PU from an adversary. The learning process adopts cyclostationary feature analysis for distinguishing adversaries and low power PU in CR communications. The process of learning is further enhanced by estimating distance variance and communication time-based analysis for improving the rate of signal classification and SU communication rate. The experimental analysis proves the stability of the proposed detection method by improving the SU throughput, with lesser signal classification time and misdetection probability.

The cognitive radio technology allows solving one of the main issues of current wireless communication technologies, namely a deficit of vacant spectrum. A dynamic spectrum access used in the cognitive radio networks (CRN) gives an ability to access an unused spectrum in real time. Cooperative spectrum sensing is the most effective method for spectrum holes detecting. It combines sensing information of multiple cognitive radio users. In this paper, an experimental evaluation of spectrum sensing methods based on the Kolmogorov - Smirnov statistical test and Energy Detector using the Universal Software Radio Peripheral (USRP) devices synchronized through a MIMO cable and with further processing in the GNU Radio and Matlab software are presented. Three hard decision fusion schemes are analyzed. Simulation comparison between these rules is presented via Receiver Operating Characteristic (ROC) curves. The influence of real channel with interferences is compared in contrast to commonly assumed AWGN channel model of vacant channel noise.

We focus on a specific class of denial-of-service (DoS) attacks that is executed through Channel Eviction Triggering (CET), whereby adversary nodes unduly invoke mechanisms inherent in a cognitive radio (CR) network (CRN) operation to protect the licensed users and thus disrupt secondary access to the otherwise idle licensed bands. Skewing the spectrum sensing decision of CRN through sensing misreports is a manifestation of CET attacks. Whereas most studies in the literature focus on making the cooperative sensing more robust against such sensing misreports, we tackle the problem from the novel perspective of incentive alleviation. We distinguish two classes of such DoS attacks, which we refer to as CET and CET-jamming attacks. In the former case, the incentive of adversary CRs is to remove the competition of truthful CRs in accessing the licensed spectral ranges. The latter class of DoS attack deals with scenarios in which the adversary nodes are mainly interested in denying the chances of communication of CRN over primary bands and as such their incentive cannot be modelled by the same utility maximisation model as truthful CRs. We propose a solution for each class of attacks, and our numerical results verify the effectiveness of the proposed CET defence scheme in both cases. Copyright © 2012 John Wiley & Sons, Ltd.

Wireless technology has enabled the development of increasingly diverse applications and devices resulting in an exponential growth in usage and services. These advancements made the radio frequency spectrum a scarce resource, and consequently, its efficient use is of the ultimate importance. To cope with the growing demand, network design focused on increasing the spectral efficiency by making use of advancement in Cognitive Radio technology. Cognitive Radio can reduce the spectrum shortage problem by enabling unlicensed users equipped with Cognitive Radios to reuse and share the licensed spectrum bands. Using the fact that a Cognitive Radio is capable of sensing the environmental conditions and automatically adapting its operating parameters in order to enhance network performance, we would like to make use of its knowledge to predict the mobility of Cognitive Radio users to improve the overall performance of the Cognitive Radio network. This study makes novel use of mobility prediction techniques to enhance reliability, bandwidth efficiency and scalability of the cognitive radio networks. Firstly, prediction techniques are evaluated and compared for prediction accuracy. Secondly, routing protocol reliability, efficiency and scalability performances are evaluated under different prediction techniques. Simulation results verify the performance improvements even with moderate accuracy predictors. Results clearly show that hybrid Markov CDF prediction performs the best. When compared with no prediction it significantly improves average reliability and efficiency by 11% and 8%, respectively.

In recent years, channel-hopping-based medium access control protocols have been proposed to improve the capacity in a decentralized multichannel cognitive radio (CR) network without using extra control channels. Each CR user has to stochastically follow a default channel-hopping sequence in order to locate a channel and conduct its frame transmission. In this paper, theoretical analysis is conducted on the probability of channel availability and the average frame delay for primary users (PUs) by considering the impact caused by imperfect sensing of CR users and imperfect synchronization between the primary and CR networks. According to the proposed analytical model with realistic considerations, an optimal channel-hopping sequence (OCS) approach is designed for the CR users based on a dynamic programming technique. It is designed by exploiting the optimal load balance between channel availability and channel utilization within the delay constraints of PUs. By adopting the OCS approach, maximum aggregate throughput of CR users can be achieved while considering PU's quality-of-service (QoS) requirements. Moreover, in addition to the paired CR networks, the logical partition problem that occurs in generalized CR networks will also be addressed. This problem can severely degrade the aggregate throughput due to the decreased probability of connectivity between CR users, especially in a CR network with heavy traffic. Therefore, both wake-up successive contention (WSC) and wake-up counter-reset successive contention (WCSC) algorithms are proposed to increase the number of negotiations by both exploring the blind spot of imperfect sensing and amending the contention mechanisms between CR users. Compared to conventional channel-hopping sequences, numerical results illustrate that the proposed approaches can effectively maximize aggregate throughput for CR users under the QoS requirements of PUs.