Explore the vast range of titles available.

This book focuses on Television White Space (TVWS) opportunities and regulatory aspects for cognitive radio applications, and includes case studies for the exploitation of TVWS depending on user's mobility, and the geo-location between user and the Base Station.

Cognitive radio sensor networks (CRSNs) are multi-channel-capable networks that inherit some of the challenges of traditional wireless sensor networks (WSNs), such as limited power source and hardware capacity. In several CRSN applications, such as surveillance and intelligent transportation systems, node mobility is a typical assumption. However, as a node changes its physical location, spectrum mobility may also follow. Therefore, the treating of node mobility in CRSN imposes new challenges on all network layers, especially in the data link layer. In this paper, we propose a novel cross-layer mobility-aware medium access control (MAC) protocol for CRSN. We also propose an efficient spectrum-aware cluster formation and maintenance. The proposed scheme is more robust against primary users’ activity as well as node mobility in a CRSN because it integrates spectrum sensing at the physical (PHY) layer with packet scheduling at the MAC layer. Simulation results show that the proposed protocol guarantees about 60 % more common channels per cluster in a higher node ratio. Moreover, the proposed MAC protocol outperforms existing protocols (e.g., CogMesh, cluster-based MAC, and KoN-MAC) in terms of the packet delivery ratio, energy consumption, and delay, by up to 5, 30, and 25 %, respectively.

This study examines the uplink and downlink communication in a structured coded nonorthogonal multiple access (NOMA) in the context of cognitive radio networks (CRNs). Due to the ever-increasing demand for spectrum-efficient communication systems, NOMA has emerged as an effective approach to enhance spectral efficiency by allowing multiple users to share the same frequency resources. Furthermore, CRN also improves spectrum utilization by enabling dynamic spectrum access while primary users are present. This work presents a method that can maximize the spectral efficiency by combining NOMA and CRN mechanisms. The suggested system is evaluated in terms of throughput, spectral efficiency, and bit error rate (BER). The collected results show that the proposed strategy performs better in reducing data mistakes when two users access the spectrum at different signal-to-noise ratios (SNR), with a 7 dB improvement for 1st user and a 2.5 dB improvement for the 2nd user, respectively, in the downlink scenario. Next, the exact BER expressions for both coded and uncoded uplink NOMA systems are introduced. As a result, the proposed system demonstrates superior performance and needs only 11 dB to reach 1 × 10−6 of BER while the uncoded system cannot operate in this harsh environment and the BER is fixed at 0.25 dB.

Providing an in-depth treatment of the core enablers of cognitive radio technology, this unique book places emphasis on critical areas that have not been sufficiently covered in existing literature. You find expert guidance in the key enablers with respect to communications and signal processing. The book presents fundamentals, basic solutions, detailed discussions of important enabler issues, and advanced algorithms to save you time with your projects in the field.For the first time in any book, you find an adequately detailed treatment of spectrum sensing that covers nearly every aspect of the subject. Moreover, this valuable resource provides you with thorough working knowledge of localization and interference mitigation as enablers of cognitive radio technology. The book includes all the necessary mathematics, statistical and probabilistic treatments, and performance analysis to give you a comprehensive understanding of the material.

In recent times, Cognitive Radio Networks (CRNS) have been broadly investigated in light of the unceasingly growing demands of the Internet of Things (IoT) applications, paving the path to equipping IoT objects with Cognitive Radio (CR) technology. Thus, the implementation of these two technologies in unison has been attracting research interests. Today, CR technology is implemented in Ad-Hoc Networks (AHNs). This combination has several benefits, namely better coverage, lower costs, and simpler maintenance compared to infrastructure-based networks. Nonetheless, a limited number of researchers have lately paid attention to the area of Quality of Service (QoS) for being one of the key routing metrics adopted to define the optimal paths for the Cognitive Radio Ad Hoc Network (CRAHN). Accordingly, this work recommends the stability of a route in CRAHN and proposes Half -Duplex (HD) CRAHN routing protocol without Common Control Channel (CCC) using the control packets’ multicast transmission, referred to as Stability Based Multipath Downstream Quality Routing Protocol (SMDQRP). Interestingly, many CRN overheads have been reduced in the proposed routing protocol such as avoiding the overhead of transmitting the Route Request Packet (RRQP) over all channels and nodes. To be precise, we allow each node to transmit over all of its available channels instead of using all channels in the network. Further, every necessary calculation is made while the RRQP is being sent from the source to the destination not vice versa. Data transmission in HD mode with path recovery is used to test the proposed protocol, along with a compound accumulative routing metric named Stability Based Multipath Downstream Quality (SMDQ) to select the required QoS paths featured with the highest level of stability and maximal throughput. The path is recovered in data transmission by allowing the nodes in the path to use the already saved available channels between every two consecutive nodes in case of failure of any suggested channel. Moreover, a unique sensing technique based on energy level extracted from the received signals at a CR node along with waveform-based detection is factored in for their suitability to our proposed routing protocol as we aim to solve the problems in Multi-Cast-based Half Duplex Routing Protocol (MC-HDRP). The performance of the newly presented protocol is assessed and compared with the most relevant protocols called Probabilistic and Deterministic Path Selection (PDPS) and MC-HDRP by conducting several related simulation experiments and scenarios with the use of a special technologically advanced simulator based on Java language. Contrary to the MC-HDRP, the simulation’s results demonstrate an explicit significant improvement related to throughput, packet drop ratio, and the number of disconnected networks.

The authors consider the problem of energy consumption in a multiband cognitive radio network, in which a secondary user can sense multiple frequency bands authorised to the primary user (PU) before it decides to access some frequency bands and keep the interference introduced to the PU under a certain threshold. The sensing time and power allocation need to be designed carefully to reduce the energy consumption. Therefore they identify the optimal sensing time and accessing power to minimise the energy consumption of the cognitive radio that simultaneously senses and accesses multiple bands under the multiband sensing-based spectrum sharing scheme. To obtain the optimal solution, they transform the original problem formulated as the ratio of two functions into another parametric formulation. The interference power is considered as one of constraints in the author's scheme in order to protect the PU. The algorithm of optimal sensing time and power allocation is proposed for the multiband cognitive radio system. Furthermore, they discuss the effect of channel number, interference power and gain estimation of channels on energy consumption and optimal sensing time and validate their schemes and analysis by simulation results.

We investigate the optimal allocation of power in the downlink cooperative cognitive radio network using decode and forward (DF) relaying technique. The power allocation in DF relaying for green cooperative cognitive radio with an objective of maximising energy-efficiency is a constraint non-linear non-convex fractional programming problem. The optimisation needs to satisfy the primary users interference constraints and secondary users outage constraints. The authors present the optimal power allocation in DF relaying by transforming the constraint non-linear non-convex fractional power allocation problem into a concave fractional programme by using Charnes–Cooper transformation. The authors also present an iterative algorithm that uses parametric transformation and guarantees ε-optimal convergence. The convergence of the iterative algorithm is proved and numerical results obtained for cooperative cognitive radio network are presented with different network parameter settings.

Vehicular communication has been envisioned to support a myriad of essential fifth-generation and beyond use-cases. However, the increasing proliferation of smart and intelligent vehicles has generated a lot of design and infrastructure challenges. Of particular interest are the problems of spectrum scarcity and communication security. Consequently, we considered a cognitive radio-enabled vehicular network framework for accessing additional radio spectrum and exploit physical layer security for secure communications. In particular, we investigated the secrecy performance of a cognitive radio vehicular network, where all the nodes in the network are moving vehicles and the channels between them are modeled as double-Rayleigh fading. Furthermore, adopting an underlay approach, the communication between secondary nodes can be performed by employing two interference constraint strategies at the primary receiver; (1) Strategy I: the secondary transmitter power is constrained by the interference threshold of the primary receiver, and (2) Strategy II: the secondary transmitter power is constrained by both the interference threshold of the primary receiver and the maximum transmit power of the secondary network. Under the considered strategies, we derive the exact secrecy outage probability (SOP) and ergodic secrecy capacity (ESC) expressions over double-Rayleigh fading. Moreover, by analyzing the asymptotic SOP behavior, we show that a full secrecy diversity of 1 can be achieved, when the average channel gain of the main link goes to infinity with a fixed average wiretap channel gain. From the ESC analysis, it is revealed that the ESC follows a scaling law of ΘlnΩm2Ωe2 for large Ωm and Ωe, where Ωm and Ωe are the average channel gains of the main link and wiretap link. The numerical and simulation results verify our analytical findings.

With new telecommunications engineering applications, the cognitive radio (CR) network‐based internet of things (IoT) resolves the bandwidth problem and spectrum problem. However, the CR‐IoT routing method sometimes presents issues in terms of road finding, spectrum resource diversity and mobility. This study presents an upgradable cross‐layer routing protocol based on CR‐IoT to improve routing efficiency and optimize data transmission in a reconfigurable network. In this context, the system is developing a distributed controller which is designed with multiple activities, including load balancing, neighbourhood sensing and machine‐learning path construction. The proposed approach is based on network traffic and load and various other network metrics including energy efficiency, network capacity and interference, on an average of 2 bps/Hz/W. The trials are carried out with conventional models, demonstrating the residual energy and resource scalability and robustness of the reconfigurable CR‐IoT.

Since there is a competition between subcarriers because FBMC (Filter Bank Multicarrier) modulation technology does not need subcarriers to be orthogonal to each other, we consider the evolutionary game method to optimize subcarrier allocation. Because the adjacent subcarriers do not need to be orthogonal to each other in FBMC, there is conflict and competition, thus the evolutionary game theory is used to optimize the subcarrier allocation problem. We innovatively introduced the channel state matrix to show the quality of subcarriers. Considering the height of secondary user and base station’s antenna, the total data transmission rate limit, total power consumption constraint and power consumption constraint on a single subcarrier, a nonlinear fractional programming problem is established where maximum energy efficiency is the objective function, total data transmission rate limit, total power consumption constraint and power consumption constraint on a single subcarrier are constraint conditions. The utility function for each secondary user is established when the evolutionary game operator is designed. When the utility function becomes optimal, the evolutionary game reaches Nash equilibrium, and the strategy combination is considered to be the energy efficient resource allocation scheme. Through experimental simulation, EESA-EG proposed in this paper gives the most reasonable subcarrier allocation scheme, allocates more subcarriers for the subcarriers with better channel state and the energy efficiency in EESA-EG is optimal.