Fuzzy Systems for Spectrum Access, Mobility and Management for Cognitive Radios

This chapter addresses the issues in air interface designs for Cognitive Radios. Fuzzy logic system is used as one of the soft computing techniques to learn to sub optimality and vagueness. Many good, simple, and quick fuzzy based solutions have been developed since few decades in many diverse domains. Through this chapter, the authors first discuss the significance and need of soft computing techniques in designing such solutions and then present fuzzy based solutions for spectrum access, mobility, and management. Hierarchical fuzzy systems have been used to get over to the problem of curse of dimensionality. The proposed solutions consider an architecture, similar to the one proposed by IEEE 802.22 working group, for spectrum sharing and management. Models have been designed using fuzzy logic toolbox in MATLAB, and the system performance is checked using SIMULINK.

Game Theory for Cognitive Radio

Demands on high data rate applications are increasing and consequently demands on spectral resources are increasing as well. Although electromagnetic spectrum is recently said to be in a scarcity situation, several studies have shown that this scarcity is mainly due to the legacy command-and-control regulation rather than due to physical scarcity of spectrum. For this reason, researchers have started investigating techniques to better manage the usage of spectrum. Among these techniques there exist the methods allowing the primary/secondary usage of spectrum, or secondary market. Secondary market techniques mainly manage sensing, accessing, and aborting the spectrum usage by the secondary users. Techniques developed for secondary market context are also referred to as algorithms for Cognitive Radio (CR) networks. Regulators worldwide took measures to promote the deployment of primary/secondary context. In this chapter, the authors give an illustrative discussion on CR and on the application of game theory to overcome the spectrum scarcity problem. Game theory is a field of applied mathematics that describes and analyzes scenarios with interactive decisions. In recent years, there has been considerable interest in adopting game theoretic approaches to model many communications and networking problems such as radio resource management and routing. Nowadays, game theory is also used to model interactive situations for CR terminals.

Dynamic Resource Management and Optimization in Heterogeneous Wireless Networks under IEEE1900.4 Framework

Next generation (xG) wireless networks will contain a number of radio access networks (RANs), which mainly depend on various radio access technologies (RATs). Meanwhile, the subscribers in the current networks will be equipped with multi-mode, reconfigurable, and cognitive equipments, with or without multi-homing abilities. This chapter looks at the definition, principle, architecture, optimization objective, specific approach, and optimization of resource for such a composite network /hybrid network context under IEEE1900.4 framework. First, the challenges of spectrum scarcity, and the requirements of a novel resource management framework in the limited resource scenario are summarized. Second, the authors focus on the techniques of resource management and optimization architecture. After a simple description of the basics of IEEE P1900.4, a novel double cognition cycle (DCC) design in the fashion of utility function theory is proposed in this chapter. The DCC contains two cognition cycles corresponding to the terminal and network side, respectively, and is uniformed in the frameworks of network utility maximization (NUM). Third, the authors capture the challenges of resource management protocols of the current developing heterogeneous networks and investigate the dynamic churning behaviors, where the subscribers are equipped with intelligent terminals with the aid of cognitive radios.

Distributed Coalition Formation and Resource Allocation in Cognitive LTE Femto-cells

This chapter investigates resource allocation in a Universal Mobile Telecommunication System (UMTS) Long Term Evolution (LTE) network. Users form coalitions, each exploiting resources in a particular femto-cell, while occupying optimal resources in the sense that total network throughput is maximized. Users in each cell collaborate to increase network throughput and simultaneously attempt to increase their own payoffs subject to a fairness criterion. Payoffs to the users are defined as the monetary equivalent of the individual users’ achievable throughput in the specified coalition structure. A distributed game-theoretic resource allocation mechanism is studied whereby users autonomously decide which sub-channel in which coalition to join. It is proved that if each user operates according to the proposed algorithm, the sum throughput of all links converges almost surely to its maximum feasible value.

Opportunistic Spectrum Sensing and Transmissions

Nowadays, cognitive radio is one of the most promising paradigms in the arena of wireless communications, as it aims at the proficient use of radio resources. Proper utilization of the radio spectrum requires dynamic spectrum accessing. To this end, spectrum sensing is undoubtedly necessary. In this chapter, various approaches for dynamic spectrum access scheme are presented, together with a survey of spectrum sensing methodologies for cognitive radio. Moreover, the challenges are analyzed that are associated with spectrum sensing and dynamic spectrum access techniques. Sensing beacon transmitted from different cognitive terminals creates significant interference to the primary users if proper precautions have not been taken into consideration. Consequently, cognitive radio transmitter power control are finally addressed to analyze energy efficiency aspects.

Boosting Secondary-User Performance

This chapter addresses a few challenges and issues in developing Cognitive Radio Networks (CRNs), and provides unique solutions to enhance security at physical layer and to boost CRN computing power in a distributed manner. In this age of vast connectivity, network security becomes more and more prominent. In addition to the security means added at the upper layers, security can be further enhanced at physical layer. In particular, location based wideband channel characteristic as a unique signature can be utilized for security enhancement. Such a scheme is proposed and examined in different configurations. Lack of computing power is another critical issue, as CRN is expected to have more and more features. Instead of increasing onboard computing power, off-board computing resources can be connected to boost overall computing power. With increased computing power, the CRNs would be able to undertake computationally heavy tasks such as executing machine-learning algorithms and performing radio intrusion detection.

Channel State Prediction in Cognitive Radio

Spectrum sensing is the cornerstone of cognitive radio, which detects the availability of a spectrum band for the current time. In theory, the result of spectrum sensing reflects the current channel state, which is the ideal case. However, according to the author’s measurements, hardware platforms can introduce a non-negligible time delay on the signal path, which undermines the accuracy of spectrum sensing. To reduce the negative impact of the hardware platform time delay, channel state prediction in cognitive radio is proposed and presented in this chapter. As examples, channel state prediction algorithms based on a modified hidden Markov model (HMM) are given and tested using recorded real-world data. Moreover, as a second stage, cooperative channel state prediction is also proposed and experimentally evaluated. The experimental results approve that channel state prediction in cognitive radio indeed helps improve the accuracy of spectrum sensing in practical cases.

Robust Performance of Spectrum Sensing in Cognitive Radio Networks

Harmonic coexistence of cognitive radio systems and licensed systems requires the secondary users to have the capability of sensing and keeping track of primary users’ transmissions. While existing spectrum sensing methods usually assume known distributions of the primary signals, such an assumption is often not true in practice. As a result, applying existing sensing methods will often lead to unreliable detection performance in practical networks. In this chapter, the authors try to investigate the sensing performance under the distribution uncertainty of primary signals. They first investigate the performance bounds for single user detection with unknown distribution, and provide an analytical expression for the lower bound of detection probability. Moreover, they bring the distribution uncertainty into multi-user cooperative sensing. The authors formulate the optimal sensing design as a robust optimization problem, and propose an iterative algorithm to determine the optimal decision threshold for each user. Extensive simulations demonstrate the effectiveness of the proposed algorithm.

Spectrum Sensing in Cognitive Radio

The cognitive radio has been widely investigated to support modern wireless applications. To exploit the spectrum vacancies in cognitive radios, the chapter considers the collaborative spectrum sensing by multiple sensor nodes in the likelihood ratio test (LRT) frameworks. In this chapter, the functions of sensors can be served through the cooperative regular nodes in the cognitive radio, or the specifically deployed sensor nodes for spectrum sensing. In the LRT, the sensors make individual decisions. These individual decisions are then transmitted to the fusion center to make the final decision, which provides better detection accuracy than the individual sensor decisions. The author provides the lowered-bounded probability of detection (LBPD) criterion as an alternative criterion to the conventional Neyman-Pearson (NP) criterion. In the LBPD criterion, the detector pursues the minimization of the probability of false alarm while maintaining the probability of detection above the pre-defined value. In cognitive radios, the LBPD criterion limits the probabilities of channel conflicts to the primary users. Under the NP and LBPD criteria, the chapter provides explicit algorithms to solve the LRT fusion rules, the probability of false alarm, and the probability of detection for the fusion center. The fusion rules generated by the algorithms are optimal under the specified criteria. In the spectrum sensing, the fading channels influence the detection accuracies. The chapter investigates the single-sensor detection and collaborative detections of multiple sensors under various fading channels and derives testing statistics of the LRT with known fading statistics.

Security for Cognitive Radio Networks

Most of the frequency spectrum bands have already been licensed, and the licensed spectrum is not being utilized efficiently. Cognitive Radio Networks (CRNs) are the kind of full duplex radio that automatically altered its transmission or reception parameters, in such a way that the entire wireless communication network of which it is a node communicates efficiently, while avoiding interference with primary or secondary users. In this chapter, the authors introduce the concept of security threats that may pose a serious attack in CRN. Due to the unique characteristics of CRN, such network is highly vulnerable to security attacks compared to wireless network or infrastructure-based wireless network. The main objective of this chapter is to assist CR designers and the CR application engineers to consider the security factors in the early development stage of CR techniques. Challenges and various security issues are explored with respect to OSI (Open Systems Interconnection) reference model. Various possible and attacks are discussed broadly and respective solutions are also proposed by this chapter. Different architectures and models are also explained, and compared with the existing models.