Cooperative Cognitive Radio Networks

The Complete Spectrum Cycle

Mohamed Ibnkahla

• Publisher: CRC Press
• Year: 2018
• ISBN:
  9781351831857
• Edition: 1
• Topic: Computer Science
• Subtopic: Computer Networking
• Index: Computer Science

Cooperative Cognitive Radio Networks: The Complete Spectrum Cycle provides a solid understanding of the foundations of cognitive radio technology, from spectrum sensing, access, and handoff to routing, trading, and security. Written in a tutorial style with several illustrative examples, this comprehensive book:

• Gives an overview of cognitive radio systems and explains the different components of the spectrum cycle
• Features step-by-step analyses of the different algorithms and systems, supported by extensive computer simulations, figures, tables, and references
• Fulfills the need for a single source of information on all aspects of the spectrum cycle, including the physical, link, medium access, network, and application layers

Offering a unifying view of the various approaches and methodologies, Cooperative Cognitive Radio Networks: The Complete Spectrum Cycle presents the state of the art of cognitive radio technology, addressing all phases of the spectrum access cycle.

1	Introduction to Cognitive Radio

1.1 INTRODUCTION

Spectrum scarcity is one of the biggest challenges that are being faced by modern communication systems. The efficient use of available licensed spectrum bands is becoming a predominant issue due to the ever-increasing demand of the radio spectrum as well as the inefficient utilization incurred by the rigid and static spectrum allocation set by the telecommunications regulating authorities. Cognitive radio (CR) has emerged as one of the most promising paradigms to address spectrum scarcity and underutilization problems. The basic idea of CR is that unlicensed users (or secondary users [SUs]) are allowed to use the spectrum when licensed users (or primary users [PUs]) are not present or when the interference caused by SUs is below a given threshold. Thus, by introducing cognition in the network, the spectrum utilization can be enhanced.

Cognition implies that the radio learns from its environment and adapts its operating parameters based on the acquired knowledge. Thus, the radio can actively exploit the possible empty bands in the licensed spectrum in order to make use of them. The network’s capacity to learn, adapt its parameters, and make decisions is basically what makes the system cognitive and agile.

This chapter provides the basic concepts of cognitive radio networks (CRNs). Section 1.2 describes the cognitive cycle. Section 1.3 discusses the functions of the CR framework. Section 1.4 presents the paradigms of CR access. Finally, Section 1.5 gives an overview of the book.

1.2 COGNITIVE RADIO FRAMEWORK

The CR framework is based on interactions among different entities within the network as well as with the surrounding environment. Each entity has a cognitive presence in the network, replacing purely centralized control or predefined rules. The aim is to better exploit resources and manage behavior based on each entity’s adaptation to the conditions of the network and its surrounding environment.

Traditionally, cross-layer design has been used to optimize different protocols by allowing the nodes to use relevant information when making decisions in the quest to improve the network’s performance. However, this process has its limitations as it cannot optimize multiple goals and learn from its surrounding environment. Therefore, there is a need for a new evolved and intelligent technique to enable learning and planning. Cognition has been introduced as the process of learning through perception, reasoning, and knowledge. CRNs are defined as self-aware, self-organizing, and adaptive networks that perform intelligent adaptations. These adaptations occur when the nodes in the network carry out observations regarding the state of the network, when the nodes share information between each other that is beyond the scope of the layered architecture, and when nodes learn and reason before making and carrying out optimized decisions.

FIGURE 1.1 The CR cycle.

Cognition has rapidly gained importance in the research fields as it enables more intelligent and better optimized networks. The cognitive cycle presented in [1] summarizes the major steps in the CR process (Figure 1.1). The cognitive loop enables intelligent adaptations through learning and sharing of information between the different entities in the network. There are six major elements that constitute the CR cycle:

• Environment: This includes the network and the surrounding environment such as physical channels, other users, devices, networks, and any objects that may affect the network conditions (e.g., weather conditions, obstacles, economic indicators, and trading rules).

• Sense: The different CR entities are capable of sensing and monitoring the environment such as the spectrum bands, interference levels, physical propagation channel parameters, and location of PUs and SUs.

• Plan: SUs make plans and assess these plans before taking decisions.

• Decide: Decision is based on knowledge and learning where the decisionmaking process optimizes the systems’ resources.

• Act: The SU will act on the environment based on the decisions made. This can be through a sequence of actions (e.g., access to the media, routing of packets, allocation of resources, and modification of transmission schemes).

• Learn: Learning is the central element in the cognitive cycle where the nodes are equipped with a knowledge base and a learning tool that allows them to keep track of all information related to the network and environment conditions. This allows the system to learn from current and previous actions, predict future behaviors, and intelligently use them in the planning and decision-making processes.

1.2.1 DEFINITION OF COGNITIVE RADIO

A CR system can be defined in [2] as follows:

A radio system employing technology that allows the system to obtain knowledge of its operational and geographical environment, established policies and its internal state; to dynamically and autonomously adjust its operational parameters and protocols according to its obtained knowledge in order to achieve predefined objectives, and to learn from the results obtained.

The main feature of the CR paradigm is dynamic spectrum access, as opposed to conventional wireless paradigms, which abide by a static spectrum allocation policy. In its broadest sense, dynamic spectrum allocation is classified into three categories [3]:

• Dynamic exclusive use model: This method follows the current spectrum regulation policy, where licensed spectrum is used exclusively by the incumbent user. However, the owner may sell, share, or trade the spectrum property rights with other parties.

• Spectrum commons model: This model is developed on the foundation of unlicensed industrial, scientific, and medical (ISM) band success such as WiFi. This allows open sharing of spectrum among all users given that these users abide by several predetermined standards.

• Hierarchical access model: It is based on hierarchical access structure with PUs and SUs. The idea behind this model is that an SU may utilize the unoccupied channels as long as it is not causing harmful interference to PUs. This model can further be classified into stand-alone (i.e., it does not share network information) and cooperative (i.e., it involves spectrum information sharing to further optimize spectrum access).

Even though these access models are essentially different, all of them strive to accomplish the same objective, that is, enhance the spectrum utilization, and this is one of the several promises and potentials envisioned by the CR paradigm. There are also other advantages of CRNs:

• Improve radio link performance: CRNs can improve radio link performance by optimizing resource allocation to SUs (e.g., channel, power, rate, modulation scheme, and coding scheme).

• Limit interference: CRNs can help to reduce the impact of interference through dynamic spectrum access and adaptive resource allocation.

• Balance traffic: CRNs can help PU networks to offload traffic from densely occupied bands to other unoccupied bands. For instance, if a cellular network is experiencing high loads, then with the help of CRs, the network can opportunistically offload some of its traffic to other available bands.

• Assist PUs: CRs can cooperate with the PUs to help relay information from a PU transmitter to a PU receiver.

1.3 FUNCTIONS OF COGNITIVE RADIO FRAMEWORK

Conventional wireless paradigms are characterized by static spectrum allocation policies, where governmental agencies assign spectrum to licensed holders on a long-term basis and for large geographical region. CRNs are envisioned to change this trend by enabling coexistence of SUs with PUs via heterogeneous wireless architectures and dynamic spectrum access techniques. Therefore, each SU in the CRN must reliably perform the following tasks:

• Determine which portions (channels) of the spectrum are available.

• Select the best available channel.

• Coordinate access to this channel with other users.

• Vacate the channel when a PU is detected or when the interference level exceeds a predefined threshold.

• Cooperate with other users to improve network or user efficiency (optional).

From these tasks, one can deduce that the SU must have the following characteristics [4]:

• Cognitive capabilities: The CR must be aware of the surrounding environment to intelligently adapt its parameters in order to provide reliable communicat...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Acknowledgments
• Author
• Preface
• Acknowledgments
• Author
• Chapter 1 Introduction to Cognitive Radio
• Chapter 2 Spectrum Sensing
• Chapter 3 Cooperative Spectrum Acquisition
• Chapter 4 Cooperative Spectrum Acquisition in the Presence of Interference
• Chapter 5 Spectrum Sensing: Performance Measures and Design Trade-Offs
• Chapter 6 Spectrum Handoff
• Chapter 7 MAC Protocols in Cognitive Radio Networks
• Chapter 8 Cognitive Radio Ad Hoc and Sensor Networks: Network Models and Local Control Schemes
• Chapter 9 Medium Access in Cognitive Radio Ad Hoc Networks
• Chapter 10 Routing in Multihop Cognitive Radio Networks
• Chapter 11 Economics of Cognitive Radio
• Chapter 12 Security Concerns in Cognitive Radio Networks
• Index