Cognitive Radio Mobile Ad Hoc Networks

In cognitive radio mobile ad hoc networks (CR-MANETs), secondary users can cooperatively sense the spectrum to detect the presence of primary users. In this chapter, we propose a fully distributed and scalable cooperative spectrum sensing scheme based on recent advances in consensus algorithms. In the proposed scheme, the secondary users can maintain coordination based on only local information exchange without a centralized common receiver. We use the consensus of secondary users to make the final decision. The proposed scheme is essentially based on recent advances in consensus algorithms that have taken inspiration from complex natural phenomena including flocking of birds, schooling of fish, swarming of ants, and honeybees. Unlike the existing cooperative spectrum sensing schemes, there is no need for a centralized receiver in the proposed schemes, which make them suitable in distributed CR-MANETs. Simulation results show that the proposed consensus schemes can have significant lower missing detection probabilities and false alarm probabilities in CR-MANETs. It is also demonstrated that the proposed scheme not only has proven sensitivity in detecting the primary user’s presence but also has robustness in choosing a desirable decision threshold.

Cognitive radio (CR) technology is a promising solution to enhance the spectrum utilization by enabling unlicensed users to exploit the spectrum in an opportunistic manner. Since unlicensed users are considered as temporary visitors to the licensed spectrum, they are required to vacate the spectrum when a licensed user reclaims it. Due to the randomness of the appearance of licensed users, disruptions to both licensed and unlicensed communications are often difficult to prevent, which may lead to low throughput of both licensed and unlicensed communications. In this chapter, a proactive spectrum handoff framework for CR ad hoc networks is proposed to address these concerns. In the proposed framework, channel switching policies and a proactive spectrum handoff protocol are proposed to let unlicensed users vacate a channel before a licensed user utilizes it to avoid unwanted interference. Network coordination schemes for unlicensed users are also incorporated into the spectrum handoff protocol design to realize channel rendezvous. Moreover, a distributed channel selection scheme to eliminate collisions among unlicensed users in a multi-user spectrum handoff scenario is proposed. In our proposed framework, unlicensed users coordinate with each other without using a common control channel, which is highly adaptable in a spectrum-varying environment. We compare our proposed proactive spectrum handoff protocol with a reactive spectrum handoff protocol, under which unlicensed users switch channels after collisions with licensed transmissions occur under different channel coordination schemes. Simulation results show that our proactive spectrum handoff outperforms the reactive spectrum handoff approach in terms of higher throughput and fewer collisions to licensed users. Furthermore, our distributed channel selection can achieve substantially higher packet delivery rate in a multi-user spectrum handoff scenario, compared with existing channel selection schemes. In addition, we propose a novel three-dimensional discrete-time Markov chain to characterize the process of reactive spectrum handoffs and analyze the performance of unlicensed users. We validate the numerical results obtained from our proposed Markov model against simulation and investigate other parameters of interest in the spectrum handoff scenario. Our proposed analytical model can be applied to various practical network scenarios.

In this chapter, we define DS-CDMA/OFDM spectrum sharing systems and investigate the impact of the primary service communication activity as well as other system parameters on the interference level at the secondary service receiver. The achieved capacity of the secondary service is directly related to the interference level at the secondary service receiver as well as the secondary service adopted sub-channel selection policy. The achievable capacity of the secondary service in such systems is obtained under different sub-channel selection policies in fading environments. Two general sub-channel selection policies are studied in this chapter: uniform sub-channel selection and non-uniform sub-channel selection. Uniform sub-channel selection fits into the cases where a priori knowledge on sub-channels state information is not available at the secondary transmitter. For cases with available a priori knowledge on sub-channels state information, a variety of non-uniform sub-channel selection policies are studied. We then present results on the scaling law of the opportunistic spectrum sharing in DS-CDMA/OFDM systems with multiple users. We provide numerical results to compare different sub-channel selection policies.

As the novel and effective approach to improve the utilization of the precious radio spectrum, cognitive radio technology is the key to realize the dynamic spectrum access (DSA) networks, where the secondary (unlicensed) users can opportunistically utilize the unused licensed spectrum in a way that confines the level of interference to the range the primary (licensed) users can tolerate. However, there are many new challenges associated with cognitive radio networks, such as the multi-channel hidden terminal problem and the fact that the time-varying channel availability differs for different secondary users, in the medium access control (MAC) layer. To overcome these challenges, we propose an efficient Cognitive Radio-EnAbled Multi-channel MAC (CREAM-MAC) protocol, which integrates the cooperative sequential spectrum sensing at physical layer and the packet scheduling at MAC layer, over the wireless cognitive radio networks. Under the proposed CREAM-MAC protocol, each secondary user is equipped with a cognitive radio-enabled transceiver and multiple channel sensors. Our cooperative sequential spectrum sensing scheme improves the accuracy of spectrum sensing and further protects the primary users. The proposed CREAM-MAC enables the secondary users to best utilize the unused frequency spectrum while avoiding the collisions among secondary users and between secondary users and primary users. We develop the Markov chain model and \(M/G^Y/1\) queueing model to rigorously study our proposed CREAM-MAC protocol for both the saturation networks and the non-saturation networks. We also conduct extensive simulations to validate our developed protocol and analytical models.

We investigate the performance of a cognitive personal area network (CPAN) in which spectrum sensing is linked to packet transmissions. Efficient CPAN operation may be achieved if each data transmission is taxed by requiring the transmitting node to participate in cooperative sensing for a prescribed time period. In this approach, each node is allowed to transmit a single packet in one transmission cycle, but must then ‘pay’ for it by spectrum sensing, which not only ensures fairness with respect to transmission but also distributes the sensing burden to all nodes. We describe a probabilistic model of the integrated system and evaluate its performance with respect to packet transmissions and spectrum sensing. We discuss two modifications that involve centralized and distributed selection of the channels to be sensed. We also propose an adaptive algorithm to determine the tax coefficient and show that it offers superior data transmission performance while not affecting the sensing accuracy.

In this chapter we introduce the concept of the control channel cloud to solve the control channel problem in dynamic spectrum access (DSA)-based ad hoc networks. A DSA-based ad hoc network is an infrastructure-less wireless network based on DSA and featured by self-organization, self-configuration, and self-healing. One of the challenges in such a network is the common control channel problem, which is caused by the opportunistic spectrum sharing nature of secondary users (SU) in the network. Without a common control channel, it is a challenge to coordinate the behaviors of SU nodes in a DSA-based ad hoc network. The control channel cloud approach, which relies only on the local information exchange to function, aligns the control channel of SU nodes to the same channel in a distributed way if a common control channel exists. It provides a simple but scalable way to synchronize the control channel in a dynamically changed radio environment. The convergence of the proposed approach is proved. The performance of proposed algorithms is studied by simulation.

Recent research activities about cognitive radio (CR) are mainly focusing on opportunistic spectrum access and spectrum utilization. However, CR technology will have significant impacts on upper layer performance such as topology control and routing in wireless networks, especially in mobile ad hoc networks (MANETs). The dynamic spectrum availability issue imposes more challenges on routing in CR-MANETs. Since the spectrum availability is affected by primary user activities and the mobility of cognitive users, cognitive routing is required to be forward looking rather than reactive. To this end, a topology control and routing framework is presented in this chapter, where cognitive routing is enabled by topology control. In the framework, topology control serves as a middleware and a cross-layer module residing between routing and CR module. Prediction techniques can be used to construct a smart network topology, which provisions cognition capability to routing. Particularly, we present a distributed prediction-based cognitive topology control (PCTC) scheme to demonstrate the framework and verify its feasibility.

In this chapter, we propose a classification of existing routing schemes for cognitive radio mobile ad hoc networks (CR-MANETs) and review these representative CR-MANET routing schemes. Then, we describe a CR-MANET model and present a novel adaptive routing design for the CR-MANET, referred to as ARDC, algorithmically and through examples. ARDC is based on the graph modeling approach, and its most significant contribution is that ARDC adapts to dynamic changes in the network topology much more computationally efficient than other CR-MANET routing schemes. At last, some further research directions on CR-MANET routing are identified.

Cognitive radio (CR) has been proposed as a promising solution to improve connectivity, self-adaptability, and efficiency of spectrum usage. When used in video applications, user-perceived video quality experienced by secondary users is a very important performance metric to evaluate the effectiveness of CR technologies. However, most current research only considers spectrum utilization and effectiveness at MAC and PHY layers, ignoring the system performance of upper layers. Therefore, in this chapter we aim to improve the user experience of secondary users for wireless video services over cognitive radio networks. We propose a quality-driven cross-layer optimized system to maximize the expected user-perceived video quality at the receiver end, under the constraint of packet delay bound. By formulating network functions such as encoder behavior, cognitive MAC scheduling, transmission, as well as modulation and coding into a distortion-delay optimization framework, important system parameters residing in different network layers are jointly optimized in a systematic way to achieve the best user-perceived video quality for secondary users in cognitive radio networks. Furthermore, the proposed problem is formulated into a MIN-MAX problem and solved by using dynamic programming. The performance enhancement of the proposed system is evaluated through extensive experiments based on H.264/AVC.

This chapter presents an adaptive networking platform using WiFi/WiMAX technologies for cognitive vehicle-to-roadside communications, which can be used to transfer safety messages and provide Internet access for mobile users inside vehicles. The proposed platform is based on a heterogeneous multihop cluster-based vehicular network, where a vehicular node can choose to play the role of a gateway or a client. The gateway nodes communicate directly with a roadside base station through a WiMAX link. The client nodes connect to the gateways through WiFi links. Traffic from client nodes are relayed by the gateways to a roadside base station. The vehicular nodes are the self-interest (i.e., rational) and have capability to learn and adapt decision to achieve their objectives independently. A decision-making framework is proposed for this WiFi/WiMAX platform. This distributed decision-making framework, which enables the vehicular nodes with cognitive capability, is modeled and analyzed using game theory. Also, a Q-learning algorithm is used in vehicular nodes to provide the cognitive capability to learn and adapt their decision. Dynamics of Q-learning algorithm can be modeled as an evolutionary game.

Low-cost automated health monitoring system sees a high demand with the Presidents’ proposal on health care reform. Legacy health care monitoring systems demand a great amount of resources such as health care personnel and medical equipments. This increases the cost of health care making it unaffordable to the majority of our society. This chapter introduces an architecture and design of a health care automation network. The health care automation network uses a cognitive radio-based infrastructure to monitor real-time patients’ vital signs, collect, and document medical information. The health care automation network can be implemented in hospitals or in senior communities. This network can leverage the existing infrastructure and reduce the cost of implementation. Research challenges in development of cognitive radio health care automation network are also discussed.

In this chapter we propose a scenario for interoperability between high-speed downlink packet access (HSDPA) and Wi-Fi. This scenario involves the end-user traveling in a public transportation system and requesting multimedia services to the operator. The interoperability between HSDPA and Wi-Fi (IEEE 802.11e standard) radio access technologies (RATs) is first addressed, a topology in which the user has access to both RATs was considered, together with a common radio resource management (CRRM) to manage the connections. We reached the conclusion that the CRRM enables to increase the system throughput when the load thresholds are set to 0.6 for HSDPA and 0.53 for Wi-Fi. Then, spectrum aggregation is implemented in HSDPA. A resource allocation (RA) algorithm allocates user packets to the available radio resources (in this case Node Bs operating at 2 and 5 GHz are available) in order to satisfy user requirements. Simulation results show that gains up to 22% may be achieved. We have also sought the most efficient way to manage routing packets inside the Wi-Fi network. The proposal which uses links with higher throughputs enables to reach the best results, with gains up to 300% in the packet delivery ratio. Finally, we discuss the challenges that need to be addressed in order to materialise the envisaged cognitive radio scenario in public transportation.

In this chapter, we present an application of the Cognitive Networking paradigm to the design and development of autonomous Cognitive Access Point (CogAP) for Wi-Fi hotspots and home wireless networks. In these environments, we typically use only one AP per service provider/residence for providing wireless connectivity to the users. Here we can reduce the cost of autonomic network control by equipping the same AP with a cognitive functionality. We first present the architecture of autonomous CogAP which consists of two main modules: Traffic sensing module and cognitive controller module. The traffic sensing module uses an efficient packet sampling scheme to characterize traffic from all Wi-Fi channels with single wireless interface. The cognitive controller module consists of two submodules: traffic predictor and cognitive decision engine. The Neural Network-based traffic predictor module makes use of the historical traffic traces for traffic prediction on all channels. The cognitive decision engine makes use of traffic forecasts to dynamically decide which channel is best for CogAP to operate on. We have built a prototype CogAP device using off-the-shelf hardware components and obtained better performance with respect to state-of-the-art channel selection strategies.

Efficient resource allocation is one of the key concerns of implementing cognitive radio networks. Game theory has been extensively used to study the strategic interactions between primary and secondary users for effective resource llocation. The concept of spectrum trading has introduced a new direction for the coexistence of primary and secondary users through economic benefits to primary users. The use of price theory and market theory from economics has played a vital role to facilitate economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks.

With this motivation, we present an extensive summary of the related work that uses economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks.

Cognitive radio networks are seen as the key enabling technology to address the spectrum shortage problem in wireless applications and services. One of the major challenges for implementing cognitive radio networks is to guarantee selfcoexistence among devices, which means address interference issues among devices operating under the same set of rules and sharing the same resources. Among the several mathematical tools used to address the self-coexistence problem, we recognize the game theoretic approach as the most powerful. In this chapter, first we present an overview of cognitive radio technology focusing on the importance of guaranteed self-coexistence among cognitive devices. Then, we analyze the pros and cons of several game theoretic approaches proposed in the literature in order to model the self-coexistence problem. We conclude by describing non-cooperative and cooperative game paradigms to model the self-coexistence problem in cognitive radio networks.