Securing Privacy Using Optimization and Statistical Models in Cognitive Radio Networks

In cognitive radio networks, secondary users need to access the licensed spectrum while neither disturbing the transmissions of the primary users nor introducing much interference to other secondary users. Hence, proper power controlling is of paramount importance to ensure efficient system operation. The previous work on power control in cognitive networks mainly focuses on the interactions among a set of secondary users. The primary users' influence is rarely considered. In this paper, a new power control game model is formulated, by including the primary users into the player set of the game. The primary users are rewarded for sharing their licensed spectrum with secondary users by setting a reasonable interference cap for the secondary transmissions. However, we ensure a minimum required Quality of Service (QoS) for primary users by severely penalizing their utility if their required transmission quality is not met. Simultaneously, the secondary users achieve energy efficient transmissions while not introducing much interference to both the primary and other secondary users. We prove that the proposed cognitive power control game has a unique Nash equilibrium (NE). The numerical examples show that the proposed game theoretical power control algorithm can provide the secondary users with energy efficient transmissions and the primary users with reasonable monetary rewards, while not compromising their required QoS.

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.

With the rapid development of wireless services and applications, the currently radio spectrum is becoming more crowded. How to accommodate more wireless services and applications within the limited radio spectrum becomes a big challenge faced by modern society. Cognitive radio (CR) is proposed as a promising technology to tackle this challenge by introducing secondary users (SUs) to opportunistically or concurrently access the spectrum allocated to primary users (PUs). Currently, there are two prevalent CR models: the spectrum sharing model and the opportunistic spectrum access model. In the spectrum sharing model, the SUs are allowed to coexist with the PUs as long as the interferences from SUs do not degrade the quality of service (QoS) of PUs to an unacceptable level. In the opportunistic spectrum access model, SUs are allowed to access the spectrum only if the PUs are detected to be inactive. These two models known as underlay and overlay schemes, respectively. This thesis studies a number of topics in CR networks under the framework of these two schemes. First, studied cognitive radio transmissions under QoS delay constraints. Initially, we focused on the concept: effective capacity for cognitive radio channels in order to identify the performance in the presence of QoS constraints. Both underlay and overlay schemes are studied taking into consideration the activity of primary users, and assuming the general case of channel fading as Gamma distribution. For this setting, we further proposed a selection criterion by which the cognitive radio network can choose the adequate mode of operation. Then, we studied the cognitive radio transmissions focusing on Rayleigh fading channel and assumed that no prior channel knowledge is available at the transmitter and the receiver. We investigated the performance of pilot-assisted transmission strategies. In particular, we analyzed the channel estimation using minimum mean-square-error (MMSE) estimation, and analyzed efficient resource allocation strategies. In both cases, power allocations and effective capacity optimization were obtained. Effective capacity and interference constraint were analyzed in both single-band and multi-band spectrum sensing settings. Finally, we studied optimal access probabilities for cognitive radio network using Markov model to achieve maximum throughput for both CR schemes.

We investigate opportunistic cooperation between secondary (unlicensed) users and primary (licensed) users in cognitive radio networks. We consider two models for such cooperation. In the first model, called the Cooperative Relay Model, a secondary user cannot transmit its own data concurrently with a primary user. However, it can employ cooperative relaying in order to improve the effective transmission rate of the primary user. In the second model, called the Interference Model, a secondary user is allowed to transmit its data concurrently with a primary user. However, the secondary user can “cooperate” by deferring its transmissions when the primary user is busy. In both models, the secondary users must make intelligent cooperation decisions as they seek to maximize their own throughput subject to average power constraints. The decision options are different during idle and busy periods of the primary user, and the decisions in turn influence the durations of these periods according to a controllable infinite state Markov chain. Such problems can be formulated as constrained Markov decision problems, and conventional solution techniques require either extensive knowledge of the system dynamics or learning based approaches that suffer from large convergence times. However, using a generalized Lyapunov optimization technique, we design a novel greedy and online control algorithm that overcomes these challenges. Remarkably, this algorithm does not require any knowledge of the network arrival rates and is provably optimal.

In cognitive networks, unlicensed users can use underutilized licensed spectrum when it is not in use by the licensed user. To avoid interference, unlicensed (secondary) user must leave the spectrum when it is accessed by the licensed (primary) user. Since it takes some time to sense the nearby free channels for the secondary user and switch to them, interruption in the ongoing data transmission is inevitable. Hence, the delay constraints of many applications cannot be met. So a cache generation approach is discussed in this paper, which reduces the time lag of delay by systematically generating cache of the signal at appropriate places. Since, every secondary users' cache must be placed in such a way that the time lag of delay is reduced to bare minimum, a game theoretic approach is used for smart distribution and allocation of cache nodes for unlicensed users.

We consider a cooperation scenario between primary users and untrusted secondary users in cognitive radio networks. The secondary users are willing to help the primary users to relay the primary users' messages in reward for being allowed to share the primary users' spectrum bands. However, the primary users might be reluctant to accept this help, since the secondary users are untrustworthy and may try unauthorized decoding of the primary users' messages. This paper will answer the question: when is this cooperation mutually beneficial for primary and secondary users? Taking an approach of information-theoretic secrecy, such as coding techniques for wiretap channels, the primary users can allow the secondary users to sense and relay the message, while ensuring that the secondary users are ignorant of the primary users' messages. We characterize an achievable secrecy rate of primary users with a rate of the secondary users' communication. From the derived rate pairs, an optimization problem is formulated such that the secondary transmitter distributes its transmit power to maximize its data rate while providing a higher secrecy rate to the primary users. We demonstrate that this cooperation can provide a positive secrecy rate, even when a non-cooperative scheme achieves a zero secrecy rate.

In cognitive radio networks, wireless nodes adapt to the surrounding radio environment and utilize the spectrum of licensed users. The cognitive radio environment is dynamic, and wireless channels are accessible by both legitimate and illegitimate users. Therefore, maintaining the security of cognitive radio networks is a challenging task, which must be addressed thoroughly. Further, with the recent exponential surge in wireless nodes and associated high data rate requirements, energy consumption is also growing at an unprecedented rate. Hence, energy efficiency becomes an important metric that must be considered in the design of future wireless networks. Accordingly, by considering the great ecological and economic benefits of green wireless networks, this work focus on energy-efficient resource allocation in secure cognitive radio networks. Since physical-layer security is an emerging technique that improves the security of communication devices, in this paper, an ergodic secure energy efficiency problem for a cognitive radio network is formulated with a primary user, a secondary user, and an eavesdropper. As the formulated problem is non-convex, a concave lower bound is applied to transform the original non-convex problem into a convex one. Further, by adopting the fractional programming and dual decomposition techniques, optimal power allocation strategies are obtained with the aim of maximizing the ergodic secure energy efficiency of the secondary user with constraints on the average interference power and average transmit power. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm.

Energy-efficient cooperative cognitive relaying schemes for cognitive radio networks

The cooperation among the secondary users or among the secondary users and the primary users have proven to bring many benefits to both primary and secondary users in cognitive radio networks. In this paper, cooperative relaying in cognitive radio networks is studied for rateless coding error-control mechanism. For a pair of primary transmitter and receiver, we find the region in which any secondary or cognitive user can cooperate with the primary user in a constructive way. A queueing theoretical model is employed to describe the underlying system parameters and to create a mathematical framework for the analysis. The throughput performance of the secondary users is maximized based on the input traffic of the primary users. Using the unique properties of rateless codes, a low-complexity relay selection mechanism is also introduced. Through the experimental analysis, we show that the proposed rateless-coding-based cooperative mechanism can perform similar to the more complicated and more costly selective-repeat automatic repeat request algorithm. The numerical analysis using the Rapid Analysis of Queueing Systems (RAQS) software package is provided to support the findings.

Cognitive radio network (CRN) has evolved to explore the unused spectrum by secondary users (SUs) where spectrum license is held by primary user (PU). CRN has two important features such as node mobility and spectrum mobility. The node mobility allows SUs to move freely in the network, whereas spectrum mobility is due to the random appearance of PU in channels. SU node may be dynamically disconnected due to both of the reasons and rejoins if the spectrum is free from PU in opportunistic manner. Therefore, in CRN, it is very difficult to ensure connectivity, quality of service (QoS), bandwidth efficiency, and throughput. To address this problem, we propose a distributed spectrum handover algorithm for CRN. The spectrum handover refers to the procedure that when the current channel of a SU is no longer available, the SU needs to break off the on-going transmission, vacate that channel, and determine a newly available channel to continue the transmission. Our algorithm is based on awareness of the channel characterization where SU node uses prediction method to find available channel list to proceed possible spectrum switching. Our algorithm is a kind a proactive handover algorithm.

Motivated by the low utilization of the licensed spectrum across many frequency bands, sensing-based oppor- tunistic spectrum access has recently emerged as an alternative to the outdated exclusive spectrum access policy. Under this new paradigm, a secondary (unlicensed) user monitors a primary (licensed) frequency band for a given and opportunistically transmits if it does not detect any ongoing licensed operations. Evidently, selection of the parameters involves balanc- ing a tradeoff between the speed and the quality with which the secondary user senses the licensed band. With the average throughput as the performance criterion, we obtain the parameters so as to optimize the performance of the secondary user while providing the primary user with its desired level of interference protection. I. INTRODUCTION As evidenced by recent measurements, many frequency bands across the licensed spectrum are significantly under- utilized (1), (2). This finding suggests that the spectrum scarcity, as perceived today, is largely due to the inefficient fixed frequency allocations rather than the physical shortage of the spectrum and has led the regulatory bodies to consider the opportunistic access to the temporally/spatially unused licensed bands (a.k.a. the white spaces) as a means to improve the efficiency of spectrum usage. In the absence of cooperation or signalling between the primary licensee and the secondary users, spectrum availability for the opportunistic access may be determined by direct spectrum where the secondary user monitors a licensed band for a given sensing time and opportunistically transmits if it does not detect any ongoing licensed operations. This approach is particularly appealing due to its low deployment cost and its compatibility with legacy primary users and is being considered for inclusion in the upcoming IEEE 802.22 standard for opportunistic access to the TV spectrum (3). Due to their ability to autonomously detect and to react to the changes in the spectrum usage, secondary users equipped with the spectrum capability may be considered as a primitive form of the cognitive radio (4). Design of any scheme involves balancing a tradeoff between the quality and the speed of through an appropriate selection of the time. As we shall illustrate, in the context of spectrum sensing, may be fine- tuned to enhance the secondary users' perceived quality-of- service (QoS) as long as the regulatory constraint for the protection of the primary users against harmful interference is satisfied. In particular, we will obtain the optimum times at different stages of the spectrum to maximize the average throughput of the secondary user. In this paper, simple energy detection (a.k.a. radiometry) (5) is chosen as the underlying detection scheme. In general, when some information about the structure of the primary signal is available, ad hoc feature-detectors offer a better performance (6). We note, however, that the methodology employed in this paper may be applied to optimize different spectrum sensors once the quality is characterized in terms of the time. The remainder of this paper is organized as follows. The regulatory constraints on spectrum are described in the following section. Section 3 provides an overview of the energy-based spectrum sensing. The optimum times for different stages of the spectrum are derived in Section 4. Finally, this paper is concluded in Section 5.

A cognitive radio (CR) network refers to a secondary network operating in a frequency band originally licensed/allocated to a primary network consisting of one or multiple primary users (PUs). A fundamental challenge for realizing such a system is to ensure the quality of service (QoS) of the PUs as well as to maximize the throughput or ensure the QoS, such as signal-to-interference-plus-noise ratios (SINRs), of the secondary users (SUs). In this paper, we study single-input multiple output multiple access channels (SIMO-MAC) for the CR network. Subject to interference constraints for the PUs as well as peak power constraints for the SUs, two optimization problems involving a joint beamforming and power allocation for the CR network are considered: the sum-rate maximization problem and the SINR balancing problem. For the sum-rate maximization problem, zero-forcing based decision feedback equalizers are used to decouple the SIMO-MAC, and a capped multi-level (CML) water-filling algorithm is proposed to maximize the achievable sum-rate of the SUs for the single PU case. When multiple PUs exist, a recursive decoupled power allocation algorithm is proposed to derive the optimal power allocation solution. For the SINR balancing problem, it is shown that, using linear minimum mean-square-error receivers, each of the interference constraints and peak power constraints can be completely decoupled, and thus the multi-constraint optimization problem can be solved through multiple single-constraint sub-problems. Theoretical analysis for the proposed algorithms is presented, together with numerical simulations which compare the performances of different power allocation schemes.

Cognitive Radio (CR) technique has been proposed for improving spectrum efficiency by dynamic spectrum access. In Cognitive Radio Networks (CRNs), unlicensed Secondary Users (SUs) with CR can utilize licensed spectrum without interfering licensed Primary Users (PUs). For effectively avoiding interference with licensed PUs and malicious attacks from jammers, a two-stage Learning-based Optimal Channel Selection (LOCS) algorithm for unlicensed SUs in distributed heterogeneous CRNs is proposed in this paper. The LOCS algorithm enables SUs to obtain real states of the licensed channels without knowing their information. Hence, SUs using LOCS algorithm can efficiently avoid collision and attack with PUs and jammers. Besides, the LOCS algorithm considers hardware limitation of the SUs, i.e., SUs can only sense and access parts of the license spectrum during any given time. SUs can select the optimal channels for spectrum sensing and data transmission by using the LOCS algorithm. Simulation results show the efficiency of our proposed algorithm in terms of collision and attack avoidance.

Turning foes to allies in cognitive radio networks

In cognitive radio network (CRN), the utilities results in Nash equilibrium of power control game without using pricing are inefficient. In this paper, a distributed power control algorithm is proposed to improve the utilities of both primary user (PU) and secondary users (SUs) in the CRN based on game theoretic framework. A distributed power control is a non-cooperative power control game, and the quality of service (QoS) received by PU and SUs terminals are referred to as the utility function. PU and SUs act as decision makers in the game and they maximize their utilities in a distributed fashion. We introduce a new pricing function for SUs as a function of transmit power and square amount of interference in order to guide SUs to an efficient Nash equilibrium point. Analysis of the existence and uniqueness of Nash equilibrium for the proposed power control game with pricing is presented. Simulation results show that the proposed power control algorithm via a new pricing function maximizes the number of SUs access the unused spectrum, and improves the utilities of PU and SUs.