Reliable spectrum sensing algorithm is a fundamental component in cognitive radio. In this paper, a non-cooperative spectrum sensing algorithm which needs only one cognitive radio node named CORDIC (Coordinate Rotation Digital Computer) Jacobi based method is proposed. The algorithm computes the eigenvalues of the sampled covariance of received signal mainly by shift and additional operations, which is suitable for hardware implementation. Based the latest random matrix theory (RMT) about the distribution of the limiting maximum and minimum eigenvalue ratio, the relationship between the probability of false alarm and the decision threshold is derived. Simulations and discussions show the method is effective. Real captured digital television (DTV) signals and Universal Software Radio Peripheral (USRP) are also employed to evaluate the performance of the algorithm, which prove the proposed algorithm can be applied in practical spectrum sensing applications.

Based on the current solutions to the problem of energy hole, this paper proposed a nonuniform node distribution clustering algorithm, NNDC. Firstly, we divide the network into rings, and then have an analysis and calculation on nodes' energy consumption in each ring of the network when clustering algorithm is applied to collect data. We also put forward a scheme of nonuniform node distribution on the basis of the proportion of nodes' energy consumption in each ring, and change nodes' active/hibernating states under density control mechanism when network coverage is guaranteed. Simulation shows NNDC algorithm can satisfyingly balance nodes' energy consumption and effectively avoid the problem of energy hole.

Cognitive radio (CR) is envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, the main concern is to reliably sense the presence of primary users (PUs) to attain protection against harmful interference caused by potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize the total sensing decision error at the common soft data fusion (SDF) centre of a structurally-centralized cognitive radio network (CRN). Using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed methods are compared with each other as well as with other conventional deterministic algorithms such as maximal ratio combining (MRC) and equal gain combining (EGC). Computer simulations confirm the superiority of the PSO-based scheme over the GA-based and other conventional MRC and EGC schemes in terms of detection performance. In addition, the PSO-based scheme also shows promising convergence performance as compared to the GA-based scheme. This makes PSO an adequate solution to meet real-time requirements.

Access control is an essential security component in protecting sensitive data and services from unauthorized access to the resources in mission-critical Cyber-Physical Systems (CPSs). CPSs are different from conventional information processing systems in such that they involve interactions between the cyber world and the physical world. Therefore, existing access control models cannot be used directly and even become disabled in an emergency situation. This paper proposes an adaptive Access Control model for Emergences (AC4E) for mission-critical CPSs. The principal aim of AC4E is to control the criticalities in these systems by executing corresponding responsive actions. AC4E not only provides the ability to control access to data and services in normal situations, but also grants the correct set of access privileges, at the correct time, to the correct set of subjects in emergency situations. It can facilitate adaptively responsive actions altering the privileges to specific subjects in a proactive manner without the need for any explicit access requests. A semiformal validation of the AC4E model is presented, with respect to responsiveness, correctness, safety, non-repudiation and concurrency, respectively. Then a case study is given to demonstrate how the AC4E model detects, responds, and controls the emergency events for a typical CPS adaptively in a proactive manner. Eventually, a wide set of simulations and performance comparisons of the proposed AC4E model are presented.

Recently, the International Telecommunication Union allocated the 470-862 MHz band to the digital broadcasting (DB) service. Moreover, the 790-862 MHz sub-band will be allocated to the next-generation mobile system, known as the International Mobile Telecommunication - Advanced (IMT-A), and to the DB on a co-primary basis in the year 2015. Currently, two candidate technologies are available to represent the IMT-A system; the Mobile WiMAX and Long Term Evolution - Advanced (LTE-A). One of the main criteria of the IMT-A candidate is to not cause additional interference to the primary service (i.e., DB). In this paper, we address the spectrum sharing issue between the IMT-A candidates and the DB service. More precisely, we investigate the interference effect between the DB service and the mobile network, which could be either LTE-A or WiMAX. Our study proposes a spectrum sharing model to take into account the impact of interference and evaluates the spectrum sharing requirements such as frequency separation and separation distance. This model considers three spectrum sharing scenarios: co-channel, zero guard band, and adjacent channel. A statistical analysis is performed, by considering the interferer spectrum emission mask and victim receiver blocking techniques. The interference-to-noise ratio is used as an essential spectrum sharing criterion between the systems. The model considers the random distribution of the users, antenna heights, and the bandwidth effect as well as the deployment environment in order to achieve spectrum sharing. The results show that LTE-A is preferable to WiMAX in terms of having less interference impact on DB; this can eventually allow the operation of both services without performance degradation and thus will lead to efficient utilization of the radio spectrum.

A terminal-based dynamic clustering algorithm is proposed in a multi-cell scenario, where the user could select the cooperative BSs from the predetermined static base stations (BSs) set based on dynamic channel condition. First, the user transmission rate is derived based on linear precoding and per-cell feedback scheme. Then, the dynamic clustering algorithm can be implemented based on two criteria: (a) the transmission rate should meet the user requirement for quality of service (QoS); (b) the rate increment exceeds the predetermined constant threshold. By adopting random vector quantization (RVQ), the optimized number of cooperative BSs and the corresponding channel conditions are presented respectively. Numerical results are given and show that the performance of the proposed method can improve the system resources utilization effectively.

This paper jointly investigates the bandwidth allocation, transmission strategy and relay positions for two-way transmission aware cellular networks with network coding (NC). Our goal is to minimize the transmission power of mobile terminals (MTs). Consider a cellular system, where multiple MTs exchange information with their common base station, firstly, we propose an efficient bandwidth allocation method and then give a transmission strategy for each MT to determine whether to use relay stations (RSs) for its two-way transmission with the BS or not. To further improve the system performance, the optimal positions of RSs are also jointly discussed. A GA-based algorithm is presented to obtain the optimum positions for RSs. Besides, the impacts of frequency reuse on MT's transmission power and system spectral efficiency (SE) under different number of relays are also discussed in our work. Numerical results show that the proposed NC aware scheme can extend MTs' battery life at least 6% more than traditional method.

With the rapid development of heterogeneous emerging wireless technologies and numerous types of mobile devices, the need to support robust mobile video streaming based on the seamless handover in Future Internet is growing. To support the seamless handover, several IP-based mobility management protocols such as Mobile IPv6 (MIPv6), fast handover for the MIPv6 (FMIPv6), Hierarchical MIPv6 (HMIPv6) and Proxy Mobile IPv6 (PMIPv6) were developed. However, MIPv6 depreciates the Quality-of-Service (QoS) and FMIPv6 is not robust for the video services in heterogeneous emerging wireless networks when the Mobile Node (MN) may move to another visited network in contrast with its anticipation. In Future Internet, the possibility of mobile video service failure is more increased because mobile users consisting of multiple wireless network interfaces (WNICs) can frequently change the access networks according to their mobility in heterogeneous wireless access networks such as 3Generation (3G), Wireless Fidelity (Wi-Fi), Worldwide Interoperability for Microwave Access (WiMax) and Bluetooth co-existed. And in this environment, seamless mobility is coupled according to user preferences, enabling mobile users to be "Always Best Connected" (ABC) so that Quality of Experience is optimised and maintained. Even though HMIPv6 and PMIPv6 are proposed for the location management, handover latency enhancement, they still have limit of local mobility region. In this paper, we propose a robust mobile video streaming in Heterogeneous Emerging Wireless Systems. In the proposed scheme, the MN selects the best-according to an appropriate metric-wireless technology for a robust video streaming service among all wireless technologies by reducing the handover latency and initiation time when handover may fail. Through performance evaluation, we show that our scheme provides more robust mechanism than other schemes.

The growth of Internet technologies and the widespread use of mobile devices have been paving the way for the increasing use of conferencing services. Two types of systems have been designed to provide conferencing services: 1) a conferencing system using session control over a peer-to-peer (P2P) network and 2) an IP Multimedia Subsystem (IMS) conferencing system. The IMS conferencing system was developed to adapt to a server-based centralized system, whereas the benefits of the P2P operational model in providing such conference services are widely acknowledged. However, each system provides conferencing services only to its own users. Therefore, in this paper, we propose an interworking model to support multimedia conferencing service between the P2P environment and IMS networks. We also introduce protocol architecture and some service scenarios. To verify this system model and the design architecture, we perform an actual implementation and show experienced test results.

Femtocells provide high quality indoor communications with low transmit power. However, when femtocells are applied in cellular systems, a co-channel interference problem between macrocells and femtocells occurs because femtocells use the same spectrum as do the macrocells. To solve the co-channel interference problem, a previous study suggested a resource allocation scheme in LTE cellular systems using FFR. However, this conventional resource allocation scheme still has interference problems between macrocells and femtocells near the boundary of the sub-areas. In this paper, we define an optimization problem for resource allocation to femtocells and propose a femtocell resource allocation scheme to solve the optimization problem and the interference problems of the conventional scheme. The evaluation of the proposed scheme is conducted by System Level Simulation while varying the simulation environments. The simulation results show that the proposed scheme is superior to the conventional scheme and that it improves the overall performance of cellular systems.

There are nowadays strong demands for intelligent surveillance systems, which can infer or understand more complex behavior. The application of crowd density estimation methods could lead to a better understanding of crowd behavior, improved design of the built environment, and increased pedestrian safety. In this paper, we propose a new crowd density estimation method, which aims at estimating not only a moving crowd, but also a stationary crowd, using images captured from surveillance cameras situated in various public locations. The crowd density of the moving people is measured, based on the moving area during a specified time period. The moving area is defined as the area where the magnitude of the accumulated optical flow exceeds a predefined threshold. In contrast, the stationary crowd density is estimated from the coarseness of textures, under the assumption that each person can be regarded as a textural unit. A multilayer neural network is designed, to classify crowd density levels into 5 classes. Finally, the proposed method is experimented with PETS 2009 and the platform of Gangnam subway station image sequences.

Traffic classification seeks to assign packet flows to an appropriate quality of service (QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.

The transmission opportunities between nodes in Delay Tolerant Network (DTNs) are uncertain, and routing algorithms in DTNs often need nodes serving as relays for others to carry and forward messages. Due to selfishness, nodes may ask the source to pay a certain reward, and the reward may be varying with time. Moreover, the reward that the source obtains from the destination may also be varying with time. For example, the sooner the destination gets the message, the more rewards the source may obtain. The goal of this paper is to explore efficient ways for the source to maximize its total reward in such complex applications when it uses the probabilistic two-hop routing policy. We first propose a theoretical framework, which can be used to evaluate the total reward that the source can obtain. Then based on the model, we prove that the optimal forwarding policy confirms to the threshold form by the Pontryagin's Maximum Principle. Simulations based on both synthetic and real motion traces show the accuracy of our theoretical framework. Furthermore, we demonstrate that the performance of the optimal forwarding policy with threshold form is better through extensive numerical results, which conforms to the result obtained by the Maximum Principle.

In this paper, we propose an efficient channel delay estimation method for orthogonal frequency-division multiplexing (OFDM) systems, especially over doubly-selective fading channels which are selective in both the symbol time domain and subcarrier frequency domain. For the doubly-selective fading channels in single frequency network (SFN), long and strong echoes exist and thus the conventional discrete Fourier Transform (DFT) based channel delay estimation system often fails to produce the exact channel delay profile. Based on the analysis of the discrete-time frequency response of the channel impulse response (CIR) coefficients in the DFT-based channel delay estimation system, we develop a method to effectively extract the true CIR from the aliased signals by employing a simple narrow-band low-pass filter (NB-LPF). The performance of the proposed system is verified using the COST207 TU6 SFN channel model.

With the prevalence of diverse services-oriented applications, such as IPTV systems and on-line games, the current underlying communication networks face more and more challenges on the aspects of flexibility and adaptability. Therefore, an effective and efficient multicast routing mechanism, which can fulfill different requirements of different personalized services, is critical and significant. In this paper, we first define the neighbor gradient, which is calculated based on the weighted sum of attributes such as residual link capacity, normalized hop count, etc. Then two distributed multicast routing algorithms which are neighbor Gradient-based Multicast Routing for Static multicast membership (GMR-S) and neighbor Gradient-based Multicast Routing for Dynamic multicast membership (GMR-D), are proposed. GMR-S is suitable for static membership situation, while GMR-D can be used for the dynamic membership network environment. Experimental results demonstrate the effectiveness and efficiency of our proposed methods.

A novel folded dipole type microstrip patch antenna designed for ultrahigh frequency (UHF) band radio frequency identification (RFID) tag is presented in this paper, which can be used on the metallic objects. The presented antenna is fabricated on a very thin Rogers 5880 substrate with a thickness of 0.508 mm. The structure consists of two folded dipole and two symmetrical shorting pins placed at both sides of feed point. An adjustable frequency response can be easy obtained via modify the location and radius of the shorting pins. The antenna has been analyzed by full wave simulations soft. The simulated bandwidth is about 67.2 MHz, which covers the Europe and North America UHF RFID frequency range. A manufactured prototype has been fabricated and measured to demonstrate the antenna performances. The simulation results agree with the measurement data well. The measured maximum reading range of the prototype can be reached 4.1 m in free space, and 3.2 m on a metal plate whose size is $150{\times}150{\times}8mm^3$.

Recent studies have indicated that a significant improvement in wireless video throughput can be achieved by Cross Layer Design with Side-information (CLDS) protocols. In this paper, we derive the operational rate of a CLDS protocol operating over a realistic wireless channel. Then, a Rate-Distortion (R-D) empirical model for above-capacity Scalable Video Coding (SVC) is deduced to estimate the loss of video quality incurred under inaccurate rate estimation scenarios. Finally, we develop a novel Unequal Error Protection (UEP) scheme which leverages the characteristics of LDPC codes to reduce the distortion of video quality in case of typically-observed burst wireless errors. The efficacy of the proposed rate adaptation architecture over conventional protocols is demonstrated by realistic video simulations using actual IEEE 802.11b wireless traces.

Peer-to-Peer (P2P) networks are becoming more and more popular in video content delivery services, such as Video on Demand (VoD). Scalability feature of P2P allows a higher number of simultaneous users at a given server load and bandwidth to use stream service. However, the quality of service (QoS) in these networks is difficult to be guaranteed because of the free-riding problem that nodes download the recourses while never uploading recourses, which degrades the performance of P2P VoD networks. In this paper, a distributed trust model is designed to reduce node's free-riding phenomenon in P2P VoD networks. In this model, the P2P network is abstracted to be a super node hierarchical structure to monitor the reputation of nodes. In order to calculate the reputation of nodes, the Hidden Markov Model (HMM) is introduced in this paper. Besides, a distinction algorithm is proposed to distinguish the free-riders and malicious nodes. The free-riders are the nodes which have a low frequency to free-ride. And the malicious nodes have a high frequency to free-ride. The distinction algorithm takes different measures to response to the request of these two kinds of free-riders. The simulation results demonstrate that this proposed trust model can improve QoS effectively in P2P VoD networks.

Wireless Body Area Networks (WBANs) are introduced as an enabling technology in tele-health for patient monitoring. Designing an efficient Medium Access Control (MAC) protocol is the main challenge in WBANs because of their various applications and strict requirements such as low level of energy consumption, low transmission delay, the wide range of data rates and prioritizing emergency data. In this paper, we propose a new MAC protocol to provide different requirements of WBANs targeted for medical applications. The proposed MAC provides an efficient emergency response mechanism by considering the correlation between medical signals. It also reduces the power consumption of nodes by minimizing contention access, reducing the probability of the collision and using an efficient synchronization algorithm. In addition, the proposed MAC protocol increases the data rate of the nodes by allocating the resources according to the condition of the network. Analytical and simulation results show that the proposed MAC protocol outperforms IEEE 802.15.4 MAC protocol in terms of power consumption level as well as the average response delay. Also, the comparison results of the proposed MAC with IEEE 802.15.6 MAC protocol show a tradeoff between average response delay and medical data rate.

Recent advances in cognitive radio technology have drawn immense attention to higher layer protocols above medium access control, such as transmission control protocol (TCP). Most proposals to improve the TCP performance in cognitive radio (CR) networks have assumed that either all nodes are in CR networks or the TCP sender side is in CR links. In those proposals, lower layer information such as the CR link status could be easily exploited to adjust the congestion window and improve throughput. In this paper, we consider a TCP network in which the TCP sender is located remotely over the Internet while the TCP receiver is connected by a CR link. This topology is more realistic than the earlier proposals, but the lower layer information cannot be exploited. Under this assumption, we propose an enhanced TCP protocol for CR networks called TCP for cognitive radio (TCP-CR) to improve the existing TCP by (1) detection of primary user (PU) interference by a remote sender without support from lower layers, (2) delayed congestion control (DCC) based on PU detection when the retransmission timeout (RTO) expires, and (3) exploitation of two separate scales of the congestion window adapted for PU activity. Performance evaluation demonstrated that the proposed TCP-CR achieves up to 255% improvement of the end-to-end throughput. Furthermore, we verified that the proposed TCP does not deteriorate the fairness of existing TCP flows and does not cause congestions.

Face detection is the first step of vision-based driver fatigue detection method. Traditional face detection methods have problems of high false-detection rates and long detection times. A space-time restrained Adaboost method is presented in this paper that resolves these problems. Firstly, the possible position of a driver's face in a video frame is measured relative to the previous frame. Secondly, a space-time restriction strategy is designed to restrain the detection window and scale of the Adaboost method to reduce time consumption and false-detection of face detection. Finally, a face knowledge restriction strategy is designed to confirm that the faces detected by this Adaboost method. Experiments compare the methods and confirm that a driver's face can be detected rapidly and precisely.

This paper describes interpolation method of motion field in the Wyner-Ziv video coding (WZVC) based on Expectation-Maximization (EM) algorithm. In the EM algorithm, the estimated motion field distribution is calculated on a block-by-block basis. Each pixel in the block shares similar probability distribution, producing an undesired blocking artefact on the pixel-based motion field. The proposed interpolation techniques are Bicubic and Lanczos which successively use 16 and 32 neighborhood probability distributions of block-based motion field for one pixel in k-by-k block on pixel-based motion field. EM-based WZVC codec updates the estimated probability distribution on block-based motion field, and interpolates it to pixel resolution. This is required to generate higher-quality soft side information (SI) such that the decoding algorithm is able to make syndrome estimation more quickly. Our experiments showed that the proposed interpolation methods have the capability to reduce EM-based WZVC decoding complexity with small increment of bit rate.

A new security management model based on Rough set and Bayesian learner is proposed in the paper. The model focuses on finding out malicious nodes and getting them under control. The degree of dissatisfaction (DoD) is defined as the probability that a node belongs to the malicious node set. Based on transaction history records local DoD (LDoD) is calculated. And recommended DoD (RDoD) is calculated based on feedbacks on recommendations (FBRs). According to the DoD, nodes are classified and controlled. In order to improve computation accuracy and efficiency of the probability, we employ Rough set combined with Bayesian learner. For the reason that in some cases, the corresponding probability result can be determined according to only one or two attribute values, the Rough set module is used; And in other cases, the probability is computed by Bayesian learner. Compared with the existing trust model, the simulation results demonstrate that the model can obtain higher examination rate of malicious nodes and achieve the higher transaction success rate.

Cryptographic hash functions are widely used in many information security applications like digital signatures, message authentication codes (MACs), and other forms of authentication. In response to recent advances in cryptanalysis of commonly used hash algorithms, National Institute of Standards and Technology (NIST) announced a publicly open competition for selection of new standard Secure Hash Algorithm called SHA-3. One important aspect of this competition is evaluation of hardware performances of the candidates. In this work we present efficient hardware implementations of SHA-3 finalists: JH, Keccak and Skein. We propose high speed architectures using Look-Up Table (LUT) resources on FPGAs, to minimize chip area and to reduce critical path lengths. This approach allows us to design data paths of SHA-3 finalists with minimum resources and higher clock frequencies. We implemented and investigated the performance of these candidates on modern and latest FPGA devices from Xilinx. This work serves as performance investigation of leading SHA-3 finalists on most up-to-date FPGAs.

In a traditional Single Sign-On (SSO) scheme, the user and the Service Providers (SPs) have given their trust to the Identity Provider (IdP) or Authentication Service Provider (ASP) for the authentication and correct assertion. However, we still need a better solution for the local/native true SSO to gain user confidence, whereby the trusted entity must play the role of the ASP between distinct SPs. This technical gap has been filled by Trusted Computing (TC), where the remote attestation approach introduced by the Trusted Computing Group (TCG) is to attest whether the remote platform integrity is indeed trusted or not. In this paper, we demonstrate a Trustworthy Mutual Attestation (TMutualA) protocol as a proof of concept implementation for a local true SSO using the Integrity Measurement Architecture (IMA) with the Trusted Platform Module (TPM). In our proposed protocol, firstly, the user and SP platform integrity are checked (i.e., hardware and software integrity state verification) before allowing access to a protected resource sited at the SP and releasing a user authentication token to the SP. We evaluated the performance of the proposed TMutualA protocol, in particular, the client and server attestation time and the round trip of the mutual attestation time.

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye's optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.

To ensure the security of wireless sensor networks, it is important to have a robust key management scheme. In this paper, we propose a Quorum-based key management scheme. A specific sensor, called as key distribution server (KDS), generates a key matrix and establishes a quorum system from the key matrix. The quorum system is a set system of subsets that the intersection of any two subsets is non-empty. In our scheme, each sensor is assigned a subset of the quorum system as its pre-distributed keys. Whenever any two sensors need a shared key, they exchange their IDs, and then each sensor by itself finds a common key from its assigned subset. A shared key is then generated by the two sensors individually based on the common key. By our scheme, no key is needed to be refreshed as a sensor leaves the network. Upon a sensor joining the network, the KDS broadcasts a message containing the joining sensor ID. After receiving the broadcast message, each sensor updates the key which is in common with the new joining one. Only XOR and hash operations are required to be executed during key update process, and each sensor needs to update one key only. Furthermore, if multiple sensors would like to have a secure group communication, the KDS broadcasts a message containing the partial information of a group key, and then each sensor in the group by itself is able to restore the group key by using the secret sharing technique without cooperating with other sensors in the group.