Variable Persistence Sensing Schemes for Opportunistic Spectrum Access

Cognition technologies can significantly enhance spectrum utilization through secondary usage. Secondary users （SUs） search for spectrum holes which are not used by Primary users （PUs） and communicate through them. The design and analysis of simple opportunistic spectrum access schemes for maximizing utilization efficiency and minimizing delay of SUs under limited sensing bandwidth and energy is still at infancy. In this work, we consider PU＇s frequency occupancy patterns and propose three simple variable persistence sensing schemes for maximum exploitation of idle spectrum chunks by SUs, and perform their theoretical analysis. Numerical case studies are presented to verify the theoretical analysis and illustrate the performance of the schemes proposed.     

Optimal energy efficiency capacity under joint design of sensing and transmission duration for cognitive radio system

Due to its opportunistic spectrum sharing capability, cognitive radio （CR） has been proposed as a fundamental solution to alleviate the contradiction between spectrum scarcity and inefficient utilization of licensed spectrum. In CR system （CRS）, to efficiently utilize the spectrum resource, one important issue is to allocate the sensing and transmission duration reasonably. In this paper, the evaluation metric of energy efficiency, which represented the total number of bits that were delivered with per joule of energy consumed, is adopted to evaluate the proposed scheme. We study a joint design of energy efficient sensing and transmission durations to maximize energy efficiency capacity （EEC） of CRS. The tradeoff between EEC and sensing and transmission durations are formulized as an optimization problem under constraints on target detection probability of secondary users （SUs） and toleration interference threshold of primary users （PUs）. To obtain the optimal solution, optimizing sensing duration and transmission duration will be first performed separately. Then, a joint optimization iterative algorithm is proposed to search the optimal pair of sensing and transmission durations. Analytical and simulation results show that there exists a unique duration pair where the EEC is maximized, and that the EEC of the proposed joint optimization algorithm outperforms that of existed algorithms. Furthermore, the simulation results also reveal that the performance of the proposed low complexity iterative algorithm is comparable with that of the exhaustive search scheme.     

Optimal and Suboptimal Access and Transmission Polices for Dynamic Spectrum Access over Fading Channels in Cognitive Radio Networks

We propose a cross-layer optimal access and transmission framework for dynamic spectrum access to maximize expected long-term average throughput under power and collision constraints by a dynamic programming method namely Constrained Markov decision process （CMDP）. The optimal policy for CMDP is capable of guiding transmitter to choose an available channel and transmission rate at the beginning of each frame for its long-term goals according to current channel sensing results and prior channel fading information. The complexity of finding the optimal policy by Linear programming （LP） approach increases exponentially with the number of channels and fading levels, which incurs so-called curse of dimensionality. Therefore we propose two complexity- reduced suboptimal policies, namely, policy separation and heuristic algorithms. Finally, we compare the performances of policies by numerical results.     

Performance Analysis of Spoken Arabic Digits Recognition Techniques

A performance evaluation of sound recognition techniques in recognizing some spoken Arabic words, namely digits from zero to nine, is proposed. One of the main characteristics of aU Arabic digits is polysyllabic words except for zero. The performance analysis is based on different features of phonetic isolated Arabic digits. The main aim of this paper is to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on three recognition features： the Yule-Walker spectrum features, the Walsh spectrum features, and the Mel frequency Cepstral coefficients （MFCC） features. The MFCC based recognition system achieves the best average correct recognition. On the other hand, the Yule-Walker based recognition system achieves the worst average correct recognition.     

TD-SCDMA： Spectrum Modeling, Experimental Verification of Power Amplifier Nonlinearity

RF Power amplifiers （PA） are critical components in Time division-Synchronous code division multiple access （TD-SCDMA） systems, and PA nonlinearity is one of the main concerns in RF power amplifier designs. This paper presents experimental verification of the spectrum modeling of a RF power amplifier in TD-SCDMA system based on our previous work. The results verify the theoretical spectrum model we derived closely fits the experimental measurements.     

Numerical Simulation of Near Field Characteristics for Lens Antenna by Hybrid FDTD-PWS Method

An efficient hybrid Finite-difference time- domain （FDTD） method and Plane wave spectrum （PWS） method is presented to analyze the near field characteristics of lens antenna. Firstly, the aperture plane field distribution is obtained by the FDTD method. Secondly, the PWS method is employed to calculate the near field distribution from the knowledge of the aperture plane field distribution. In order to demonstrate the accuracy of the proposed method, a lens antenna at Ka band is designed and fabricated as an example. For comparison, a horn an- tenna and a lens antenna without outer lens are simulated to evaluate differences among the lenses on focusing prop- erties. And the focal plane field is measured by the Planar- near-fields （PNF） method. It is found that the results obtained by the FDTD-PWS method are in good agreement with the experimental data after the probe compensation.     

lntra-Cavity Absorption Sensors for Gas Detection Using Wavelength Sweep Technique

Wavelength sweep technique （WST） is introduced into intra-cavity fiber laser （ICFL） for low concentration gas detection. The limitation induced by noise can be eliminated using this method, and the performance of the system is improved. The sensitivity of the system is reduced to less than 300 ppm. With WST, sweeping characteristic of the ICFL can be described according to known gas absorption spectra.     

Self-Organization Approaches for Optimization in Cognitive Radio Networks

Cognitive radio （CR） is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques. However, cognitive radio networks （CRNs） may also impose some challenges due to the ever increasing complexity of network architecture, the increasing complexity with configuration and management of large-scale networks, fluctuating nature of the available spectrum, diverse Quality-of-Service （QoS） requirements of various applications, and the intensifying difficulties of centralized control, etc. Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm. In this paper, fundamentals of CR, including spectrum sensing, spectrum management, spectrum mobility and spectrum sharing, have been surveyed, with their paradigms of self-organization being emphasized. Variant aspects of self- organization paradigms in CRNs, including critical functionalities of Media Access Control （MAC）- and network-layer operations, are surveyed and compared. Furthermore, new directions and open problems in CRNs are also identified in this survey.     

A Probability Driven Quadri-Stage Contention Protocol for Mobile Ad Hoc Networks

The paper proposes a new contention based Time division multiple access （TDMA） Medium access control （MAC） protocol in wireless ad hoc networks, which can be termed Quadri-stage contention protocol （QSCP）. The QSCP protocol is free of both the ＂hidden terminal＂ and the ＂exposed terminal＂ problems. It is distributive and arbitrarily scalable. In the dedicated contention stage, nodes exchange their ＂Normalized accumulation and dissipation rate of payload （NADROP）＂ messages in 2-hop neighborhood, and then run a contention probability calculation algorithm to decide the probability of sending a contention frame. The algorithm guaran- tees that the number of time slot reserved by a node is proportional to its NADROP value, which can remarkably improve the end-to-end throughput when network load is heavy, and is more efficient in energy consumption. The simulation results demonstrate that QSCP performs better than the existing protocols.     

A Scalable Peer-to-Peer Web Services Overlay for Semantic Discovery

The growing number of web services advocates distributed discovery infrastructures which are semantics-enabled. We introduce a novel approach for semantic discovery of web services in structured P2P-based （Peer-to-Peer） registries. We partition concepts into different CGs （Concept groups） and index these ordered concept sets in a two-phase semantic routing mechanism. Each node and query has one concept set as its unique ID. For each concept in the query, current node first route the query to a node with nodeID that shares a prefix as long as with the query, but a longer CG. Second, the query will be routed to a node sharing a longer prefix than that of the current node. Combining with semantic similarity calculation, our proposal guarantees that most existing services matching a query will be found with bounded costs in terms of number of nodes involved. The scalability and reliability of our approach are also confirmed through emulation tests.     

A Fuzzy Similarity-based Clustering Optimized by Particle Swarm Optimization

Traditional fuzzy clustering algorithms based on objective function is unable to determine the optimum number of clusters, sensitive to the initial cluster centers, and easily sunk into the issue of local optimum. A Fuzzy similarity-based clustering （FSBC） algorithm is proposed in this paper. This method consists three phases： first, the objective function is modified by integrating Fuzzy C-means （FCM） and Possibilistic C-means （PCM） method; second, using the density function from data for similarity-based clustering to automatically generate initial prototype without requesting users to specify; finally, the iteration process optimized by Particle swarm optimization （PSO） to obtain appropriate adjustment parameters that can provide better results, which avoids the local minimum problems of traditional methods. The experimental results on the synthetic data and UCI standard data sets show that the proposed algorithm has greater searching capability, less computational complexity, higher clustering precision.     

Novel Active Contour Model for Image Segmentation Based on Local Fuzzy Gaussian Distribution Fitting

A novel active contour model is proposed, which incorporates local information distributions in a fuzzy energy function to effectively deal with the intensity inhomogeneity. Moreover, the proposed model is convex with respect to the variable which is used for extracting the contour. This makes the model independent on the initial condition and suitable for an automatic segmentation. Furthermore, the energy function is minimized in a computationally efficient way by calculating the fuzzy energy alterations directly. Experiments are carried out to prove the performance of the proposed model over some existing methods. The obtained results confirm the efficiency of the method.     

PTCP Incast in Data Center Networks

In recent years, dual-homed topologies have appeared in data centers in order to offer higher aggregate bandwidth by using multiple paths simultaneously. Multipath TCP （MPTCP） has been proposed as a replacement for TCP in those topologies as it can efficiently offer improved throughput and better fairness. However, we have found that MPTCP has a problem in terms of incast collapse where the receiver suffers a drastic goodput drop when it simultaneously requests data over multiple servers. In this paper, we investigate why the goodput collapses even if MPTCP is able to actively relieve hot spots. In order to address the problem, we propose an equally-weighted congestion control algorithm for MPTCP, namely EW-MPTCP, without need for centralized control, additional infrastructure and a hardware upgrade. In our scheme, in addition to the coupled congestion control performed on each subflow of an MPTCP connection, we allow each subflow to perform an additional congestion control operation by weighting the congestion window in reverse proportion to the number of servers. The goal is to mitigate incast collapse by allowing multiple MPTCP subflows to compete fairly with a single-TCP flow at the shared bottleneck. The simulation results show that our solution mitigates the incast problem and noticeably improves goodput in data centers.     

A New Key Management Protocol to MANET

MANET （Mobile ad-hoc networks） are networks in which nodes are mobile and link connectivity might be changing all the time. The wireless and dis- tributed nature of MANET pose a great challenge to system security. Key management is an important and complex problem to the authentication and system security. The paper proposes a new method to the key management with high efficiency. Which,making use of the ideas of self-organization and local driven by intercross authenti-cation of CAs and threshold encryption. It＇s proved that the new method can reduce the communications delay and time delay in the key management process compared to other methods. So, it is a contribution to the field of key management in MANET.     

Action-Based Access Control Modelt

Access control is one of the powerful and generalized approaches for restricted resource access. The environmental state is introduced and the term “action” is defined based on roles, temporal states and environmental states. Actions can be used to capture security-relevant aspects of roles, environmental and temporal states in different information systems. Then, the action hierarchy, environmental hierarchy, temporal hierarchy and Action- based access control （ABAC） model are presented. ABAC is compared with the existing models and the result shows that the ABAC model can solve the problem of access control in information systems with mobile computation for its convenient and flexible designs. An application example of ABAC model is described at the end of the paper.     

On the Design and Temporal Petri Net Verification of Grid Commerce Architecture

The emergence of Grid Computing settings lays a solid foundation for designing and constructing a next generation E-commerce environment. This work presents a new E-commerce architecture based on a Grid Computing environment, and models and analyzes the architecture using Temporal Petri nets （TPNs）. It can make sufficiently use of the Grid resources to implement various electronic bargains between the geographically dispersed users. By means of its TPN model, some main temporal properties are represented and verified formally.     

Joint Optimization of Subchannel Reassignment and Power Adaptation for Multicarrier Cooperative Systems

An amplify-and-forward multicarrier cooperative system was proposed in this paper. The optimal resource-allocation problem was investigated in terms of improving data rate. An effective resource-allocation algorithm was proposed based on three techniques, adaptive modulation, subchannel reassignment design and transmit power adaptation. The designed subchannel reassignment not only increases the average data rate, but also raises the threshold of ＂water-filling＂ in optimizing power allocation that can further increase data rate. Since the power allocation is based on the designed subchannel reassignment, the complexity of the proposed algorithm is reduced greatly. Simulation results show that the proposed algorithm effectively increases the system＇s average data rate.     

An Effective Gated Scheduling with Pre-defined QoS Cross-layer Design for Wireless Networks

The proposed M-gated scheduling algorithm rules the server in wireless networks stays with a station for at most M times gated services. By the method of embedded Markov chain and probability generating function we developed a model with vacations and acquired the theoretical value of average queue length and packet delay. Like E-limlted scheduling algorithm, its performance is close to that of the optimal polling scheme, exhaustive scheduling, but the inherent unfairness problem for the latter is avoided. And it also does not require the server to know the status of stations, queues information. Compared with E-limited, M-gated has less jitter and is more robust. We then use the derived quality of service parameter as the basis for cross-layer design. Simulations results show the network is more stable and can keep the queue length and the packets delay under QoS level. When putting E- limited and M-gated scheduling in the same cross-layer design scheme, the latter has less overhead especially when the system is heavily loaded.     

A Novel Surface Treatment Method for Improving the Antenna System Performance of Mobile Phones with Stainless Steel Frame

A novel surface treatment method of plat-ing Cu＋PPS film/coating on a mobile phone＇s stainless steel frame for improving the antenna system efficiencies is proposed. The mobile phone was measured in free space, in a silicon cover, and in the hand and cover si- multaneously. It＇s found that with this surface treat-ment, the total efficiency of the antenna system can be improved in all the four cases respectively by 14.22%, 1.38%, 15.19% and 1.72% at 940MHz （GSM900：880- 960MHz）, 2.59%, 3.21%, 4.81% and 1.43% at 1720MHz （DCS：1710-1880MHz） and 6.34%, 2.85%, 9.83% and 2.32% at 2100 MHz （WCDMA：1920-2170MHz）. This low- cost surface treatment method is an important break- through to improve antenna system performance of mobile phones especially for those with a stainless steel frame, and suitable for mass production.     

Contour-Based Multi-Source Information Fusion for Motion Segmentation

A motion segmentation framework that effectively exploited the multiple sources of image information and fused these sources of the information synergisti-cally was proposed to serve the purpose of motion segmen- tation. A Markov process was formulated for motion seg- mentation in which two feature spaces were established to estimate the state transition Probability density function （PDF） and the initial state, respectively. An information fusion space was developed such that each motion struc-ture was described as a single distribution in this space. The proposed framework can naturally embed the evolution equations of the active contour methods into the seg-mentation to achieve contour-based segmentation results. Extensive empirical evaluations demonstrate the robust-ness and the promise of this framework.