？hrough-Wall Tracking of Human Movers Using Continuous-Wave Radar

An intelligent frequency fitting algorithm is presented for continuous-wave radar to track human movers through walls. With the proper fitting dimension, which is usually determined by the practical detection re- quirements, this technique can improve the localization ac- curacy and the tracking performance without introducing too much calculation burden, and more precisely identify different targets even in the frequency ambiguous areas. This technology can also help to match the estimation re- sults to their corresponding targets automatically, which is of great importance to certain urban sensing applications, such as specific target surveillance and tracking. To further improve the detection performance and better identify the weak targets in the presence of strong noise, CLEAN al- gorithm and adaptive filter technology are also involved. Experimental results are provided to illustrate the algo- rithm performance.     

Spaceborne/Airborne Hybrid Bistatic SAR Frequency Domain Imaging Processing Algorithm

An imaging algorithm mainly processed in the frequency domain for the hybrid spaceborne/airborne BSAR is presented. The key point of deriving the algo- rithm is the analytical evaluation of the system transfer function＇s 2-D spectrum. To overcome the difficulty of resolving analytical solution for the stationary phase point, the spectrum＇s phase is approximated by two-order Taylor expanding around the point, which is in the neighborhood of the system＇s corresponding stationary phase point and can be obtained analytically. Thus the approximated analytical spectrum is pretty close to the actual one. In the imaging algorithm, both range-dependent range cell migration and azimuth-dependent range cell migration are compensated in two steps： Scaled inverse Fourier trans- form （SIFT）, which can be realized through the chirp z-transform, and phase multiplication. The validity of the algorithm is demonstrated by simulation with both the point target and area target.     

An Improved Cochlear Implant Strategy Incorporating Frequency Modulation Information

Some currently popular strategies in Cochlear implants （CIs） fail to encode the temporal fine structure cues, which are crucial for speech perception in noise or melody appreciation of CI patients. We propose an improved strategy based on the CIS （Continuous interleaved sampling） model by introducing partial lowfrequency temporal fine structure cues or Frequency modulation （FM） information into the slowly varying temporal envelops. A psychoacoustic experiment was conducted to validate the improved strategy by measuring the Mandarin vowel, tone, consonant and sentence recognitions on normal hearing listeners. Experimental data show that the introduction of frequency modulation information can improve the CI performance greatly, especially for vowel and tone perception. Firstly even at the most severe noise condition the vowel perception can get nearly half intelligibility, and the tone recognition scores increased over 20% at various noise conditions. Secondly under moderate noise conditions or in quiet the fine structure cues also contribute significantly to the consonant and sentence recognitions. Finally, the proposed strategy has its own application values because it does not introduce too many high-frequency components into the model, which can not be perceived by deaf patients. .     

Joint Maximum-Likelihood Estimation of Frequency Offset and Channel in MIMO Systems

This paper addresses the problem of frequency offsets and channel gains estimation for a Multiinput multi-output （MIMO） system in fiat-fading channels. The general case where the frequency offsets are possibly different for each transmit antenna is considered, The Maximum-likelihood （ML） estimation of the carrier frequency offset for each transmit antenna in a MIMO system is investigated in this paper. The exact solution to this estimation problem turns out to be too complex as it involves a search over a multi-dimensional domain. However, by making use of the Particle swarm optimization （PSO） method, we efficiently solve the above complex problem. So based on the PSO theory, a novel joint estimation algorithm of frequency offsets and channel gains is proposed. Simulation results show that the proposed algorithm has better performance as compared with the correlation-based estimation algorithm and asymptotically achieves the Cramer-Rao lower bound （CRLB）, which provides a new idea to solve the problem of joint frequency offsets and channel gains estimation for MIMO systems.     

Quantized Phase Step Technique Based on Different Frequency Signals and Its Characteristics

Through theoretical analysis and experiments, we discovered the quantized phase step technique existing in two cyclical movements, and the variation law of phase difference between two different frequency signals. This discovery is a major breakthrough in the traditional phase processing for researching frequency signals or cyclical movements that widely exist in nature. It has realized direct phase comparison between any signals without frequency normalization. Experimental results show that the resolution with femtosecond （fs） can be easily achieved in frequency measurement, frequency standard comparison and control on the basis of the quantized phase step characteristics. This important discovery can be widely used in navigation positioning, space technique, communication, radar, astronomy, atomic frequency standard and so on.     

The Euclidean Distance Spectra of FDMA-CPM： Algorithms and Applications

The performance of multiuser Continuous phase modulation（CPM） over the additive white Gaussian noise channel with coherent maximum likelihood detection is considered. Algorithms are developed to calculate the Euclidean distance spectra employing tree-search and Astar algorithm. The complexity of proposed algorithms are further reduced using trellis minimization. The distance spectrum is then used to evaluate the performance of mul- tiuser CPM systems, which reveals that the performance of multiuser CPM can be significantly improved by using op- timized parameters. Both equally-powered and non-equally powered systems are considered. Numerical and simulated results confirm that the proposed algorithms can generate the distance spectra of all systems with lower complexity relative to previous methods and are particularly suited for multi user CPM systems.     

Directional Beamforming for High-Speed Railway Communications with Frequency Offset Precorrection

This paper considers a multi-antenna transmission strategy for high speed railway communica- tions. In order to achieve better performance than conven- tional space-frequency block coding schemes, we propose a directional beamforming strategy for the High-speed rail- way （HSR） communication by exploiting some characteris- tic of the railway system including predetermined moving tracks and real-time positioning information. Moreover, for alleviating the effect of Doppler shift due to the moving train, a frequency offset precorrection method is also incor- porated with direction beamforming. Theoretical Signal- to-noise ratio （SNR） gain of the proposed beamforming scheme over traditional HSR communication schemes is also derived for illustrating the performance enhancement. Numerical results verify the effectiveness of our proposed scheme even with some kind of imperfect position infor- mation available at the transmitter.     

Real-Time Hand Motion Parameter Estimation with Feature Point Detection Using Kinect

This paper presents a real-time Kinect- based hand pose estimation method. Different from model-based and appearance-based approaches, our approach retrieves continuous hand motion parameters in real time. First, the hand region is segmented from the depth image. Then, some specific feature points on the hand are located by the random forest classifier, and the relative displacements of these feature points are transformed to a rotation invariant feature vector. Finally, the system retrieves the hand joint parameters by applying the regression functions on the feature vectors. Experimental results are compared with the ground truth dataset obtained by a data glove to show the effectiveness of our approach. The effects of different distances and different rotation angles for the estimation accuracy are also evaluated.     

An Area Weighted Surface Sampling Method for 3D Model Retrieval

3D model feature extraction is a key step for geometric content based 3D model retrieval. A 3D model is usually expressed by patches and it has large amount of data. Pseudo-random sequential Monte Carlo surface sampling method is used to sample 3D model data. It has strong randomness. The sampling results are not uniform, which worsen the efficiency and precision of feature extraction. An area weighted surface sampling method for 3D Models is proposed. The larger area patches get the higher probability of sampling. The sampling points are evenly distributed in sampling space, which represent more accurate 3D model features. Experiments show that the proposed method needs less computing resources. Even when there are less sampling points, it can still keep high calculation accuracy and stability.     

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.     

Best Effort Spectrum Allocation Scheme for Femtocell Networks in Dense Deployment

In orthogonal frequency division multiple access（OFDMA） based femtocell networks,the co-tier interference among femto base stations（FBS） becomes important in multiuser and densely deployed environment.In order to mitigate the co-tier interference and enhance the system total throughput,this paper proposed a best effort spectrum allocation scheme based on the extension of graph theory.In the scheme,a controller was proposed to collect the channel state information（CSI）of all femtocell user equipments（FUEs） in a certain range.Then,the controller evaluated the signal-to-interference Ratio（SIR） of each FUE and determined the set of its interference neighbors.By calculating the received power matrix（RPM） among FUEs and building interference graph matrix（IGM）,different spectrum resource blocks（RBs） were assigned to the users with interference relation,while users without interference relation shared the same RBs,which could increase the spectrum efficiency.Simulation results show that the proposed algorithm can significantly improve the RB usage efficiency compared with the basic graph coloring theory,and more than 80% improvement can be acquired in dense deployment scenario.Besides,the throughput of both cell edge macro user equipments（MUEs） and cell edge FUEs is guaranteed on the premise of low interference.     

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.     

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.     

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.     

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.     

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.     

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.