In this paper, a stepped‐frequency spaceborne/airborne bistatic synthetic aperture radar (SFSA‐BiSAR) configuration is proposed to show to improve the range resolution of BiSAR. First, the geometry and the signal model of SFSA‐BiSAR are formulated, and then an analytical bistatic point target reference spectrum (BPTRS) is derived. Second, based on the developed BPTRS, two imaging algorithms called combination‐before‐focusing algorithm (CBFA) and combination‐after‐focusing algorithm (CAFA) are proposed to obtain BiSAR images with improved range resolution. CBFA uses sub‐band combination to obtain synthetic BPTRS, and then uses a new bistatic frequency‐domain algorithm (BFDA) to obtain the improved BiSAR image, whereas CAFA first uses the BFDA to focus all the sub‐pulses, and then uses sub‐image combination to obtain the improved BiSAR image. Both of the two algorithms can focus the SFSA‐BiSAR signal well and comparison simulations are performed to verify the authors' conclusion. Computation loads are also calculated to compare the two algorithms and show that CAFA uses less floating‐point operations than CBFA. Besides, some important parameters of SFSA‐BiSAR are analysed both theoretically and numerically to provide a reference for system design.

In general detection problems, targets or sources may be present at an unknown direction. This letter proposes a detection scheme for the randomly present case based on the MIMO radar transmit beamspace (TB) technique. An average likelihood ratio (ALR) detector for randomly present target detection is formulated firstly. Then two TB design strategies for different present cases are proposed accordingly to get optimal detectors. Numerical results demonstrate that a significant gain in detection can be achieved by these designs comparing to the conventional methods. Finally, theoretical and numerical analyses illustrate the influence of the transceiver parameters on detection performance.

In this letter, based on the narrow-band radar echoes, a 3-D imaging method for spinning space debris is proposed, which is named single-range 3-D imaging (SRTI). Not only the spinning nature but also the fact that the remainder phase trace after removal of spin contains the height information of the scattering center are taken advantage of in the SRTI. First, all the radar echoes in the observation time are divided into equal parts by the spinning period, and the traditional single-range 2-D imaging is made in each period. Then, the remainder phase trace of each scattering center is extracted via projection position separation, alignment, reconstruction, and spinning compensation. Finally, the height image of each scattering center is obtained from the remainder phase trace, which yields the 3-D image of the space debris. The simulation results for both the isolated point scattering centers and the continuous target have confirmed that the SRTI is able to reconstruct the 3-D shape of the spinning target effectively.

In this letter, we propose a novel track-to-track association (TTTA) algorithm based upon the reference topology (RET) feature, which is insensitive to sensor biases. A rigorous mathematical definition of RET is presented. The insensitivity of RET to sensor biases is analyzed theoretically. In order to construct the association cost matrix, we make use of the optimal subpattern assignment (OSPA) metric to measure the distance between two RETs. Simulation results demonstrate the advantages of the proposed algorithm.

A new method for estimating the rotational motion of a noncooperative target is presented by exploiting the 2-D space-variant characteristic of inverse synthetic aperture radar imaging. With a space-time analysis technique, the position variation of every extracted scattering center in both the range and cross-range directions can be utilized for rotation estimation. This method differs substantially from conventional methods that exploit high-order terms of the Doppler frequency, i.e., only the position variation in the cross-range direction. An iterative processing scheme is proposed to extract as many scattering centers as possible from the phase history of returned echoes. Experimental results with some measured airplane data demonstrate the effectiveness of the proposed method.

In next generation networks, mobile communication calls for service with higher quality, which brings new challenge for mobility management. Thereinto, utilization and improvement of mobility prediction helps for preserving resource and providing better performance. So this paper aims to propose a theoretical and factual method to perform mobility prediction in cellular network. By analyzing the demand and character of this kind of personal mobility prediction in large spacial and temporal scale, it is concluded that Hidden Markov Model fits for system modeling. However, classical HMM algorithm will meet with numerical calculation problem when adopted to practical communication system. An improved algorithm is put forward to overcome possible calculating defects. Three different scenarios are set to testify HMM's efficiency and accuracy, using factual measurement data in cellular network.

Understanding of urban mobility dynamics benefits both aggregate human mobility in wireless communications, and the planning and provision of urban facilities and services. Due to the high penetration of cell phones, the cellular networks provide information for urban dynamics with large spatial extent and continuous temporal coverage. In this paper, a novel approach is proposed to explore the space-time structure of urban dynamics, based on the original data collected by cellular networks in a southern city of China, recording population distribution by dividing the city into thousands of pixels. By applying principal component analysis, the intrinsic dimensionality is revealed. The structure of all the pixel population variations could be well captured by a small set of eigen pixel population variations. According to the classification of eigen pixel population variations, each pixel population variation can be decomposed into three constitutions: deterministic trends, short-lived spikes, and noise. Moreover, the most significant eigen pixel population variations are utilized in the applications of forecasting and anomaly detection.

Environmental surveillance applications usually require a long living cycle of sensor nodes, especially when they are powered by non-charged batteries. Inspired by cellular automata, we propose a non-cluster based topology control method to prolong the lifetime of wireless sensor networks. Differing from the traditional cluster-based methods, our approaches lead a special way to maintain longer system lifetime by sacrificing a small proportion of network coverage and connectivity degrees. The demonstration contains both theoretical simulation and system-level experiment, which will be instructive for future study.

We consider the range-based localization with highly insufficient inter-node distance measurements in Wireless Sensor Networks (WSNs). With an error model established, a novel distributed probabilistic localization approach which exploits the network constraints through statistical inference on missing distances is proposed. The advantage of the new approach over traditional methods is proved analytically and further confirmed by extensive simulations.

This paper studies Ranking-Based localization method, which, as a special case of common Range-Based localization methods, statistically estimates node positions using the ranking-order constraints rather than the actual values of network measurements. Through extensive empirical evaluation, the advantages of Ranking-Based approach over traditional Range-Based approaches under extreme network conditions are verified. Ranking-Based approach turns out to be more robust to measurement insufficiency and more immune to measurement noise.

A novel adaptive resource-based probabilistic search algorithm (ARPS) for P2P networks is proposed in this paper. ARPS introduces weighted probabilistic forwarding for query messages according to the node degree distribution and the popularity of the resource being searched. A mechanism is introduced to estimate the popularity and adjust the forwarding probability accordingly such that a tradeoff between search performance and cost can be made. Using computer simulations, we compare the performance of ARPS with several other search algorithms. It is shown that ARPS performs well under various P2P scenarios. ARPS guarantees a success rate above a certain level under all circumstances, and enjoys high and popularity-invariant search success rate.

An energy model for wireless sensor networks based on the cooperative MIMO (multiple-in-multiple-out) technique is proposed, taking into consideration of both the transmission and data aggregation energy. Based on the model, two cooperative wireless sensor network schemes, namely, MIMO approach and SISO (single-in-single-out) approach are compared. It is shown that the overall energy consumption in the systems is related to not only the transmission range but also the correlation among the raw sensor data, and can be solved as a nonlinear programming problem. Furthermore, a critical value above which MIMO approach outperforms SISO approach is analyzed. Simulation results show that jointly considering both data aggregation and cooperative MIMO techniques further reduce the total energy consumption and thus prolong the network lifetime.

This paper addresses the issue of transmission scheduling in multi-channel wireless ad hoc networks. The authors propose a multi-channel time division multiple access (TDMA) scheduling based on edge coloring and algebraic coding theory, called CC-TDMA. The authors categorized the conflicts suffered by wireless links into two types: explicit conflicts and implicit conflicts, and CC-TDMA utilize two different strategies to deal with them. Explicit conflicts are avoided completely by a simple distributed edge-coloring algorithm mu-M, and implicit conflicts are minimized by using coding theory to assign channels to links. The authors evaluate CC-TDMA analytically and numerically, and find that it exhibits a better performance than previous work in terms of throughput and delay.

Data association is one of the most important problems in multiple-sensor multiple-target tracking systems. A novel approach for biased-data association based on patterns extracted from topologies of measurements is presented in this paper. The introduction of patterns reveals a new paradigm for exploiting redundant spatial information in association. Fuzzy pattern recognition method has been applied to analyze the similarity of target patterns, and the criterion of association can be set up accordingly. By virtue of the inherent character of patterns, the proposed pattern-based association algorithm is robust to large registration errors between systems. Furthermore, the association results can provide feedback information for sensor registration. Simulation results show that the proposed algorithm is effective and feasible in solving association problems under the conditions of sensor bias

The problem of traffic congestion in complex networks is studied. Two kinds of complex network structures, namely random graphs and scale-free networks, are considered. In terms of the structure of connection, random graphs are homogeneous networks whereas the scale-free networks are heterogeneous networks. For both types of networks, we introduce an additional scale-free feature in the load generation process such that a small number of nodes are more heavily loaded than others. A traffic model similar to the routing algorithm in computer networks is used in our simulation study. We show how the network structures and parameters influence the traffic congestion status.

A novel receiver-initiated soft-state probabilistic multicasting protocol (RISP) for mobile ad hoc network is proposed in this paper. RISP introduces probabilistic forwarding and soft-state for making relay decisions. Multicast members periodically initiate control packets, through which intermediate nodes adjust the forwarding probability. With a probability decay function (soft-state), routes traversed by more control packets are reinforced, while the less utilized paths are gradually relinquished. In this way, RISP can adapt to node mobility; at low mobility, RISP performs similar to a tree-based protocol; at high mobility, it produces a multicast mesh in the network. Simulation results show RISP has lower delivery redundancy than mesh-based protocols, while achieving higher delivery ratio. Further, the control overhead is lower than other compared protocols.

This paper presents a proxy-based framework for Internet access through GPRS/UMTS networks. The proxy, deployed at the network boundary, is able to employ some scheduling strategies to assist the wireless network in charge of incoming traffic according to system capacity and user demand. In particular, we investigate the system performance on flow level and consider the impact of some user behaviors. The objective is to maximize utilization of the network by exploiting the property of delay tolerance, and to improve user-level performance such as response time. In addition, the proxy splits TCP connections into two halves, the wired and wireless sides. The TCP stacks on the wireless-facing side of the proxy can be modified to enhance the performance over the wireless link, while keeping compatibility with the conventional TCP implementations on mobile hosts. The effectiveness of this approach is illustrated by analysis and simulations.

Multicasting protocols deliver data packets from a source node to multiple receivers, and serve a very important function in mobile ad-hoc networks (MANETs). In this paper, a novel receiver-initiated soft-state probabilistic multicasting protocol (RISP) for MANETs is proposed. RISP is inspired by the ant colony's route-seeking mechanism, in which an individual ant chooses the optimal path to its destination through cooperation with others in a totally distributed manner. Imitating the behaviour of ants in nature, RISP introduces probabilistic forwarding and soft-state for making relay decisions that are automatically adaptive to node mobility in MANETs. Compared with other protocols, we show by computer simulations that RISP has lower delivery redundancy, while achieving higher delivery ratio at all mobility scenarios. Furthermore, RISP has lower control overhead.

Discrete wavelet multicarrier transceiver (DWMT) system, which can be viewed as a kind of OFDM, has many advantages because it uses wavelet as its base functions. In this paper we present a new sub-carrier frequency synchronize method for DWMT systems with little assistant information. The essential ideal of this arithmetic is: when an orthogonal multicarrier system is of perfect frequency synchronize, the demodulated signals of different sub-carriers are independent of each other. Whereas when frequency offset exists, every demodulated signal is constructed by several modulated signals projects on the demodulating frequency. So the adjacent demodulated signals consist of the element of the same modulated signal, and these demodulated signals are correlated with each other. The degree what they correlated with each other is a function of the sub-carrier relative frequency offset. Since that little assistant information is used in this algorithm, the spectrum efficiency can be largely increased. Simulation result show that if the number of the sub-carrier of the DWMT system is bigger than 1000, the relative frequency offset can be limited in 2%.

A novel predictor for network traffic, the wavelet domain recursive least-squares (WDRLS) predictor is discussed. Empirical studies have shown that network traffic possesses diverse statistical properties and exhibits a complex correlation structure characterized by short-range dependence (SRD) and long-range dependence (LRD). A challenge in predicting network traffic is how to exploit such a complex correlation structure with both high accuracy and computational efficiency. In the proposed WDRLS predictor, we use the wavelet transform to tackle these issues. Specifically, we predict the wavelet coefficients and solve the prediction of network traffic through a reverse wavelet transform. Our approach is based on the discovery that, although the network traffic has both SRD and LRD correlation structures, the corresponding wavelet coefficients are all SRD. We further assume that the SRD wavelet coefficients can be well approximated by a linear correlation structure for prediction. A least-squares method is adopted to make predictions in the wavelet domain. An important feature about the WDRLS predictor is that it can make an on-line prediction of network traffic. This is made possible by implementing the least-squares method in a recursive way. The performance of WDRLS is investigated with real network traffic. Simulation results demonstrate the feasibility of using the linear correlation structure to predict SRD wavelet coefficients and show that WDRLS can achieve high prediction accuracy when working with real LAN or WAN traffic.

As an effective mechanism acting on the intermediate nodes to support end-to-end congestion control, active queue management (AQM) takes a trade-off between link utilization and delay experienced by data packets. Most of the existing AQM algorithms are heuristic, and a lack systematic and theoretical design and analysis approach. From the viewpoint of control theory, it is rational to regard AQM as a typical regulating system. Although the PI controller for AQM outperforms the RED algorithm, the mismatches in the simplified TCP flow model inevitably degrade the performance of a controller designed with classical control theory. In this paper, a robust SMVS controller for AQM is put forward based on sliding mode variable structure control (SMVS), its superiority is insensitive to the noise and variance of the parameters, thus it very suitable to a time-varying network system. The principle and guidelines on design of a SMVS controller are presented in detail. The integrated performance is evaluated using ns simulations. The results show that SMVS is very responsive and robust against disturbances. At the same time, a complete comparison between the SMVS controller and PI controller is made. The conclusion is that both the transient and steady performance of the SMVS controller is superior to that of the PI controller, thus the SMVS controller is in favor of the achievement of AQM objectives.

Wireless channels are error-prone and susceptible to several kinds of interference from different time scales, causing difficulties in the support of real-time multimedia services. This paper investigates the resource optimization and scheduling of wireless networks through a time-scale decomposition approach. We decompose the dynamics of time-varying wireless channel conditions into random processes in two different time scales and deal with the two time scales by two different algorithms: the resource optimizer optimizes the sum of utilities in the slowly changing time scale, and the slot scheduler exploits the efficiency in the highly variable time scale. Our scheme can obtain high system utilization and provide a minimum service guarantee simultaneously. Simulation results show that our scheme can improve substantially the performance and efficiency.

Wireless channels are error-prone and susceptible to several kinds of interference from different time scales. This paper investigates the resource optimization and scheduling of wireless networks through a time-scale decomposition approach. We decompose the dynamics of time-varying wireless channel conditions into two random processes in different time scales: a slow time-varying process in a larger time scale, called frame-scale, and a stationary random process with high variation in a smaller time scale, called slot-scale. This results in two different algorithms dealing with each time-scale: the resource optimizer optimize the sum of utilities in the slowly changed time scale, and the slot scheduler exploits the efficiency in the highly variable time scale. Our scheme can obtain a high utilization while providing service guarantee. Simulation results show our scheme can improve the performance and efficiency substantially.

ATM networks oriented connections provide pure QoS (quality of service) for diversified services through a series of traffic management mechanisms, the ABR (available bit rate) flow control is especially important among these approaches. In the binary flow control scheme, the cell rate and queue length may oscillate with great magnitude to reduce link utilization, so that the EFCI (explicit forward congestion indication) algorithm is regard as ineffective, however its simplicity is attractive to high performance switch design. In this paper, the EFCI algorithm is analyzed based on classical control theory. It is found that the nonlinear hysteresis determines the congestion, and is the dominant reason that causes the oscillation. Then, a probability congestion detection approach, called p-EFCI is put forward. Numerical results show that the improved algorithm deeply constrains the oscillation magnitude, and the queue length is controlled in limited scope to guarantee cell zero loss.

In this paper, we focus on understanding the binomial congestion control algorithms (Bansal et al., 2001) and can generalize TCP-style additive-increase by increasing inversely proportional to a power k of the current window (for TCP, k=0) and generalize TCP-style multiplicative-decrease by decreasing proportional to a power l of the current window (for TCP, l=1). We discuss their global fairness and stability. We prove that such congestion control algorithms can achieve (p, k+l+1)-proportional fairness globally no matter what the network topology is and how many users there are. We also study their dynamical behavior through a control theoretical approach. The smoothness of the congestion control results in a less stable system and slower convergence to fair bandwidth allocation. The modeling and discussion in this paper are quite general and can be easily applied to equation-based TCP-friendly congestion control schemes, another category of TCP-friendly transport protocols.