Showing papers in "IEEE Transactions on Vehicular Technology in 2008"

Spatial Modulation

Abstract: Spatial modulation (SM) is a recently developed transmission technique that uses multiple antennas. The basic idea is to map a block of information bits to two information carrying units: 1) a symbol that was chosen from a constellation diagram and 2) a unique transmit antenna number that was chosen from a set of transmit antennas. The use of the transmit antenna number as an information-bearing unit increases the overall spectral efficiency by the base-two logarithm of the number of transmit antennas. At the receiver, a maximum receive ratio combining algorithm is used to retrieve the transmitted block of information bits. Here, we apply SM to orthogonal frequency division multiplexing (OFDM) transmission. We develop an analytical approach for symbol error ratio (SER) analysis of the SM algorithm in independent identically distributed (i.i.d.) Rayleigh channels. The analytical and simulation results closely match. The performance and the receiver complexity of the SM-OFDM technique are compared to those of the vertical Bell Labs layered space-time (V-BLAST-OFDM) and Alamouti-OFDM algorithms. V-BLAST uses minimum mean square error (MMSE) detection with ordered successive interference cancellation. The combined effect of spatial correlation, mutual antenna coupling, and Rician fading on both coded and uncoded systems are presented. It is shown that, for the same spectral efficiency, SM results in a reduction of around 90% in receiver complexity as compared to V-BLAST and nearly the same receiver complexity as Alamouti. In addition, we show that SM achieves better performance in all studied channel conditions, as compared with other techniques. It is also shown to efficiently work for any configuration of transmit and receive antennas, even for the case of fewer receive antennas than transmit antennas.

VADD: Vehicle-Assisted Data Delivery in Vehicular Ad Hoc Networks

Abstract: Multihop data delivery through vehicular ad hoc networks is complicated by the fact that vehicular networks are highly mobile and frequently disconnected. To address this issue, we adopt the idea of carry and forward, where a moving vehicle carries a packet until a new vehicle moves into its vicinity and forwards the packet. Being different from existing carry and forward solutions, we make use of predictable vehicle mobility, which is limited by traffic pattern and road layout. Based on the existing traffic pattern, a vehicle can find the next road to forward the packet to reduce the delay. We propose several vehicle-assisted data delivery (VADD) protocols to forward the packet to the best road with the lowest data-delivery delay. Experimental results show that the proposed VADD protocols outperform existing solutions in terms of packet-delivery ratio, data packet delay, and protocol overhead. Among the proposed VADD protocols, the hybrid probe (H-VADD) protocol has a much better performance.

An MDP-Based Vertical Handoff Decision Algorithm for Heterogeneous Wireless Networks

Abstract: The architecture for the Beyond 3rd Generation (B3G) or 4th Generation (4G) wireless networks aims at integrating various heterogeneous wireless access networks. One of the major design issues is the support of vertical handoff. Vertical handoff occurs when a mobile terminal switches from one network to another (e.g., from wireless local area network to code-division multiple-access 1x radio transmission technology). The objective of this paper is to determine the conditions under which vertical handoff should be performed. The problem is formulated as a Markov decision process with the objective of maximizing the total expected reward per connection. The network resources that are utilized by the connection are captured by a link reward function. A signaling cost is used to model the signaling and processing load incurred on the network when vertical handoff is performed. The value iteration algorithm is used to compute a stationary deterministic policy. For performance evaluation, voice and data applications are considered. The numerical results show that our proposed scheme performs better than other vertical handoff decision algorithms, namely, simple additive weighting, the technique for order preference by similarity to ideal solution, and Grey relational analysis.

Design and New Control of DC/DC Converters to Share Energy Between Supercapacitors and Batteries in Hybrid Vehicles

Abstract: In this paper, the authors propose the supercapacitor integration strategy in a hybrid series vehicle. The designed vehicle is an experimental test bench developed at the laboratory of electrical engineering and systems (L2ES) in collaboration with the research in electrical engineering and electronics center of Belfort (CREEBEL). This test bench currently has two diesel motors (each connected to one alternator) and lead-acid batteries with a voltage rating of 540 V and a fluctuation margin between +12% and -20% of the rated voltage. The alternators are connected to the dc link by rectifiers. An original strategy of the supercapacitor integration in this vehicle with their control is presented to find a better compromise between the dimensions of the embarked devices, the share energy efficiency, the dynamics of the supply, and the electric power storage. The supercapacitor packs are made up of two modules of 108 cells each and present a maximum voltage of 270 V. The main objective is to provide a peak power of 216 kW over 20 s from supercapacitors to the dc link. Various topologies of dc/dc converters are presented with effective methodologies of electric power management in the hybrid vehicle.

Trip-Based Optimal Power Management of Plug-in Hybrid Electric Vehicles

Abstract: Hybrid electric vehicles (HEVs) have demonstrated the capability to improve fuel economy and emissions. The plug-in HEV (PHEV), utilizing more battery power, has become a more attractive upgrade of the HEV. The charge-depletion mode is more appropriate for the power management of PHEVs, i.e., the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the trip destination. Trip information has so far been considered as future information for vehicle operation and is thus not available a priori. This situation can be changed by the recent advancement in intelligent transportation systems (ITSs) based on the use of on-board global positioning systems (GPSs), geographical information systems (GISs), and advanced traffic flow modeling techniques. In this paper, a new approach to optimal power management of PHEVs in the charge-depletion mode is proposed with driving cycle modeling based on the historic traffic information. A dynamic programming (DP) algorithm is applied to reinforce the charge-depletion control such that the SOC drops to a specific terminal value at the end of the driving cycle. The vehicle model was based on a hybrid electric sport utility vehicle (SUV). Only fuel consumption is considered for the current stage of the study. A simulation study was conducted for several standard driving cycles and two trip models using the proposed method, and the results showed significant improvement in fuel economy compared with a rule-based control and a depletion sustenance control for most cases. Furthermore, the results showed much better consistency in fuel economy compared with rule-based and depletion sustenance control.

A Comparative Study of Fuel-Cell–Battery, Fuel-Cell–Ultracapacitor, and Fuel-Cell–Battery–Ultracapacitor Vehicles

Abstract: Although many researchers have investigated the use of different powertrain topologies, component sizes, and control strategies in fuel-cell vehicles, a detailed parametric study of the vehicle types must be conducted before a fair comparison of fuel-cell vehicle types can be performed. This paper compares the near-optimal configurations for three topologies of vehicles: fuel-cell-battery, fuel-cell-ultracapacitor, and fuel-cell-battery-ultracapacitor. The objective function includes performance, fuel economy, and powertrain cost. The vehicle models, including detailed dc/dc converter models, are programmed in Matlab/Simulink for the customized parametric study. A controller variable for each vehicle type is varied in the optimization.

Analytical Model for Connectivity in Vehicular Ad Hoc Networks

Abstract: We investigate connectivity in the ad hoc network formed between vehicles that move on a typical highway. We use a common model in vehicular traffic theory in which a fixed point on the highway sees cars passing it that are separated by times with an exponentially distributed duration. We obtain the distribution of the distances between the cars, which allows us to use techniques from queuing theory to study connectivity. We obtain the Laplace transform of the probability distribution of the connectivity distance, explicit expressions for the expected connectivity distance, and the probability distribution and expectation of the number of cars in a platoon. Then, we conduct extensive simulation studies to evaluate the obtained results. The analytical model that we present is able to describe the effects of various system parameters, including road traffic parameters (i.e., speed distribution and traffic flow) and the transmission range of vehicles, on the connectivity. To more precisely study the effect of speed on connectivity, we provide bounds obtained using stochastic ordering techniques. Our approach is based on the work of Miorandi and Altman, which transformed the problem of connectivity distance distribution into that of the distribution of the busy period of an equivalent infinite server queue. We use our analytical results, along with common road traffic statistical data, to understand connectivity in vehicular ad hoc networks.

Silent Positioning in Underwater Acoustic Sensor Networks

Abstract: In this paper, we present a silent positioning scheme termed UPS for underwater acoustic sensor networks. UPS relies on the time difference of arrivals locally measured at a sensor to detect range differences from the sensor to four anchor nodes. These range differences are averaged over multiple beacon intervals before they are combined to estimate the 3-D sensor location through trilateration. UPS requires no time synchronization and provides location privacy at underwater vehicles/sensors whose locations need to be determined. To study the performance of UPS, we model the underwater acoustic channel as a modified ultrawideband Saleh-Valenzuela model: The arrival of each path cluster and the paths within each cluster follow double Poisson distributions, and the multipath channel gain follows a Rician distribution. Based on this channel model, we perform both theoretical analysis and simulation study on the position error of UPS under acoustic fading channels. The obtained results indicate that UPS is an effective scheme for underwater vehicle/sensor self-positioning.

Circularity-Based I/Q Imbalance Compensation in Wideband Direct-Conversion Receivers

Abstract: Communication receivers that utilize I/Q downconversion are troubled by amplitude and phase mismatches between the analog I and Q branches. These mismatches are unavoidable in practice and reduce the obtainable image frequency attenuation to the 20-40-dB range in practical receivers. In wideband multichannel receivers, where the overall bandwidths are in the range of several megahertz and the incoming carriers located at each other's mirror frequencies have a high dynamic range, the image attenuation of the analog front-end (FE) alone is clearly insufficient. In this paper, two novel blind low-complexity I/Q imbalance compensation techniques are proposed and analyzed to digitally enhance the analog FE image attenuation in wideband direct-conversion receivers. The proposed algorithms are grounded on the concept of circular or proper complex random signals, and they are, by design, able to handle the often overlooked yet increasingly important case of frequency-dependent I/Q mismatches. The first technique is an iterative one, stemming from adaptive filtering principles, whereas the second one is a moment-estimation-based block method. The performance of the algorithms is evaluated through computer simulations, as well as real-world laboratory signal measurement examples in practical multicarrier receiver cases. Based on the obtained results, the proposed compensation techniques can provide very good compensation performance with low computational resources and are robust in the face of different imbalance levels and dynamics of the received signals, as well as many other crucial practical aspects such as the effects of the communications channel and carrier synchronization.

An Efficient Message Authentication Scheme for Vehicular Communications

Abstract: In this paper, we introduce a novel roadside unit (RSU)-aided message authentication scheme named RAISE, which makes RSUs responsible for verifying the authenticity of messages sent from vehicles and for notifying the results back to vehicles. In addition, RAISE adopts the k- anonymity property for preserving user privacy, where a message cannot be associated with a common vehicle. In the case of the absence of an RSU, we further propose a supplementary scheme, where vehicles would cooperatively work to probabilistically verify only a small percentage of these message signatures based on their own computing capacity. Extensive simulations are conducted to validate the proposed scheme. It is demonstrated that RAISE yields a much better performance than previously reported counterparts in terms of message loss ratio (LR) and delay.

Online Energy Management for Hybrid Electric Vehicles

Abstract: Hybrid electric vehicles (HEVs) are equipped with multiple power sources for improving the efficiency and performance of their power supply system. An energy management (EM) strategy is needed to optimize the internal power flows and satisfy the driver's power demand. To achieve maximum fuel profits from EM, many solution methods have been presented. Optimal solution methods are typically not feasible in an online application due to their computational demand and their need to have a priori knowledge about future vehicle power demand. In this paper, an online EM strategy is presented with the ability to mimic the optimal solution but without using a priori road information. Rather than solving a mathematical optimization problem, the methodology concentrates on a physical explanation about when to produce, consume, and store electric power. This immediately reveals the vehicle characteristics that are important for EM. It is shown that this concept applies to many existing HEVs as well as possible future vehicle configurations. Since the method only focuses on typical vehicle characteristics, the underlying algorithm requires minor computational effort and can be executed in real time. Clear directions for online implementation are given in this paper. A parallel HEV with a 5-kW integrated starter/generator (ISG) is selected to demonstrate the performance of the EM strategy. Simulation results indicate that the proposed EM strategy exhibits similar behavior as an optimal solution obtained from dynamic programming. Profits in fuel economy primarily arise from engine stop/start and energy obtained during regenerative braking. This latter energy is preferably used for pure electric propulsion where the internal combustion engine is switched off.

Battery Management System Based on Battery Nonlinear Dynamics Modeling

Abstract: This paper presents a method of determining electromotive force and battery internal resistance as time functions, which are depicted as functions of state of charge (SOC) because . The model is based on battery discharge and charge characteristics under different constant currents that are tested by a laboratory experiment. This paper further presents the method of determining the battery SOC according to a battery modeling result. The influence of temperature on battery performance is analyzed according to laboratory-tested data, and the theoretical background for calculating the SOC is obtained. The algorithm of battery SOC indication is depicted in detail. The algorithm of the battery SOC ldquoonlinerdquo indication considering the influence of temperature can be easily used in practice by a microprocessor. An NiMH battery is used in this paper to depict the modeling method. In fact, the method can also be used for different types of contemporary batteries, as well as Li-ion batteries, if the required test data are available.

Call Admission Control Optimization in WiMAX Networks

Abstract: Worldwide interoperability for microwave access (WiMAX) is a promising technology for last-mile Internet access, particularly in the areas where wired infrastructures are not available. In a WiMAX network, call admission control (CAC) is deployed to effectively control different traffic loads and prevent the network from being overloaded. In this paper, we propose a framework of a 2-D CAC to accommodate various features of WiMAX networks. Specifically, we decompose the 2-D uplink and downlink WiMAX CAC problem into two independent 1-D CAC problems and formulate the 1-D CAC optimization, in which the demands of service providers and subscribers are jointly taken into account. To solve the optimization problem, we develop a utility- and fairness-constrained optimal revenue policy, as well as its corresponding approximation algorithm. Simulation results are presented to demonstrate the effectiveness of the proposed WiMAX CAC approach.

Energy-Efficient Cooperative Communication in a Clustered Wireless Sensor Network

Abstract: In this paper, we consider a clustered wireless sensor network where sensors within each cluster relay data packets to nearby clusters using cooperative communications. We propose a cooperative transmission scheme based on distributed space-time block coding and conduct a systematic analysis on the resulting energy consumption. Compared with existing work, our distinctions are twofold: (1) Only sensors that can correctly decode received packets participate in the cooperative transmission, where the number of cooperating nodes depends on both channel and noise realizations; and (2) we use packet-error-rate-based analysis rather than symbol-error-rate-based analysis. This is more realistic since error detection is usually done at the packet level via, e.g., cyclic-redundancy-check codes. Based on the analysis, we further minimize the overall energy consumption by power allocation between the intracluster and intercluster transmissions. With numerical methods, we investigate how energy consumption is affected by the transmit power allocation, the total number of sensors in a cluster, the end-to-end packet error rate requirement, and the relative magnitudes between the intracluster and intercluster distances. Comparisons with direct (noncooperative) transmission schemes demonstrate the significant energy-saving advantage of the proposed cooperative scheme.

A Performance Modeling of Connectivity in Vehicular Ad Hoc Networks

Abstract: In this paper, we study the statistical properties of the connectivity of vehicular ad hoc networks (VANETs) with user mobility. It is assumed that the nodes travel along a multilane highway that allows vehicles to pass each other. The nodes arrive at the highway through one of the traffic entry points according to a Poisson process and then travel in the same direction according to a user mobility model until they reach their exit points. The nodes on the highway may be able to communicate with each other. We derive the probability distribution of the node population size on the highway and the node's location distribution. Then, we determine the mean cluster size and the probability that the nodes will form a single cluster. The analysis of this paper also applies to any path in a network of highways, as well as to two-way traffic. The numerical results show the significance of mobility on the connectivity of VANETs. We also present simulation results that confirm the accuracy of the analysis. The results of this paper may be used to study the routing algorithms, throughput, or delay in VANETs.

Cross-Layer-Based Adaptive Vertical Handoff With Predictive RSS in Heterogeneous Wireless Networks

Abstract: A heterogeneous wireless network consists of various wireless networks [e.g., Worldwide Interoperability for Microwave Access (WiMAX) and Wireless Fidelity (WiFi)] and cellular communications [e.g., beyond the third generation (B3G) and the fourth generation (4G)]. Vertical handoff is an important mechanism for achieving continuous seamless transmissions in these networks. In contrast to horizontal handoff, vertical handoff considers not only the received signal strength (RSS) but also the service-class mapping between handoff-in and handoff-out networks. Most previous works have adopted the RSS-based mechanism to determine handoff thresholds, which causes a serious ping-pong effect that increases unnecessary handoff. Although integrating the RSS-based mechanism with a hysteresis method reduces the unnecessary handoff, it suffers from high dropping [i.e., high Sum of Weighted Grade of Service (SWGoS)] and low utilization. Therefore, this paper proposes a cross-layer-based adaptive vertical handoff algorithm with predictive RSS to reduce the unnecessary handoff while significantly increasing utilization and decreasing connection dropping. The proposed approach determines the optimal target network in two phases, i.e., polynomial regression RSS prediction and Markov decision process analysis. Furthermore, fast changes in bandwidth caused by vertical handoff result in inaccurate Transmission Control Protocol (TCP) congestion control and, thus, reduce the TCP goodput. The cross-layer scheme provides a TCP receiver to reply to the TCP sender with the wireless network's protocol type. By using the cross-layer information, the TCP sender can accurately predict the available bandwidth and increase the network goodput. Numerical results indicate that the proposed cross-layer-based approach outperforms the other approaches in the number of vertical handoffs and SWGoS while yielding competitive utilization. In addition, the cross-layer scheme cooperates with existing TCP algorithms to increase goodput by up to 18%.

A Cooperation Strategy Based on Nash Bargaining Solution in Cooperative Relay Networks

Abstract: This paper proposes a cooperation strategy among rational nodes in a wireless cooperative relaying network as an effort to solve two basic problems, i.e., when to cooperate and how to cooperate. First, a symmetric system model comprising two users and an access point (AP) is presented. In this model, each user plays an equal role and acts as a source as well as a potential relay and has the right to decide the amount of bandwidth it should contribute for cooperation. Second, referring to the cooperative game theory, the above problems are formulated as a two-person bargaining problem. Then, a cooperation bandwidth allocation strategy based on the Nash bargaining solution is proposed, in which if a derived condition is satisfied, users will cooperatively work, and each will share a certain fraction of its bandwidth for relaying; otherwise, they will independently work. Simulation results demonstrate that when cooperation takes place, users benefit from the proposed strategy in terms of utility, and those with longer distance to the AP should spend more bandwidth to cooperate with others.

License Plate Localization and Character Segmentation With Feedback Self-Learning and Hybrid Binarization Techniques

Abstract: License plate localization (LPL) and character segmentation (CS) play key roles in the license plate (LP) recognition system. In this paper, we dedicate ourselves to these two issues. In LPL, histogram equalization is employed to solve the low-contrast and dynamic-range problems; the texture properties, e.g., aspect ratio, and color similarity are used to locate the LP; and the Hough transform is adopted to correct the rotation problem. In CS, the hybrid binarization technique is proposed to effectively segment the characters in the dirt LP. The feedback self-learning procedure is also employed to adjust the parameters in the system. As documented in the experiments, good localization and segmentation results are achieved with the proposed algorithms.

Vehicle Stability Enhancement of Four-Wheel-Drive Hybrid Electric Vehicle Using Rear Motor Control

Abstract: A vehicle stability enhancement control algorithm for a four-wheel-drive hybrid electric vehicle (HEV) is proposed using rear motor driving, regenerative braking control, and electrohydraulic brake (EHB) control. A fuzzy-rule-based control algorithm is proposed, which generates the direct yaw moment to compensate for the errors of the sideslip angle and yaw rate. Performance of the vehicle stability control algorithm is evaluated using ADAMS and MATLAB Simulink cosimulations. HEV chassis elements such as the tires, suspension system, and steering system are modeled to describe the vehicle's dynamic behavior in more detail using ADAMS, whereas HEV power train elements such as the engine, motor, battery, and transmission are modeled using MATLAB Simulink with the control algorithm. It is found from the simulation results that the driving and regenerative braking at the rear motor is able to provide improved stability. In addition, better performance can be achieved by applying the driving and regenerative braking control, as well as EHB control.

Space-Time Correlated Mobile-to-Mobile Channels: Modelling and Simulation

Abstract: A single- and double-bounced two-ring parametric reference model is proposed for multiple-input multiple-output (MIMO) mobile-to-mobile (M-to-M) Ricean fading channels. From this model, a closed-form joint space-time correlation function and a space-Doppler power spectrum are derived for a two-dimensional (2D) non-isotropic scattering environment. Also, space-time correlation functions for the in-phase and quadrature components of the complex faded envelope are derived, assuming a 2D isotropic scattering environment. Finally, two new sum-of-sinusoids based simulation models for MIMO M-to-M Ricean fading channels are proposed. The statistics of the simulation models are verified by simulation. The results show that the simulation models are a good approximation of the reference model and that they outperform existing simulation models.

Extending a Fixed-Complexity Sphere Decoder to Obtain Likelihood Information for Turbo-MIMO Systems

Abstract: A list extension for a fixed-complexity sphere decoder (FSD) to perform iterative detection and decoding in turbo-multiple input-multiple output (MIMO) systems is proposed in this paper. The algorithm obtains a list of candidates that can be used to calculate likelihood information about the transmitted bits required by the outer decoder. The list FSD (LFSD) overcomes the two main problems of the list sphere decoder (LSD), namely, its variable complexity and the sequential nature of its tree search. It combines a search through a very small subset of the complete transmit constellation and a specific channel matrix ordering to approximate the soft- quality of the list of candidates obtained by the LSD. A simple method is proposed to generate that subset, extending the subset searched by the original FSD. Simulation results show that the LFSD can be used to approach the performance of the LSD while having a lower and fixed complexity, making the algorithm suitable for hardware implementation.

Joint Shadowing Process in Urban Peer-to-Peer Radio Channels

Abstract: For multihop and ad hoc networks, a conventional 1-D channel model cannot capture the spatial correlation of the shadowing processes. This paper investigates the joint spatial correlation property of the shadowing process for peer-to-peer (P2P) radio links in urban environments. When a fixed base station is assumed, statistical analysis reveals that the shadowing process is mainly a result of spatial displacement at the mobile station (MS). Furthermore, the joint correlation property of the MS-MS channel shows that MS displacements at each end of the P2P link have an independent and equal effect on the correlation coefficient. A sum-of-sinusoids simulation model is proposed to generate the joint correlation shadowing process for urban P2P radio channels. The performance of the proposed channel simulator is analyzed in terms of the autocorrelation and joint correlation function of the simulated shadowing process. Simulations illustrate that the proposed model is able to output deterministic shadowing with a normal distribution (in decibels) and the desired correlation properties. It is thus suitable for use in system-level simulations, such as the evaluation of routing and radio resource management algorithms in ad hoc or mesh networks.

Automated Diagnosis for UMTS Networks Using Bayesian Network Approach

Abstract: This paper presents an automated diagnosis in troubleshooting (TS) for Universal Mobile Telecommunications System (UMTS) networks using a Bayesian network (BN) approach. An automated diagnosis model is first described using the Naive Bayesian Classifier. To increase the performance of the diagnosis model, the entropy minimization discretization (EMD) method is incorporated into the model to select optimal segments for the discretization of the input symptoms. In the first phase, the diagnosis model is constructed using a dynamic simulator. The simulator TS platform allows generation of a large amount of data required to study the relations between faults and symptoms. In the second phase, the diagnosis model is adapted to a real UMTS network using counters and key performance indicators (KPIs) recovered from an Operations and Maintenance Center (OMC). Results for the automated diagnosis using both network simulator and real UMTS network measurements illustrate the efficiency of the proposed TS approach and its importance to mobile network operators.

Cross-Layer Design in Wireless Mesh Networks

Abstract: The conventional layered-protocol architecture does not provide optimal performance for wireless mesh networks (WMNs). The method of optimization decomposition of the protocol stack can achieve optimal network performance. This method usually results in a clean-slate protocol architecture that is different from the protocol architecture of WMNs. Such a difference actually demonstrates the need for a cross-layer design. Specific features pertaining to WMNs also show the need for cross-layer optimization across different protocol layers. In this paper, motivations for cross-layer design in WMNs are stated first. Moreover, cross-layer optimization schemes and algorithms between different protocol layers are investigated with an objective of shedding light on open research problems and new approaches. Guidelines for carrying out cross-layer design in WMNs are also provided in this paper.

Lane-Change Decision Aid System Based on Motion-Driven Vehicle Tracking

Abstract: Overtaking and lane changing are very dangerous driving maneuvers due to possible driver distraction and blind spots. We propose an aid system based on image processing to help the driver in these situations. The main purpose of an overtaking monitoring system is to segment the rear view and track the overtaking vehicle. We address this task with an optic-flow-driven scheme, focusing on the visual field in the side mirror by placing a camera on top of it. When driving a car, the ego-motion optic-flow pattern is very regular, i.e., all the static objects (such as trees, buildings on the roadside, or landmarks) move backwards. An overtaking vehicle, on the other hand, generates an optic-flow pattern in the opposite direction, i.e., moving forward toward the vehicle. This well-structured motion scenario facilitates the segmentation of regular motion patterns that correspond to the overtaking vehicle. Our approach is based on two main processing stages: First, the computation of optical flow in real time uses a customized digital signal processor (DSP) particularly designed for this task and, second, the tracking stage itself, based on motion pattern analysis, which we address using a standard processor. We present a validation benchmark scheme to evaluate the viability and robustness of the system using a set of overtaking vehicle sequences to determine a reliable vehicle-detection distance.

A Distributed Framework for Correlated Data Gathering in Sensor Networks

Abstract: We consider the problem of correlated data gathering in sensor networks with multiple sink nodes. The problem has two objectives. First, we would like to find a rate allocation on the correlated sensor nodes such that the data gathered by the sink nodes can reproduce the field of observation. Second, we would like to find a transmission structure on the network graph such that the total transmission energy consumed by the network is minimized. The existing solutions to this problem are impractical for deployment because they have not considered all of the following factors: (1) distributed implementation; (2) capacity and interference associated with the shared medium; and (3) realistic data correlation model. In this paper, we propose a new distributed framework to achieve minimum energy data gathering while considering these three factors. Based on a localized version of Slepian-Wolf coding, the problem is modeled as an optimization formulation with a distributed solution. The formulation is first relaxed with Lagrangian dualization and then solved with the subgradient algorithm. The algorithm is amenable to fully distributed implementations, which corresponds to the decentralized nature of sensor networks. To evaluate its effectiveness, we have conducted extensive simulations under a variety of network environments. The results indicate that the algorithm supports asynchronous network settings, sink mobility, and duty schedules.

Three-Dimensional Modeling, Simulation, and Capacity Analysis of Space–Time Correlated Mobile-to-Mobile Channels

Abstract: A 3-D reference model is proposed for multiple-input multiple-output (MIMO) mobile-to-mobile (M-to-M) multipath-fading channels. From this model, a closed-form joint space-time correlation function is derived for a 3-D nonisotropic scattering environment. Two sum-of-sinusoids-based 3-D simulation models for MIMO M-to-M multipath-fading channels are proposed. The statistics of the simulation models are verified by simulation. Finally, these simulation models are used to evaluate the effect of the space-time correlation on the outage capacity of uniform linear antenna arrays and to compare the capacities of linear, circular, and spherical antenna arrays.

Improved Positioning Algorithms for Nonline-of-Sight Environments

Abstract: Nonline-of-sight (NLOS) conditions pose a major challenge to radio positioning. In this paper, a constrained-optimization-based location algorithm is proposed to jointly estimate the unknown location and bias by using the sequential quadratic programming (SQP) algorithm. This method does not rely on any prior statistics information, and simulation results show that the proposed method considerably outperforms existing methods. To reduce the complexity of the SQP-based algorithm, we further propose a Taylor-series expansion-based linear quadratic programming (TS-LQP) algorithm. It is demonstrated that the computational complexity of the TS-LQP algorithm is only a fraction of that of the SQP algorithm, whereas the accuracy loss is limited. Also, maximum-likelihood (ML) algorithms that are suited for different NLOS error statistics are developed under several circumstances when there are different levels of a priori information. The analytical performance of the ML estimation (MLE) is investigated. Moreover, analytical expressions to approximate the variance of the MLE with and without model parameter mismatches are derived. Simulation results show that the approximate variance can be used as a better accuracy measure than the Cramer-Rao lower bound (CRLB).

Performance Analysis of IEEE 802.11 Broadcast Scheme in Ad Hoc Wireless LANs

Abstract: Since there have been increasing applications of IEEE 80211-based broadcast wireless networks, the ability to characterize medium access control (MAC) behavior and performance of mobile stations plays a key role in understanding and designing such broadcast systems In this paper, we study the saturation performance of the broadcast scheme in IEEE 80211 by an analytical model as well as by simulation Having investigated the literature and studied the features of the broadcast service, we point out that analytical models for saturation performance evaluation of IEEE 80211 unicast communication cannot simply be reduced for the analysis of broadcast service Under realistic assumptions, we construct an accurate model to characterize the operation of the backoff counter for broadcast service Based on solutions to the model, closed-form expressions of broadcast saturation performance indices, including throughput, packet delay, and packet delivery ratio (PDR), are derived The proposed analytical model is validated by simulation From the analysis of the proposed model, some observations and constructive suggestions to improve the performance of the broadcast service are given Numerical results also reveal the characteristics of the broadcast service

Connectivity Requirements for Self-Organizing Traffic Information Systems

Abstract: To facilitate the dissemination of a time-critical information in a vehicular ad hoc network (VANET), immediate network connectivity is needed. In other words, a time-critical message from a source should be able to propagate and reach all of the vehicles on the road segment without any delay due to the unavailability of the vehicles to forward the message. Clearly, this requires the road segment to have a certain number of vehicles equipped with communication devices. It is the task of a system designer to determine the minimum number of vehicles (i.e., the minimum penetration) necessary to form a connected network as well as the critical transmission range required to provide such connectivity. In this paper, we present an analytical framework for determining the connectivity requirements in distributing the traffic information in a self-organizing vehicular network. One- and two-way street scenarios are considered. In addition to the conventional perspective on connectivity, where the characteristics of the wireless channel are often neglected, our analysis offers a new view by taking important physical-layer parameters, such as fading, propagation path loss, transmit power, and transmission data rate, into consideration.