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In intelligent transportation systems (ITSs), the communication between the base station (BS) and the vehicles can form a virtual multiple-input multiple-out put (VMIMO) vehicle communication system. This paper addresses the issue of channel estimation in a virtual MIMO system that simultaneously adopt a smart antenna (SA). First, based on quaternion theory, a novel algorithm named quaternion noncircular MUSIC (QNC-MUSIC) is proposed, and direction of arrival (DOA) estimation is achieved for circular and noncircular signals. Then, a dimension reduction procedure is performed for the parameter search by employing the partial derivative of the spectrum function with respect to the noncircular phase; thus, a novel dimensional reduction noncircular MUSIC (DRNC-MUSIC) algorithm with a low computational complexity is proposed for DOA and polarization estimation of circular signals and noncircular signals. Finally, numerical examples are provided to demonstrate the parameter estimation performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a novel scheme is proposed to optimize the effectiveness of the device-to-device (D2D) enabled vehicular communications (D2D-V), which are underlaid in cellular networks, where the uplink channel allocated to one cellular user (CU) is reused by the multiple D2D-V links. To develop a well-functioning D2D-V system, the sum rate of all D2D-V links is necessary to be maximized, and also the reliability of the co-channel CU to infrastructure has to be guaranteed with the CU interference constraint. Unlike the traditional statical D2D systems, the D2D-V system suffers with high mobility and channel uncertainty. Therefore, the CU interference constraint is formulated as a probabilistic function by the Bernstein approximation, the constraint attempts to address the mobile channel fluctuations. Besides, the tractable approximate constraint is reformulated as two separable structure, this reformulated constraint attempts to determine the near-optimal solutions more efficiently. Since the objective function with a logarithmic form is nonconvex, successive convex approximation is applied to transform the nonconvex problem into the convex problem. The dual decomposition is used to determine the near-optimal solutions. After the problem is reformulated, a distributed robust power control algorithm is proposed to perform the chance-constrained optimization. Numerical simulations are used to evaluate the performance of the proposed scheme. The simulation results show the impacts of system performance when applying the proposed scheme in vehicular environments with high mobility. The proposed optimization schemes are further verified by comparing with the existing methods. [ABSTRACT FROM AUTHOR]

How to stimulate the devices to participate is a key problem in the device-to-device (D2D) communications, especially when there are multiple base stations in practice. On one hand, the base station needs to lower the price to compete with other base stations for attracting more devices. On the other hand, the base station needs to increase the price to obtain more benefit. In this paper, we propose an optimal multiprincipal multiagent contract design to tackle such a challenge. Specifically, we formulate the multiprincipal contract design problem as a game theoretic optimization problem, where the objective of each principle (base station) through contract design is to maximize its overall utility obtaining from the trade with agents (devices) subject to the individual rationality and incentive compatibility constraints. By solving the game theoretic optimization problems, we can obtain the equilibrium contract where the contracts of different principals reach an equilibrium and any deviation from a single principal will lead to the degradation of its own utility. Moreover, under the equilibrium, both the individual rationality and incentive compatibility constraints are satisfied, i.e., all agents will choose the corresponding contract according to their types to reach the optimal nonnegative utilities. Simulation results show that compared with the monoprincipal contract design, both the utilities of devices and the social welfare can be improved with the multiprincipal contract design. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is a promising scheme for the fifth generation (5G) of mobile communication systems. In this scheme, transmission to multiple users is performed on the same subchannel using superposition coding and successive interference cancellation. In this paper, we focus on a multi-cell network with two users’ data traffic models, namely elastic and streaming. We exploit the NOMA scheme in order to maximize the download elastic traffic rate at cells, without degrading the download streaming traffic rates. Since elastic traffic rates at different cells are interactive, we maximize the total elastic traffic rates assuming either perfect or partial channel state information available at each base station subject to a target rate for streaming users. Because of the interference due to NOMA as well as the interference among different cells, subchannel assignment and power allocation affect the system performance significantly. For this reason, we propose an iterative algorithm to jointly solve the subchannel assignment and the power allocation problem via the Hungarian algorithm and successive convex approximation, respectively. Finally, our simulation results show the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Small cells are introduced to cellular systems to enhance coverage and improve capacity. Densely deploying small cells can not only offload the traffic of macrocells but also provide an energy- and cost-efficient way to meet the sharp increase in traffic demands in mobile networks. However, such a cell deployment paradigm also leads to heterogeneous network (HetNet) infrastructure and raises new challenges for cell planning. In this paper, we study the cell planning issue in the HetNet. Our optimization task is to select a subset of candidate sites to deploy macro or small cells to minimize the total cost of ownership (TCO) or the energy consumption of the cellular system while satisfying practical constraints. We introduce approximation algorithms to cope with two different cell-planning cases, which are both NP-hard. First, we discuss the macrocell-only case. Our proposed algorithm achieves an approximation ratio of O(\log R) in this scenario, where R is the maximum achievable capacity of macrocells. Then, we introduce an O(\log \widetildeR)-approximation algorithm to the small-cell scenario, where \widetildeR is the maximum achievable capacity of a macrocell with small cells overlaid on it. Numerical results indicate that the HetNet can significantly reduce the TCO and the energy consumption of the cellular system. [ABSTRACT FROM PUBLISHER]

Object detection plays an important role in intelligent transportation systems and intelligent vehicles. Although the topic of object detection has been studied for decades, it is still challenging to accurately detect objects under complex scenarios. The contributing factors for challenges include diversified object and background appearance, motion blur, adverse weather conditions, and complex interactions among objects. In this paper, we propose a new convolutional neural network (CNN) model for traffic object detection, by using multi-scale local and global feature representation (MFR). The proposed model consists of two components: a region proposal network that generates candidate object regions and an object detection network that incorporates multi-scale features and global information, namely MFR-CNN. These two components are jointly optimized. Once the system is trained, it can detect real-world traffic objects accurately, especially small objects and heavily occluded objects. We evaluate the proposed method on four benchmark datasets, achieving consistent improvements over the state of the art. [ABSTRACT FROM AUTHOR]

Deploying femtocells underlaying macrocells is a promising way to improve the capacity and enhance the coverage of cellular systems. However, such a two-tier network also gives rise to a cross-tier and intratier interference issue that should be properly addressed to acquire the potential performance gain. In this paper, we study the resource-allocation (RA) problem in a two-tier orthogonal frequency-division multiplexing (OFDM) access-based heterogeneous cellular network, where the femtocells that employ a closed access strategy are equipped with a cognitive radio (CR) function to identify radio environment so that they can share subchannels with the macrocells without generating excessive interference to the macrocell users (MUs), which fall into the coverage of the femtocells. We formulate an optimization task to maximize the sum throughput of the femtocell users (FUs) under the consideration of imperfect spectrum sensing and channel uncertainty while controlling the interference to the MUs below their bearable thresholds in the sense of probability. We introduce a conservative convex approximation to the formulated problem and develop a fast algorithm to solve it by exploiting its structure. Simulation results show that our proposal can improve the throughput of the FUs with almost no changes in the infrastructure of the cellular network. [ABSTRACT FROM PUBLISHER]

Wireless vehicle-to-vehicle (V2V) and vehicle-toinfrastructure (V2I) communication holds great promise for significantly reducing the human and financial costs of vehicle collisions. A common characteristic of this communication is the broadcast of a device's core state information at regular intervals (e.g., vehicle speed and location or traffic signal state and timing). Unless controlled, the aggregate of these broadcasts will congest the channel under dense traffic scenarios, reducing the effectiveness of collision avoidance applications that use transmitted information. Active congestion control using distributed techniques is a topic of great interest for establishing the scalability of this technology. This paper defines a new adaptive congestion control algorithm that can be applied to the message rate of devices in this vehicular environment. While other published approaches rely on binary control, the LInear MEssage Rate Integrated Control (LIMERIC) algorithm takes advantage of full-precision control inputs that are available on the wireless channel. The result is provable convergence to fair and efficient channel utilization in the deterministic environment, under simple criteria for setting adaptive parameters. This “perfect” convergence avoids the limit cycle behavior that is inherent to binary control. We also discuss several practical aspects associated with implementing LIMERIC, including guidelines for the choice of system parameters to obtain desired utilization outcomes, a gain saturation technique that maintains robust convergence under all conditions, convergence with asynchronous updates, and using channel load to determine the aggregate message rate that is observable at a receiver. This paper also extends the convergence analysis for two important cases, i.e., measurement noise in the input signal and delay in the update process. This paper illustrates key analytical results using MATLAB numerical results and employs standard NS-2 simulations to demonstrate the performance of LIMERIC in several high-density scenarios. [ABSTRACT FROM PUBLISHER]

Rising user expectations are changing the way mobile operators manage their networks. In this paper, a self-tuning algorithm for adjusting parameters in a multiservice packet scheduler of a Long-Term Evolution base station is proposed to optimize the overall system Quality of Experience (QoE) based on network performance statistics. For this purpose, the algorithm iteratively changes service priority parameters to reprioritize services so as to make the most of available resources. The proposed algorithm ensures that the best overall system QoE is always reached by analyzing optimality conditions, unlike previous works, which only guarantee a minimum user satisfaction level or aim to balance QoE among services. Method assessment is carried out with a dynamic system-level simulator in a realistic service scenario. Simulation results show that the overall network QoE can be improved up to $35\%$ by tuning service priority parameters. [ABSTRACT FROM PUBLISHER]

In opportunistic mobile networks (OppNets), a large amount of energy is consumed by idle listening, instead of infrequent data exchange. This makes energy saving a challenging and fundamental problem in OppNets since nodes are typically battery powered. Asynchronous duty-cycle operation is a promising approach for energy saving in OppNets; however, if its working schedule is not effectively designed, it may also cause significant network performance degradation. Therefore, it is pressing to design an energy-efficient working schedule for duty-cycle OppNets. In this paper, we first analyze the contact process in duty-cycle OppNets and then propose an adaptive working schedule for duty-cycle OppNets. The proposed adaptive working schedule uses the past recorded contact histories to predict future contact information to adaptively configure the working schedule of each node in the network. Finally, extensive real trace-driven simulations are conducted to evaluate the performance of our proposed adaptive working schedule. Extensive real trace-driven simulation results demonstrate that our proposed adaptive working schedule is superior to the random working schedule and the periodical working schedule algorithms in terms of the number of effect contacts, delivery ratio, and delivery delay. [ABSTRACT FROM AUTHOR]

This paper addresses self-optimization of the random access channel (RACH) in the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE). Ensuring satisfactory random access (RA) performance in terms of access delay (AD) is crucial for reducing the delays associated with initial access and handovers. The feasibility of self-optimization is investigated by means of simulations, where the coupling between several parameters and the RACH performance in terms of AD is provided. We present two candidate feedback control algorithms that automatically adjust key RACH parameters to meet specified AD targets. [ABSTRACT FROM PUBLISHER]

The introduction of fourth-generation wireless technologies has fueled the rapid development of cellular networks, significantly increasing the energy consumption and the expenditures of mobile network operators (MNOs). In addition, network underutilization during low-traffic periods (e.g., night zone) has motivated a new business model, namely, infrastructure sharing, which allows the MNOs to have their traffic served by other MNOs in the same geographic area, thus enabling them to switch off part of their network. In this paper, we propose a novel infrastructure-sharing algorithm for multioperator environments, which enables the deactivation of underutilized base stations during low-traffic periods. Motivated by the conflicting interests of the MNOs and the necessity for effective solutions, we introduce a game-theoretic framework that enables the MNOs to individually estimate the switching-off probabilities that reduce their expected financial cost. Our approach reaches dominant strategy equilibrium, which is the strategy that minimizes the cost of each player. Finally, we provide extensive analytical and experimental results to estimate the potential energy and cost savings that can be achieved in multioperator environments, incentivizing the MNOs to apply the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the network resource allocation in multiuser downlink wireless systems where the base station and the mobile stations are equipped with multiple antennas to provide fair and efficient transmission services to the mobile users. We focus on packet scheduling, given that it has a significant impact on the overall performance of a multiple-input-multiple-output (MIMO) system. Most previous schedulers designed at the packet level do not take into account the traffic characteristics (different packet lengths and the arrival process parameters); consequently, they fall short of simultaneously providing fairness and a low average packet transmission delay. We are making use of a flexible packet transmission algorithm at the medium access control (MAC) layer to develop and propose a novel scheduler, which is referred to as MIMO packet-based proportional fairness (MP-PF). The new scheduler is designed with the goal of providing high performance in terms of a low average packet transmission delay and time and service fairness among the users based on the concept of proportional fairness. The scheduler also conserves work and takes into consideration the packet length, the user queue length, the user transmission rate (related to its channel quality), and the service guarantees for heterogeneous users. The well-known ideal service fair scheduler called max-min can also significantly be improved using our framework by taking into consideration the traffic characteristics. We also provide an analysis for the fairness of the new scheduler in terms of time and service allocation, which is the key contribution of this paper. Simulations that consider the traffic characteristics and the mobility of users show the relatively low average packet transmission delay and demonstrate the time and service fairness capabilities of MP-PF, compared with other well-known MIMO schedulers. [ABSTRACT FROM AUTHOR]

Maximum-likelihood (ML) detection for higher order multiple-input-multiple-output (MIMO) systems faces a major challenge in computational complexity. This limits the practicality of these systems from an implementation point of view, particularly for mobile battery-operated devices. In this paper, we propose a modified approach for MIMO detection, which takes advantage of the quadratic-amplitude modulation (QAM) constellation structure to accelerate the detection procedure. This approach achieves low-power operation by extending the minimum number of paths and reducing the number of required computations for each path extension, which results in an order-of-magnitude reduction in computations in comparison with existing algorithms. This paper also describes the very-large-scale integration (VLSI) design of the low-power path metric computation unit. The approach is applied to a 4 x 4, 64-QAM MIMO detector system. Results show negligible performance degradation compared with conventional algorithms while reducing the complexity by more than 50%. [ABSTRACT FROM AUTHOR]

In this paper, we propose to develop wireless Sensor Networks with Mobile Sinks (MSSNs). The proposed MSSN is highly energy efficient, because the multihop transmissions of high-volume data over the network are converted into single-hop transmissions. We focus our investigation on sparsely deployed networks, where single node-to-sink transmission is considered. The transmission-scheduling algorithm (TSA-MSSN) is proposed, where a parameter λ is employed to control the tradeoff between the maximization of the probability of successful information retrieval and the minimization of the energy-consumption cost. It is shown that the proposed implementation of the TSA-MSSN has a complexity of O(1). This paper serves as the foundation for understanding fundamental laws behind the aforementioned tradeoff with useful implications for the design of more complex MSSNs. [ABSTRACT FROM AUTHOR]

To enhance the backscatter-links with double fading effect in non-orthogonal multiple access assisted backscatter communication (NOMABC), a new reconfigurable intelligent surface (RIS) enhanced NOMABC (RIS-NOMABC) system is proposed. A joint optimization problem over power reflection coefficients at the backscatter devices (BDs) and phase shifts at the RIS is formulated. To solve this non-convex problem, a low complexity algorithm is proposed by invoking the alternative optimization, successive convex approximation and manifold optimization algorithms. Numerical results corroborate that the proposed RIS-NOMABC system outperforms the conventional NOMABC system without RIS, and demonstrate the feasibility and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Automated and coordinated vehicles' driving (platooning) is very challenging due to the multibody control complexity and the presence of unreliable time-varying wireless intervehicular communication (IVC). We propose a novel controller for vehicle platooning based on consensus and analytically demonstrate its stability and dynamic properties. Traditional approaches assume the logical control topology as a constraint fixed a priori, and the control law is designed consequently; our approach makes the control topology a design parameter that can be exploited to reconfigure the controller, depending on the needs and characteristics of the scenario. Furthermore, the controller automatically compensates outdated information caused by network losses and delays. The controller is implemented in Plexe, which is a state-of-the-art IVC and mobility simulator that includes basic building blocks for platooning. Analysis and simulations show the controller robustness and performance in several scenarios, including realistic propagation conditions with interference caused by other vehicles. We compare our approach against a controller taken from the literature, which is generally considered among the most performing ones. Finally, we test the proposed controller by implementing the real dynamics (engine, transmission, braking systems, etc.) of heterogeneous vehicles in Plexe and verifying that platoons remain stable and safe, regardless of real-life impairments that cannot be modeled in the analytic solution. The results show the ability of the proposed approach to maintain a stable string of realistic vehicles with different control-communication topologies, even in the presence of strong interference, delays, and fading conditions, providing higher comfort and safety for platoon drivers. [ABSTRACT FROM PUBLISHER]

This paper considers the problem of network-based mobile-phone positioning when multiple providers are available. This paper proposes two cross-provider localization algorithms via a cooperative approach, which are called linear regression (LR) and locally cooperative embedding (LCE), to efficiently exploit the complementary information from each network provider. The former chooses the provider weights that minimize the mean-square positioning errors. The latter dynamically embeds the cooperation and iteratively refines the positioning process according to each provider's local accuracy surrounding the user. This paper applies the proposed cross-provider positioning algorithms to actual Global System for Mobile Communications (GSM) networks, using a dual-subscriber-identity-module (SIM) mobile phone connecting to multiple providers simultaneously. On-site experiments clearly demonstrated that the proposed cross-provider approaches provide better positioning accuracy than any individual provider, where LCE achieves the best performance. [ABSTRACT FROM PUBLISHER]

An adaptive estimation algorithm based on the Lorentzian norm is proposed for echo cancellation in vehicle hands-free communication systems and video teleconferencing systems, namely the affine-projection Lorentzian (APL) algorithm. By minimizing the Lorentzian norm of the a posteriori error vector with a suitable constraint on the weight vector and providing a dynamic Lorentzian-norm-controlling parameter, the proposed APL algorithm achieves robustness against impulsive disturbances and speeds up convergence for colored input signals. The computational complexity of the APL algorithm is analyzed and a fast recursive filtering method is employed to reduce its complexity. The stability analysis, based on energy-conservation arguments, shows that the APL algorithm converges. Furthermore, its tracking behavior is also investigated and a step size optimizing the tracking performance is derived. Simulation results agree well with the theoretical analysis. Simulation results for channel estimation and in-car echo cancellation scenarios demonstrate that the APL algorithm achieves better performance compared to the maximum-correntropy-criterion, affine-projection-generalized-maximum-correntropy, affine-projection-sign, affine-projection-like M-estimate, and Lorentzian adaptive filtering algorithms in various impulsive interference environments. [ABSTRACT FROM AUTHOR]

This paper presents and evaluates artificial neural network (ANN) models used for macrocell path-loss prediction. Measurement data obtained by utilizing the IS-95 pilot signal from a commercial code-division multiple-access (CDMA) mobile network in rural Australia are used to train and evaluate the models. A simple neuron model and feed-forward networks with different numbers of hidden layers and neurons are evaluated regarding their training time, prediction accuracy, and generalization properties. Furthermore, different backpropagation training algorithms, such as gradient descent and Levenberg--Marquardt, are evaluated. The artificial neural network inputs are chosen to be distance to base station, parameters easily obtained from terrain path profiles, land usage, and vegetation type and density near the receiving antenna. The path-loss prediction results obtained by using the ANN models are evaluated against different versions of the semi-terrain based propagation model Recommendation ITU-R P.1546 and the Okumura--Hata model. The statistical analysis shows that a non-complex ANN model performs very well compared with traditional propagation models with regard to prediction accuracy, complexity, and prediction time. The average ANN prediction results were 1) maximum error: 22 dB; 2) mean error: 0 dB; and 3) standard deviation: 7 dB. A multilayered feedforward network trained using the standard backpropagation algorithm was compared with a neuron model trained using the Levenberg--Marquardt algorithm. It was found that the training time decreases from 150 000 to 10 iterations, while the prediction accuracy is maintained. [ABSTRACT FROM AUTHOR]

This paper presents a novel vehicle-classification algorithm that uses the time-variable signal generated by a single inductive loop detector. In earlier studies, the noisy raw signal was fed into the algorithm by reducing its size with rough sampling. However, this approach loses the original signal form and cannot be the best exemplar vector. The developed algorithm suggests three contributions to cope with these problems. The first contribution is to clear the noise with discrete Fourier transform (DFT). The second contribution is to transfer the noiseless pattern into the Principal Component Analysis (PCA) domain. PCA is exploited not only for decorrelation but for explicit dimensionality reduction as well. This goal cannot be achieved by simple raw data sampling. The last contribution is to expand the principal components with a local maximum (Lmax) parameter. It strengthens the classification accuracy by emphasizing the undercarriage height variation of the vehicle. These parameters are fed into the three-layered backpropagation neural network (BPNN). BPNN classifies the vehicles into five groups, and the recognition rate is 94.21%. This recognition rate has performed best, compared with the methods presented in published works. [ABSTRACT FROM AUTHOR]

This paper studies the performance of cellular mobile systems employing a signal-to-noise ratio (SNR)-based generalized selection combining (GSC) algorithm in the presence of background white noise and multiple cochannel interfering signals. Closed-form expressions are derived for the received signal-to-interference-plus-noise ratio (SINR) distribution and outage probability, considering the case when the interfering signals experience mixed Rayleigh and Nakagami-q fading conditions, and the desired-signal replicas are attenuated by flat Rayleigh fading. These expressions are obtained via the new representation of the total interference-to-noise ratio (INR) distribution for the mixed mode of fading experienced by different interferers. The derived expressions for the aforementioned statistical measures are valid for an arbitrary number of interferers and system diversity order and can be employed to investigate the impact of various system and fading parameters on the performance measures. Several case studies can be deduced from the results presented in this paper, including interference-limited systems, wherein the impact of white noise can be neglected. [ABSTRACT FROM AUTHOR]

There are numerous research challenges that need to be addressed until a wide deployment of vehicular ad hoc networks (VANETs) becomes possible. One of the critical issues consists of the design of scalable routing algorithms that are robust to frequent path disruptions caused by vehicles' mobility. This paper argues the use of information on vehicles' movement information (e.g., position, direction, speed, and digital mapping of roads) to predict a possible link-breakage event prior to its occurrence. Vehicles are grouped according to their velocity vectors. This kind of grouping ensures that vehicles, belonging to the same group, are more likely to establish stable single and multihop paths as they are moving together. Setting up routes that involve only vehicles from the same group guarantees a high level of stable communication in VANETs. The scheme presented in this paper also reduces the overall traffic in highly mobile VANET networks. The frequency of flood requests is reduced by elongating the link duration of the selected paths. To prevent broadcast storms that may be intrigued during path discovery operation, another scheme is also introduced. The basic concept behind the proposed scheme is to broadcast only specific and well-defined packets, referred to as "best packets" in this paper. The performance of the scheme is evaluated through computer simulations. Simulation results indicate the benefits of the proposed routing strategy in terms of increasing link duration, reducing the number of link-breakage events and increasing the end-to-end throughput. [ABSTRACT FROM AUTHOR]

This paper investigates the features of a cellular geometry in code-division multiple-access (CDMA) systems with soft handoff and distinguishes controlling area of a cell from coverage area of a cell. Some important characteristics of the cellular configuration in soft handoff systems are used to propose a new design of efficient call admission control (CAC) in CDMA systems. Then, the paper constructs a continuous-time Markov chain (CTMC) model for CAC in CDMA with a soft handoff queue, obtains closed-form solutions, and thus develops loss formulas as performance indices such as the new blocking probability and the handoff dropping probability. In order to determine handoff traffic arrival rate, a fixed-point strategy is developed. Algorithms are also provided to stably compute loss probabilities and to determine the optimal number of guard channels. A new soft handoff scheme—eliminating pseudo handoff calls (EPHC)—is proposed to improve channel utilization efficiency based on mobility information. As an application of the loss formulas, the proposed modeling techniques are used to evaluate and compare the performance of conventional and proposed EPHC soft handoff schemes. Numerical results show the effectiveness of the proposed Markov chain models and the benefits of the new soft handoff scheme. [ABSTRACT FROM AUTHOR]

Recently, a hardware-friendly fixed-complexity Lenstra–Lenstra–Lovász (fcLLL) algorithm has been developed for use in the linear receivers of multiple-input–multiple-output (MIMO) systems. In this paper, we propose a novel fcLLL-based detection method that significantly outperforms conventional fcLLL-based linear receivers at a lower fixed complexity. The main idea is that the complexity of fcLLL can be significantly reduced by disregarding a single column of the channel matrix. We also propose column selection methods that consider both the error performance and complexity simultaneously. Simulations are performed to demonstrate the efficacy of the proposed method. [ABSTRACT FROM PUBLISHER]

Monitoring of lateral vehicle motion is very useful in many active safety applications such as yaw stability control and rollover prevention. Lateral velocity and sideslip angle are regarded as the most important motion variables. However, it is not feasible during vehicle operation to directly measure them due to the high cost of sensors, limitations to sensor technology, etc. Therefore, the monitoring of lateral vehicle motion can be realized by using either accurate monitoring models or improved estimation algorithms. In this paper, monitoring models are obtained such that they utilize not only the vehicle dynamics but the cornering stiffness and the roll motion as well. Based on these monitoring models, three monitoring systems are constructed to estimate the vehicle velocity and the sideslip angle based on the sliding mode observer, the extended Kalman filter (EKF) including Dugoff's tire model, and the scaled Kalman filter with model error compensator (SKFMEC) methods, respectively. The estimation performance of the monitoring systems is verified in field tests, and the experimental results demonstrate the effectiveness of this approach to provide accurate monitoring of lateral vehicle motion. [ABSTRACT FROM PUBLISHER]

Location determination of a mobile subscriber (MS) to support location-based services has become an area of highly active research over the past few years. The stationary signal-strength-difference (SSSD)-based positioning technique has been proposed as a cost-effective low-complexity solution. However, its accuracy is limited due to the error in reference distance estimation. This paper contributes a simple and efficient method to minimize the error in the reference distance and consequently reduce the error in MS location determination. The proposed method is based on a standard parameter separation least-square algorithm by following the convergences of the gradient-descent algorithm to determine the MS location. Accuracy evaluation is implemented at 55 different test locations in an urban environment under a commercial cellular network. Experimental results clearly demonstrated that the proposed method performs superior positioning accuracy as compared with our previous works and the trilateration positioning method. [ABSTRACT FROM PUBLISHER]

Due to the uncertainty of transmission opportunities between mobile nodes, the routing of delay-tolerant networks (DTNs) exploits the mechanism of opportunistic forwarding. Efficient algorithms and policies for opportunistic forwarding are crucial for maximizing the message delivery probability while reducing the delivery cost. In this paper, we investigate the problem of energy-efficient opportunistic forwarding for DTNs. First, we model the message dissemination by introducing a continuoustime Markov framework. Based on this framework, we formulate the optimization problem of opportunistic forwarding, with the constraint of energy consumed by the message delivery for both two-hop and epidemic forwarding. Then, based on the solution of the optimization problem, we design different kinds of forwarding policies such as static and dynamic policies. Among these policies, we find that the threshold dynamic policy is optimal for both two-hop and epidemic forwarding. By simulation results, we show the accuracy of our continuous-time Markov analysis model. Furthermore, through extensive numerical results, we demonstrate that the performance of the threshold dynamic policy is the best among the static and continuous dynamic policies, and among the continuous dynamic policies, the negative-power policy provides relatively better performance. [ABSTRACT FROM PUBLISHER]

Relay selection is crucial in improving the performance of wireless cooperative networks. Most previous works for relay selection use the current observed channel conditions to make the relay-selection decision for the subsequent frame. However, this memoryless channel assumption is often not realistic given the time-varying nature of some mobile environments. In this paper, we consider finite-state Markov channels in the relay-selection problem. Moreover, we also incorporate adaptive modulation and coding, as well as residual relay energy in the relay-selection process. The objectives of the proposed scheme are to increase spectral efficiency, mitigate error propagation, and maximize the network lifetime. The formulation of the proposed relay-selection scheme is based on recent advances in stochastic control algorithms. The obtained relay-selection policy has an indexability property that dramatically reduces the computation and implementation complexity. In addition, there is no need for a centralized control point in the network, and relays can freely join and leave from the set of potential relays. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The Mobile IP Authentication, Authorization, and Accounting (AAA) framework architecture is designed to protect signaling messages from eavesdropping by malicious attackers. The message exchanges for AAA incur heavy signaling overhead and long network access latency for mobility service. To solve this problem, the most typical approach is to adopt a key caching mechanism so that the authentication can locally be done and so that the signaling overhead can be significantly reduced. However, in the literature, very little work has conducted a thorough analytical study on the proposed key caching scheme. As a result, the statistical behavior of these schemes cannot be well justified. In this paper, we develop an analytical model that describes the key caching behavior in Mobile IP networks. The accuracy of this model is validated by simulations. Based on the performance analysis, we then propose an adaptive algorithm that dynamically adjusts key cache size so that the signaling overhead can be minimized. [ABSTRACT FROM AUTHOR]

As functionality of vehicles increases in complexity, the demand on the in-vehicle networks increases as well. Maxi- mum bus utilization often becomes the communication bottleneck. One way to satisfy the high bandwidth requirement for future vehicles is to use a higher bandwidth bus or multiple buses. However, the use of a higher bandwidth bus increases the cost of the network. Similarly, the use of multiple buses increases the cost as well as the complexity of wiring and network handling. Both options are becoming solutions to high bandwidth demand. An alternative option is the development of a higher layer protocol that uses data-reduction (DR) techniques to reduce the amount of data to be transferred. Its goal is to communicate the same amount of information using less bus bandwidth. It would be acceptable, provided that it does not increase the message latencies significantly so that the safety of the vehicle is not compromised. The cost of the protocol is expected to be marginal because it consists of one-time changes to software. Various DR algorithms are available in the literature, but DR technology has not been introduced in in-vehicle protocol standards. This paper presents a unique DR methodology, along with its comparison with other proposed methodologies. The performance of this new DR algorithm is found to be better than that of the existing DR algorithms for a wide range of signal dynamics. The cost, as well as the impact of this protocol on the end-to-end message latency, has been found to be very marginal. [ABSTRACT FROM AUTHOR]

Vehicle-based sensors can be used for traffic monitoring. These sensors are usually set with long sampling intervals to save communication costs and to avoid network congestion. In this paper, we are interested in understanding the traffic-monitoring performance that we can expect from such vehicle-based mobile sensor networks, despite the incomplete information provided. This is a fundamental problem to be addressed. A performance evaluation has been carried out in Shanghai, China, by utilizing the vehicle-based sensors installed in about 4000 taxies. Two types of traffic status-estimation algorithms, i.e., the link-based and the vehicle-based, are introduced and analyzed. The results show that estimations of the traffic status based on these imperfect data are reasonably accurate. Therefore, the feasibility of such an application is demonstrated. [ABSTRACT FROM AUTHOR]

The stationary signal-strength-difference (SSSD)-based positioning technique has been proposed as a cost-effective, low-complexity solution. The positioning accuracy with this technique, however, is limited, as a result of the large error in the distance. In this paper, we contribute a simple and efficient method for the accuracy improvement issues in the distance. Starting from the concept of the Global Positioning System (GPS) pseudorange (PD) equation, a complete set of distance difference (DD) is formulated. In addition, we then correct the error in the distance by going in the set of DD, based on the least-squares (LS) sense. The theoretical model is established and verified via experimental data gathered in an urban environment. Results clearly show that the proposed method performs well when encountering a large error in the distance. On top of this, we investigate the accuracy improvement issues in the location estimation and propose an iterative LS algorithm by using the corrected distances. The positioning accuracy is studied based on the analysis of different location errors, and the effect of geometric dilution of precision (GDOP) is also investigated. The improvement of the positioning accuracy is clearly demonstrated through the experimental data collected at 55 different test points with 25 133 samples, which is outstanding. [ABSTRACT FROM AUTHOR]

Abstract-This paper proposes a dynamic resource-allocation (DRA) algorithm for packet data services in wireless communication systems based on Hopfield neural networks (HNNs). The resource-allocation algorithm assumes a delay-centric approach in that it maximizes resource utilization of the overall system while minimizing the packet delay. The real-time (RT) working capability of HNN hardware implementation means that a very powerful scheduling DRA algorithm can be obtained. A generic formulation of the algorithm is presented to establish the optimal bit rate allocation. In addition, some illustrative examples of this formulation are given, considering specific wireless communication systems, such as General Packet Radio Service (GPRS) or Universal Mobile Telecommunications System (UMTS). lo be more precise, the performance of the proposed DRA algorithm is evaluated in a realistic UMTS scenario, considering both RT and nonreal-time (NRT) services. To obtain the best resource distribution and fulfill the different quality-of-service (QoS) levels required by RT and NRT services, the new HNN-based delay-centric DRA algorithm is performed twice. Initially, only the RT services are considered, and following this, all the NRT services are taken into account. The results reveal that the proposed DRA algorithm outperforms other reference algorithms in terms of not only average packet delay but the allocated total bit rate as well. [ABSTRACT FROM AUTHOR]

This paper considers the optimal distributed assignment of rates to elastic users in a broadband multicell code-division multiple-access (CDMA) network with variable rate assignments, which is connected to a traditional wired Internet Protocol (IP) network. We show that by using an optimization framework, it is possible to construct a distributed rate assignment algorithm similar to current congestion control protocols that addresses both media access control and transport layer issues (i.e., addresses both interference and congestion control). Practical implementation of this algorithm, as well as its impact on convergence and performance, is also addressed. [ABSTRACT FROM AUTHOR]

This paper proposes a novel downlink spatial scheduling algorithm in multiuser multiple-input--multiple-output (MIMO) systems, which selects a good combination of terminals and base station's (BS's) transmit beams so that the BS's beams nullify interstream interference at the selected terminals. In the derivation process, we reveal the new property that the optimization problem of downlink spatial scheduling is equivalent to that of uplink scheduling under the BS's zero-forcing beamforming. Using this property, an efficient downlink scheduling algorithm is presented, applying the principle of an uplink scheduling algorithm. Numerical results show that the presented spatial scheduling achieves a much higher system throughput than a multiuser MIMO system without spatial scheduling or with conventional spatial scheduling by linear processing. We also present a realistic control structure to achieve the uplink and downlink spatial scheduling in time-division duplex systems. [ABSTRACT FROM AUTHOR]

In this paper, we present an opportunistic packet scheduling algorithm based on buffer management (OSBM) over the downlink of a packet cellular network. OSBM is a channel-dependent scheduling algorithm with a provable delay bound. It is able to provide differentiated services to both real-time and nonreal-time applications. Particularly, these features of OSBM are achieved through a novel buffer management scheme. Since this buffer management scheme does not involve any complex online computation, OSBM is very efficient and easy to implement in an operational environment. We also present a new analytical approach for performance analysis of opportunistic scheduling in wireless networks based on the proposed concept of effective downlink capacity (EDC). This approach attempts to adapt the service curve tool for deterministic quality-of-service analysis to the wireless environment, and the concept of the EDC serves to bridge the deterministic method and the stochastic nature of the wireless link. Using this approach, the explicit expression of the delay bound of the OSBM algorithm is obtained. Simulation results are presented to demonstrate the effectiveness of the proposed opportunistic scheduling algorithm. [ABSTRACT FROM AUTHOR]

With a small amount of software modification, wireless extension points (EPs), which are now commercially available, can be used to improve the throughput capacity of a wireless local area network (WLAN). An EP is an immobile device that has access to the power supply or is equipped with a high-capacity battery but does not have direct access to the Internet. They wirelessly relay data between the access point and the mobile hosts. In this paper, we investigate the optimal placement of the EPs such that the throughput capacity of an urban rectilineal WLAN can be maximized. Two channel models that are based on the Shannon capacity bound and IEEE 802.11 specifications are studied. We first formulate a solution for the optimal EP placement problem in a general network scenario as a nonlinear programming problem; then, we propose an efficient algorithm that determines the optimal locations of a fixed number of EPs in a rectilineal network. Our results show that, for a wide range of system parameters, the optimally placed EPs can significantly increase the network throughput capacity. Moreover, we study how the number of EPs, transmission power, path loss exponent, channel models, and traffic characteristics affect the optimal EP placement and expected throughput capacity of the network. [ABSTRACT FROM AUTHOR]

With various wireless technologies developed over the past few years, a ubiquitous and integrated architecture is envisioned for future wireless communication. An important optimization issue in such an integrated system is how to minimize the overall communication cost by intelligently utilizing the avail- able heterogeneous wireless technologies while, at the same time, meeting the quality-of-service requirements of mobile users. In this paper, we first identify the cost-minimization (CM) problem to be NP-hard. We then present an efficient minimum-cost data- delivery algorithm based on linear programming (LP), with various constraints, such as channel bandwidth, link costs, delay budgets, and user mobility, taken into consideration. In case of insufficient bandwidth for communication with the core network, prefetch is employed to fully utilize the wireless-network capacity. If multiple routes are available, a probability-based approach is taken for CM. Extensive simulations are carried out to evaluate the proposed CM scheme. Our results show that the proposed LP approach can effectively reduce the overall communication cost, with small overhead (< 3%) for signaling, computing, and handoff. We expect that minimum-cost data delivery will become imperative for the future heterogeneous wireless networks and the emerging 4G wireless systems. [ABSTRACT FROM AUTHOR]

State-of-the-art vehicles are now being equipped with multiple video channels for video-data transmission from multiple surveillance cameras mounted on the automobile, navigation videos reporting the traffic conditions on the planned route, as well as entertainment-multimedia streaming for passengers watching on rear-seat monitors. Wireless LANs provide a low-cost and flexible infrastructure for these emerging in-vehicle multimedia services aimed at the driver's and passengers' safety, convenience, and entertainment. To enable the successful simultaneous deployment of such applications over in-vehicle wireless networks, we propose delay-sensitive streaming and packet-scheduling algorithms that enable simple, flexible, and efficient adaptation of the video bitstreams to the instantaneously changing video source and wireless-channel characteristics while complying with the a priori negotiated quality-of-service (QoS) parameters for that video service. Our focus is on real-time low-cost solutions for multimedia transmission over in-vehicle wireless networks that are derived based on existing protocols defined by QoS-enabled networks, such as the IEEE 802.11e standard. In addition, the aim of this paper is to couple the proposed solutions with a novel multitrack-hinting method that is proposed as an extension of conventional MP4 hint tracks in order to provide real-time adaptation of multimedia streams to multiple quality levels for different in-vehicle applications, depending on their importance and delay constraints. First, the scheduling constraints for these simultaneous wireless video-streaming sessions are analytically expressed as a function of the negotiated QoS parameters. This is imperative because a video stream received from an in-vehicle road-surveillance camera will have a different set of delay and quality constraints in comparison to that of traffic monitoring received from remote video cameras located on the planned route. Hence, transmission parameters, such as peak data rate, maximum burst size, minimum transmission delay, maximum error rate, etc., will differ for the various video streams. For this reason, new low-complexity packet-scheduling algorithms that can fulfill diverse QoS streaming conditions are proposed and analyzed. The proposed algorithms produce viable schedules (i.e., strictly QoS.compliant) that jointly consider the delay constraints and the in-vehicle video-receiver-buffer conditions. Hence, these scheduling schemes can completely avoid the underflow or overflow event of the receiving-device buffer while guaranteeing the agreement between the real-time video traffic and the predetermined traffic specification reached during QoS negotiation for various in-vehicle video channels. When combined with multitrack hinting, an integrated flexible system for adaptive multimedia streaming over QoS-enabled in-vehicle wireless networks can be constructed. We demonstrate the viability of the proposed scheduling mechanisms experimentally by using real video traces under multiple quality levels, as derived by the multitrack-hinting design. In addition, simulations under realistic conditions are also performed to validate the ability of the method to satisfy buffer-occupancy constraints. [ABSTRACT FROM AUTHOR]

In this paper, novel connection admission control (CAC) algorithms that take into account the effect of mobility of users both inside and outside the cell in the downlink of third-generation mobile systems are developed. First, the system capacity, including the other-cell interference, subject to feedback between cells is studied. Then, effective bandwidth expressions for calls are obtained as a function of both their location in the cell as well as their class of traffic (i.e., voice versus data). Next, this formulation is used to derive two mobility-aware admission control algorithms, i.e., a priority CAC, where calls are accepted not only upon resource availability, but also through acceptance ratios that reflect their levels of priority, and a squeezing CAC, where elastic calls may be squeezed to a minimum agreed value, giving way to admit more calls in the system and to secure further ongoing mobile users. Using Markovian analysis, several performance measures are obtained, namely the blocking probability, the dropping probability, both intracell and intercell, as well as the overall cell throughput. The authors eventually investigate the performance of our CAC and show how to extend the Erlang capacity bounds, i.e., the set of arrival rates such that the corresponding blocking/dropping probabilities are kept below predetermined thresholds. [ABSTRACT FROM AUTHOR]

This paper presents efficient dynamic resource allocation schemes with interference mitigation techniques for multimedia services in downlink orthogonal frequency-division multiplexing mobile cellular systems. Performance of the proposed algorithms is evaluated in terms of user quality-of-service and system spectral efficiency. It is shown that the best subcarrier allocation scheme with interference mitigation and macrodiversity techniques gives significant performance gains in terms of system spectral efficiency. Furthermore, sharing the system bandwidth among real-time stream-type voice and bursty data services can support much larger system loads than having a hard division. [ABSTRACT FROM AUTHOR]

Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper investigates the base station (BS) selection (or anycast) problem in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes) is considered. Each source node must send all its locally generated data to only one of the BSs. To maximize network lifetime, it is essential to optimally match each source node to a particular BS and find an optimal routing solution. A polynomial time heuristic is proposed for optimal BS selection and anycast via a sequential fixing procedure. Through extensive simulation results, it is shown that this algorithm has excellent performance behavior and provides a near-optimal solution. [ABSTRACT FROM AUTHOR]

In this paper, we present a unified approach for the computation of the outage probability, the level crossing rate (LCR), and the average outage duration (AOD) of selection combining (SC) in the presence of multiple cochannel interferences and under both minimum signal-to-interference ratio (SIR) and desired signal power constraints. We consider three selection algorithms, namely, 1) the best signal power algorithm; 2) the best SIR algorithm; and 3) the best total power (desired plus interference) algorithm. As a specific application example, we analyze the three algorithms for a low-complexity dual-branch SC receiver subject to multiple interferers over Rayleigh fading channels. When applicable, the new results are compared to those previously reported in the literature dealing with the outage probability, AOD, and LCR of 1) interference-limited systems and 2) power-limited systems. Numerical examples show that the minimum desired signal power constraint induces a floor to the outage probability, AOD, and LCR performance measures. They also show that the best SIR algorithm provides the best outage probability and AOD performance for low average SIR. On the other hand, the best signal power algorithm and the best S + I algorithm outperform the best SIR algorithm for high average SIR. It is also shown that the best SIR algorithm tends to have more outage level crossings. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of two control parameters of the Universal Mobile Telecommunications System (UMTS) handoff algorithm on the total peak base station (BS) transmit power required per mobile station (MS) to satisfy a prescribed outage probability. Denoting the set of BSs supporting an MS in soft handoff (SH) as the active group, the first parameter n is the maximum allowed size of the active group. The second, denoted r, is the upper limit on the difference between the path loss of the dominant BS and that of any other member of the active group, where the term "dominant" refers to the BS with the lowest path loss to the MS. It was assumed that the MS is equipped with a Rake receiver capable of performing "maximal ratio combining" of the signals it receives from the transmitting BSs. General analytical derivations along with results derived for specific situations through numerical integration are presented. [ABSTRACT FROM AUTHOR]

This paper deals with a class of power control problems where the system link gains are assumed to be time varying and the signal-to-interference ratio (SIR) estimates are allowed to be corrupted with bounded noises. A simple control algorithm is devised by applying a distributed, fixed step approach. It is a feedback algorithm that requires only local information. By modifying the distributed, fixed step power control algorithm proposed by Sung and Wong, we obtain here a more robust version that can handle time varying link gains and measurement noises. The convergence property of the new algorithm is established and simulation studies were carried out to show that it is effective. [ABSTRACT FROM AUTHOR]

This paper provides mobility estimation and pree-diction for a variant of the GSM network that resembles an ad hoc wireless mobile network in which base stations and users are both mobile. We propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user's next mobile base station from the user's location, heading, and altitude, to improve connection reliability and bandwidth efficiency of the underlying system. Our analysis demonstrates that our algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation. [ABSTRACT FROM AUTHOR]

The focus of this paper is to analyze the throughput performance of TCP Thhoe and Reno on a differentiated services network with correlated wireless losses. An analytical model of TCP on a wireless link with differentiated services (DiffServ) based on the packet train model is developed. The network model is based on the state dependent arrival process. A major contribution of this paper is an analytical model combining the performance of TCP throughput and DiffServ leading to a model that represents an almost complete network scenario. It is shown that DiflServ in a wireless channel with correlated error losses is possible if the prob' ability of the channel changing from a good state to a bad state is less than a particular value. It is also shown that TCP Reno has a higher sensitivity to DiffServ than Tahoe. Our analytical model is validated through a number of simulations. [ABSTRACT FROM AUTHOR]

Power control has been widely studied and shown to be crucial for the capacity and performance of direct-sequence code-division multiple-access (DS-CDMA) systems. Practical implementations typically employ fast closed-loop power control, where transmitters adjust their transmit powers according to commands received in a feedback channel. The loop delay resulting from the measurements, processing, and transmission of the power control commands can result in oscillations of the transmission powers and lead to degradation in the system performance. In this paper we present new adaptive closed-loop power control algorithms that are able to alleviate the effect of the loop delay. The algorithms are based on self-tuning controllers designed for a log-linear model of the power control process. We carried out computational experiments on a DS-CDMA network using the distributed constrained power control (DCPC) as a reference algorithm. Practical versions of the algorithms are also provided and they were compared with the fixedstep power control (FSPC) algorithm employed in the IS-95 and WCDMA systems. The numerical results indicate that our algorithms can significantly improve the radio network capacity without any increase in power control signaling. [ABSTRACT FROM AUTHOR]

In power control, the convergence rate is one of the most important criteria that can determine the practical applicability of a given algorithm. The Convergence rate of power control is especially important when propagation and traffic conditions are changing rapidly. To track these changes, the power control algorithm must converge quickly. The purpose of this paper is to generalize the existing power control framework such that we can utilize partially known link gain information in improving the convergence speed. For the purpose, block power control (BPC) is suggested with its convergence properties. BPC is centralized within each block in the sense that it exchanges link gain information within the same block. However, it is distributed in a block-wise manner, and no information is exchanged between different blocks. Depending on availability of link gain information, a block can be any set of users, and can even consist of a single user. Computational experiments are carried out on a direct-sequence code-division multiple-access system, illustrating how BPC utilizes available link gain information in increasing the convergence speed of the power control. [ABSTRACT FROM AUTHOR]