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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]

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]

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]

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 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]

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]

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]

Sensing coverage is an important issue in wireless mobile sensor networks. The strategy of how to deploy sensor nodes in an environment, particularly in an unknown expanse, will affect the utility of the network just like the quality of communication. In this paper, using the concept of molecule spreading from physics, we present an efficient method for sensor deployment, assuming that global information is not available. Our algorithm, i.e., Self-Deployment by Density Control (SDDC), uses density control by each node to concurrently deploy sensor nodes. We make the nodes form clusters to achieve area density balance. The characteristics in SDDC are concurrent multisensor moving, distributed operation, localized calculation, and self-deployment. Simulations show its good performances compared to the incremental self-deployment algorithm. [ABSTRACT FROM AUTHOR]

Call admission control (CAC) strongly influences the performance of 3G/4G spread spectrum systems because it determines the number of active users that are admitted to the network, i.e., influences spectral efficiency. A novel air interface CAC algorithm is introduced in this paper. It optimizes the utilization of radio resources and provides real-time adaptation to the radio channel with generalized multiplicative fading. Users are handled as memory-less traffic sources. The suggested CAC method was evaluated for lognormal fading and ON/OFF traffic. [ABSTRACT FROM AUTHOR]

Design of efficient dynamic channel allocation (DCA) algorithms has an important impact on performance optimization of wireless mobile networks. The previously proposed DCA algorithms are shown to have good performance but only for certain services and under certain load conditions. Within this paper, we propose a new cost-function-based DCA algorithm, which is fully adaptive to service and load conditions and includes some well-known DCA algorithms such as Random, Minimum Interference, and Autonomous Reuse Partitioning DCA as special cases. By using dynamic system-level simulations, we show that the algorithm provides the same or substantially better performance than these DCA algorithms, with low signalization and computation overhead. We also show the general limits of DCA algorithms in the presence of other interference reduction techniques such as power control and smart antennas. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of blind channel estimation for single-input-single-output (SISO) orthogonal frequency-division multiplexing (OFDM) system via second-order statistics only. Based on the assumption that the transmitted symbols are independent and identically distributed, we develop a simple blind channel estimation technique for OFDM systems by utilizing a generalized linear nonredundant block precoding. Instead of using partial information from the signal covariance matrix, as done in previous works where a specific precoder is designed and only one column of the signal covariance matrix is exploited, our work jointly considers all the information contained in the signal covariance matrix. Compared to the popular subspace-based blind channel estimation methods, the proposed algorithm is much more computationally efficient. A design criterion of the precoders by which the performance can be improved is provided, and the closed-form stochastic Cramér-Rao bound is derived. The numerical results clearly show the effectiveness of our proposed algorithm, as well as its improvement over the existing techniques. [ABSTRACT FROM AUTHOR]

This paper examines the problem of quality-of-service group communications in a heterogeneous network, which consists of multiple mobile ad hoc networks attached to the backbone Internet. A heuristic multicast algorithm named delay and delay variation multicast algorithm (DDVMA) is proposed. DDVMA is designed for solving the delay- and delay-variation-bounded multicast tree problem, which has been proved to be NP-complete. It can find a multicast tree satisfying the multicast end-to-end delay constraint and minimizing the multicast delay variation. Two concepts, which can help the DDVMA achieve better performance in terms of multicast delay variation than the delay and delay variation constraint algorithm that is known to be the most efficient so far, are proposed, namely, 1) the proprietary second shortest path and 2) the partially proprietary second shortest path. An analysis is given to show the correctness of DDVMA, and simulations are conducted to demonstrate the performance improvement of DDVMA in terms of multicast delay variation. It is also shown that the strategy employed by DDVMA is also applicable to handling the mobility of mobile hosts in a heterogeneous network. [ABSTRACT FROM AUTHOR]

One of the main problems facing accurate location in wireless communication systems is nonline-of-sight (NLoS) propagation. In this paper, we propose a novel location technique that estimates the true, or line-of-sight (LoS), ranges based on NLoS range measurements. This approach utilizes a constrained nonlinear optimization approach, when range measurements are available from three base stations (BSs) only. Bounds on the NLoS error and the relationship between the true ranges are extracted from the geometry of the cell layout and the measured range circles to serve as constraints. Simulations studying the performance of the algorithm for different NLoS error distributions and BS configurations show that the location accuracy is significantly improved over traditional algorithms, even under highly NLoS conditions. [ABSTRACT FROM AUTHOR]

Positioning algorithms in cellular networks has become increasingly important as a means of supporting emerging services that require a sufficiently precise estimation of the position of the mobile terminal (MT) associated with a given base station (BS). Currently, even the most sophisticated positioning algorithms require at least three BSs to achieve satisfactory precision. This paper presents a novel algorithm that makes use of a single-BS antenna array to locate MTs in cellular networks. A triangulation technique is utilized and supported by some minimal information about the environment in the BS neighborhood. This algorithm is shown to perform well when operating in a microcellular environment with perfect channel-parameter estimation. The effect of finite resolution of the input parameters is also investigated. The performance is analyzed for a universal mobile telecommunications system microcellular scenario through a three-dimensional deterministic channel model. Finally, the performance of the proposed positioning technique is compared to the well-known location method based on the time-of-arrival measurements at three different BSs. [ABSTRACT FROM AUTHOR]

We address cooperative caching in wireless networks, where the nodes may be mobile and exchange information in a peer-to-peer fashion. We consider both cases of nodes with large- and small-sized caches. For large-sized caches, we devise a strategy where nodes, independent of each other, decide whether to cache some content and for how long. In the case of small-sized caches, we aim to design a content replacement strategy that allows nodes to successfully store newly received information while maintaining the good performance of the content distribution system. Under both conditions, each node takes decisions according to its perception of what nearby users may store in their caches and with the aim of differentiating its own cache content from the other nodes'. The result is the creation of content diversity within the nodes neighborhood so that a requesting user likely finds the desired information nearby. We simulate our caching algorithms in different ad hoc network scenarios and compare them with other caching schemes, showing that our solution succeeds in creating the desired content diversity, thus leading to a resource-efficient information access. [ABSTRACT FROM PUBLISHER]

Wireless access points (APs) divide a plane into small areas where their coverage ranges overlap. A mobile device can be located within a particular small overlapped area based on the unique set of APs covering the device. We formally define an Optimal Loc-deployment problem for both coverage and area localization. Our objective is to deploy a minimum number of APs that provide full communication coverage while achieving the ability to locate a mobile device within a certain area no larger than a given accuracy parameter. We obtain a formula that precisely determines the optimal solution for more than half of the accuracy values. For the rest of the accuracy values, we propose an algorithm that will return an approximation whose difference to the optimal solution is less than \epsilon for any \epsilon > 0. Finally, we conduct extensive numerical evaluation and real experiments to validate our proposed solutions. [ABSTRACT FROM PUBLISHER]

The wireless mesh network (WMN) has recently emerged as a promising technology for next-generation wireless networking. In the WMN, it is crucial to support mobile users roaming around the network without service interruption. This consideration motivates us to develop an efficient fast handoff approach using distributed computing technology. Particularly, we propose a mobile agent (MA).based handoff architecture for the WMN, where each mesh client has an MA residing on its registered mesh router to handle the handoff signaling process. To guarantee quality of service (QoS) and achieve differentiated priorities during the handoff, we develop a proportional threshold structured optimal effective bandwidth (PTOEB) policy for call admission control (CAC) on the mesh router, as well as a genetic algorithm (GA)-based approximation approach for the heuristic solution. The simulation study shows that the proposed CAC scheme can obtain a satisfying tradeoff between differentiated priorities and the statistical effective bandwidth in a WMN handoff environment. [ABSTRACT FROM AUTHOR]

We study the problem of accurate localization of static or mobile nodes in a wireless ad hoc network using the distance estimates of a group of untrusted anchors within the communication range of the nodes. Some of the anchors may be malicious and may independently lie about the distance estimate. The malicious anchors may also collude to lie about the distance estimates. In both cases, accurate node localization may be seriously undermined. We propose a scheme that performs accurate localization of the nodes in the network despite the presence of such malicious anchors. We also show how to identify most of these malicious anchors. In the case where measurements are error free, we derive a critical threshold B for the number of malicious anchors that can be tolerated in the localization process without undermining accuracy. We also show how to correctly localize a node and identify all the malicious anchors in this setting. In the presence of measurement errors, we propose a convex optimization-based localization scheme that can accurately localize a node, as long as the number of malicious anchors in its communication range is no more than B. Simulation results show that our schemes are very effective. When the measurements are error prone and the number of malicious anchors is no more than B, our scheme localizes a node with an error less than 8% and is also able to identify a significant number of malicious anchors. Our schemes guarantee that a true anchor is not identified as malicious. [ABSTRACT FROM AUTHOR]

Several channel-allocation algorithms have been pro- posed in the literature for traditional cellular networks with static base stations (BS5), while not much attention has been given to channel-allocation problems for cellular networks where BSs are mobile. In cellular networks with mobile BSs (MBSs), the network topology is dynamic due to the mobility of the BSs. This makes the channel-allocation problem in such networks more challenging. Moreover, the MBSs may fail and degrade the performance of the cellular network. Therefore, it is desirable that the channel- allocation algorithm be fault tolerant. Thus, even in the presence of failure of the MBSs, the channel-allocation algorithm should work reasonably well. It is also desirable to design a channel-allocation approach that guarantees that the request from a mobile host (MH) is responded to in a timely manner. In this paper, a distributed dynamic channel-allocation algorithm that addresses these problems in cellular networks with MBSs is proposed. The proposed algorithm is fault tolerant and guarantees that the time to respond to an MH's request for supporting a call is upperbounded. The performance evaluation of the proposed algorithm shows that the proposed algorithm performs well, even in the presence of failure of the MBSs. [ABSTRACT FROM AUTHOR]

Scheduling plays an important role in providing quality of service (QoS) support to multimedia communications in various kinds of wireless networks, including cellular networks, mobile ad hoc networks, and wireless sensor networks. The authors propose a scheduling algorithm at the medium access control (MAC) layer for multiple connections with diverse QoS requirements, where each connection employs adaptive modulation and coding (AMC) scheme at the physical (PHY) layer over wireless fading channels. Each connection is assigned a priority, which is updated dynamically based on its channel and service status; the connection with the highest priority is scheduled each time. The authors' scheduler provides diverse QoS guarantees, uses the wireless bandwidth efficiently, and enjoys flexibility, scalability, and low implementation complexity. Its performance is evaluated via simulations. [ABSTRACT FROM AUTHOR]

Discusses the minimization of the total power transmitted over given discrete sets of available power levels subject to maintaining an acceptable signal quality for each mobile in a wireless system. Integer programming generalization; Iterative algorithm for solving integer programming problem; Variations of the iterative algorithms involving the addition and deletion of constraints.