A framework for positioning, navigation and tracking problems using particle filters (sequential Monte Carlo methods) is developed. It consists of a class of motion models and a general non-linear measurement equation in position. A general algorithm is presented, which is parsimonious with the particle dimension. It is based on marginalization, enabling a Kalman filter to estimate all position derivatives, and the particle filter becomes low-dimensional. This is of utmost importance for highperformance real-time applications. Automotive and airborne applications illustrate numerically the advantage over classical Kalman filter based algorithms. Here the use of non-linear models and non-Gaussian noise is the main explanation for the improvement in accuracy. More specifically, we describe how the technique of map matching is used to match an aircraft's elevation profile to a digital elevation map, and a car's horizontal driven path to a street map. In both cases, real-time implementations are available, and tests have shown that the accuracy in both cases is comparable to satellite navigation (as GPS), but with higher integrity. Based on simulations, we also argue how the particle filter can be used for positioning based on cellular phone measurements, for integrated navigation in aircraft, and for target tracking in aircraft and cars. Finally, the particle filter enables a promising solution to the combined task of navigation and tracking, with possible application to airborne hunting and collision avoidance systems in cars.

monitora region fortra$ tra versafl sensors ca be deployed to perform colla ora1= etafl$1 detection. Sucha sensor networka chievesa certaO level of detection performaR7 witha na$# cia1$ cost of deployment. This pa era ddresses this problem by proposingpan exposure a a mea6F6 of the goodness ofa deploymenta nd presents a asCfl1fl h for sequentia deployment in steps. Itillustra7fl tha the cost of deploymentca be minimized to a hieve the desired detection performaCR bya ppropria6$fl choosing the number of sensors deployed in ea h step.

Multielement system capacities are usually thought of as limited only by correlations between elements. It is shown here that degenerate channel phenomena called "keyholes" may arise under realistic assumptions which have zero correlation between the entries of the channel matrix H and yet only a single degree of freedom. Canonical physical examples of keyholes are presented. For outdoor environments, it is shown that roof edge diffraction is perceived as a "keyhole" by a vertical base array that may be avoided by employing instead a horizontal base array.

Collaboration in sensor networks must be fault tolerant due to the harsh environmental conditions in which such networks can be deployed. This paper focuses on finding algorithms for collaborative target detection that are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the network. Two algorithms, namely value fusion and decision fusion are identified first. When comparing their performance and communication overhead, decision fusion is found to become superior to value fusion as the ratio of faulty sensors increases.

This paper presents a demand-based engineering method for designing radio networks of cellular mobile communication systems. The proposed procedure is based on a forward-engineering method, the Integrated Approach to cellular network planning and is facilitated by the application of a new discrete population model for the traffic description, the Demand Node Concept. The use of the concept enables the formulation of the transmitter locating task as a Maximal Coverage Location Problem (MCLP), whichiswell known in economics for modeling and solving facility location problems. For the network optimization task, we introduced the Set Cover Base Station Positioning Algorithm (SCBPA), which is based on a greedy heuristic for solving the MCLP problem. Furthermore, we present the planning tool prototype ICEPT (Integrated Cellular network Planning Tool), which is based on these ideas and show a first result from a real world planning case.

Classical coverage models, adopted for second-generation cellular systems, are not suited for planning universal mobile telecommunication system (UMTS) base station (BS) location because they are only based on signal predictions and do not consider the traffic distribution, the signal quality requirements, and the power control (PC) mechanism. In this paper, we propose discrete optimization models and algorithms aimed at supporting the decisions in the process of planning where to locate new BSs. These models consider the signal-to-interference ratio as quality measure and capture at different levels of detail the signal quality requirements and the specific PC mechanism of the wideband CDMA air interface. Given that these UMTS BS location models are nonpolynomial (NP)-hard, we propose two randomized greedy procedures and a tabu search algorithm for the uplink (mobile to BS) direction which is the most stringent one from the traffic point of view in the presence of balanced connections such as voice calls. The different models, which take into account installation costs, signal quality and traffic coverage, and the corresponding algorithms, are compared on families of small to large-size instances generated by using classical propagation models.

We consider schemes for reuse-efficient packet access in wireless data networks. We show that computing the maximum ergodic packet arrival rate is NPhard. We give an upper bound on the maximum ergodic throughput in terms of the eigenvalues of matrices related to the path-gain matrix. We present simple, practical heuristic algorithms which exhibit good throughput and packet delay and report on results of preliminary simulations. More sophisticated algorithms that yield optimal throughput are also presented. A recent result of McKeown, Anantharam and Walrand on scheduling of input-queued switches is obtained as a byproduct. 1. Introduction This paper addresses schemes for reuse-efficient transmission in wireless packet data networks. Particular attention is paid to recent proposals (see for example [19]) for wireless data packet networks in which the medium access (MAC) layer protocol is: (i) deterministically scheduled. (ii) has good delay performance. (iii) provides near-optimal ch...

Sensing devices can be deployed to form a network for monitoring a region of interest. This paper investigates detection of a target traversing the region being monitored by using collaborative target detection algorithms among the sensors. The objective of the study is to develop a low cost sensor deployment strategy to meet a performance criteria. The paper defines a path exposure metric as a measure of goodness of deployment. It then gives a problem formulation for the random sensor deployment and defines cost functions that take into account the cost of single sensors and the cost of deployment. A sequential sensor deployment approach is then developed. The paper illustrates that the overall cost of deployment can be minimized to achieve the desired detection performance by appropriately choosing the number of sensors deployed in each step of the sequential deployment strategy.

If only good coverage is required in GSM networks, high frequency reuse factors can be used. In that case the network capacity is directly determined by the number of available time slots, and no advanced radio control algorithms are needed. If high capacity is required and fractional loading is used in GSM networks, advanced radio resource management algorithms are required. Sophisticated network simulators are needed for algorithm development in GSM base station systems. Also, finding out the capacity for accurate network planning is difficult without radio network simulators. In UMTS the need for an advanced radio network simulator will further increase because of new services, higher bit rates, multiplexing of services, and because of the possible asymmetric capacity requirement between uplink and downlink. Additionally, the UTRA WCDMA air interface is more dynamic than the GSM air interface, and therefore, optimised radio resource management algorithms need to be developed to fully exploit the WCDMA capabilities. The algorithm development for highly loaded dynamic networks is not possible without accurate modelling in computer simulations. In this paper the modelling principles of a WCDMA radio network simulator are presented.

: In this paper we present a fast ray-tracing technique with scalable approximation accuracy for field strength prediction in cellular mobile network planning. Automatic network design methods, like the Adaptive Base Station Positioning Algorithm (ABPA), [2, 3], perform a huge number of field strength estimations and require therefore a fast and accurate approximation. However, common prediction techniques either give only rough estimations or are too complex for fast evaluation, cf. [7]. The proposed new ray-tracing technique obtains its speed-up by taking advantage of the topological information inherent in the used triangulation data structure of the investigated terrain. By that, it is possible to apply simple mathematics and algorithms to trace individual rays. The applicability of the fast ray-tracing technique is demonstrated for both a single transmitter scenario and in conjunction with ABPA. Keywords: mobile communication, network planning, base station location, field stren...