Ulrich Killat

On the statistical properties of deterministic simulation models for mobile fading channels

Rices (9144, 1945) sum of sinusoids can be used for an efficient approximation of colored Gaussian noise processes and is therefore of great importance to the software and hardware realization of mobile fading channel models. Although several methods can be found in the literature for the computation of the parameters characterizing a proper set of sinusoids, less is reported about the statistical properties of the resulting (deterministic) simulation model. In this paper, not only is the simulation models amplitude and phase probability density function (PDF) investigated, but also higher order statistics [e.g., level-crossing rate (LCR) and average duration of fades (ADFs)]. It is shown that due to the deterministic nature of the simulation model, analytical expressions for the PDF of the amplitude and phase, autocorrelation function (ACF), crosscorrelation function (CCF), LCR, and ADFs can be derived. We also propose a new procedure for the determination of an optimal set of sinusoids, i.e., the method results for a given number of sinusoids in an optimal approximation of Gaussian, Rayleigh, and Rice processes with given Doppler power spectral density (PSD) properties. It is shown that the new method can easily be applied to the approximation of various other kinds of distribution functions, such as the Nakagami (1960) and Weibull distributions. Moreover, a quasi-optimal parameter computation method is presented.

A deterministic digital simulation model for Suzuki processes with application to a shadowed Rayleigh land mobile radio channel

We present a novel computer simulation model for a land mobile radio channel. The underlying channel model takes for granted non-frequency-selective fading but considers the effects caused by shadowing. For such a channel model we design a simulation model that is based on an efficient approximation of filtered white Gaussian noise processes by finite sums of properly weighted sinusoids with uniformly distributed phases. In all, four completely different methods for the computation of the coefficients of the simulation model are introduced. Furthermore, the performance of each procedure is investigated on the basis of two quality criteria. All the presented methods have in common the fact that the resulting simulation model has a completely determined fading behavior for all time. Therefore, the simulation model can be interpreted as a deterministic model that approximates stochastic processes such as Rayleigh, log-normal, and Suzuki (1977) processes.

An extended Suzuki model for land mobile satellite channels and its statistical properties

This paper deals with the statistical characterization of a stochastic process which is a product of a Rice and lognormal process. Thereby, we consider the more general case where the two Gaussian noise processes describing the Rice process are correlated. The resulting process are named as extended Suzuki process, which can be used as a suitable statistical model for describing the fading behavior of large classes of frequency nonselective land mobile satellite channels. In particular, the statistical properties (e.g., probability density function (pdf) of amplitude and phase, level-crossing rate, and average duration of fades) of the Rice process with cross-correlated components as well as of the proposed extended Suzuki process are investigated. Moreover, all statistical model parameters are optimized numerically to fit the cumulative distribution function and the level-crossing rate of the underlying analytical model to measured data collected in different environments. Finally, an efficient simulation model is presented which is in excellent conformity with the proposed analytical model.

A new strategy for the application of genetic algorithms to the channel-assignment problem

The channel-assignment problem in cellular radio networks is known to belong to the class of NP-complete optimization problems. So far, this problem has been solved by heuristic assignment strategies or by the application of combinatorial optimization tools like simulated annealing or neural networks. We propose a new powerful approach to the channel-assignment problem by combining the two mentioned groups of solution techniques. The results obtained by the application to a well-known benchmark problem reveal that this absolutely new strategy clearly outperforms the already existing algorithms.

- The random waypoint city model -: user distribution in a street-based mobility model for wireless network simulations

In this paper we present a new mobility model for mobile network simulations and evaluate user distributions in a real topology using different parameters.

Optimal Virtual Network Embedding: Node-Link Formulation

Network Virtualization is claimed to be a key component of the Future Internet, providing the dynamic support of different networks with different paradigms and mechanisms in the same physical infrastructure. A major challenge in the dynamic provision of virtual networks is the efficient embedding of virtual resources into physical ones. Since this problem is known to be NP-hard, previous research focused on designing heuristic-based algorithms; most of them either do not consider a simultaneous embedding of virtual nodes and virtual links, or apply link-path formulation, leading to non-optimal solutions. This paper proposes an integer linear programming (ILP) formulation to solve the online virtual network embedding problem as a result of an objective function striving for the minimization of resource consumption and load balancing. To this end 3 different objective functions are proposed and evaluated. This approach applies multi-commodity flow constraint to accomplish a node-link formulation that optimizes the allocation of physical network resources. This proposal is evaluated against state of the art heuristics. The performance of the heuristics related to Virtual Network (VN) request acceptance ratio is, at least, 30% below the one of the Virtual Network Embedding Node-Link Formulation (VNE-NLF) method. From the three cost functions evaluated, the Weighted Shortest Distance Path (WSDP) is the one which embeds more VNs and also requires, on average, less physical resources per embedding.

A new and optimal method for the derivation of deterministic simulation models for mobile radio channels

Stochastic multipath propagation models for indoor and outdoor mobile radio channels are in general derived by employing coloured Gaussian noise processes. Efficient design and realization techniques of such processes are therefore of particular importance in the area of mobile radio channel modelling. This paper presents especially for complex coloured Gaussian noise processes a deterministic simulation model that is based on Rices (1944) sum of sinusoids. A new method is introduced for the derivation of an optimal set of sinusoids, i.e., the procedure is such that for a given number of sinusoids an optimal approximation of Gaussian (Rayleigh, Rice) processes with given Doppler power spectral density shapes is obtained. Moreover, the statistical properties of the resulting (deterministic) simulation model are investigated.

Modeling, analysis, and simulation of nonfrequency-selective mobile radio channels with asymmetrical Doppler power spectral density shapes

What terrestrial and satellite land mobile radio channels have in common is that they are usually assumed to be nonfrequency selective. For such fading channels, a highly flexible analytical model is presented. Our model takes into account short-term fading with superimposed long-term lognormal variations of the local mean value of the received signal. It is assumed that the introduced complex stochastical process, which is used for modeling the short-term fading behavior, has a Doppler power spectral density with an asymmetrical shape. Closed solutions are presented showing the influence of asymmetrical Doppler power spectral density shapes on the statistical properties of the proposed channel model. A numerical optimization procedure is shown for the optimization of the model parameters in order to fit the statistics of the analytical model [amplitude probability density function (PDF), level-crossing rate (LCR), and average duration of fades (ADF)] to measurement results of an equivalent land mobile satellite channel for light and heavy shadowing environments. Finally, from the analytical model, an efficient simulation model is derived that enables the simulation of such realistic land mobile satellite channel scenarios on a digital computer.

Bandwidth Trading in Unstructured P2P Content Distribution Networks

Bandwidth trading schemes give peers an incentive to provide upload bandwidth to other peers in a P2P network for fast file distribution. A popular example is the tit-for-tat strategy used in the BitTorrent protocol. Although this game theoretical scheme provides an incentive to peers to contribute resources to the network it does not prevent unfairness and the performances of peers vary considerably. Therefore, we propose two new trading schemes, which are based on pricing. One uses explicit price information whereas the other scheme uses the download rates from other peers as the price. For both distributed algorithms the stable point provides a fair resource allocation as well as a Nash equilibrium, i.e. fairness is preserved although peers behave selfishly and try to maximise their own download rates only. We compare both pricing schemes with BitTorrent in simulations of static and dynamic networks. The pricing algorithms outperform BitTorrent with respect to fairness. With explicit prices the download rates converge faster to the fair equilibrium than with implicit ones

Bandwidth trading in BitTorrent-like P2P networks for content distribution

Bandwidth trading schemes give peers an incentive to provide upload bandwidth to other peers in a P2P network for fast file distribution. A popular example is the tit-for-tat strategy used in the BitTorrent protocol. Although this game theoretical scheme provides an incentive to peers to contribute resources to the network it does not prevent unfairness and the performances of peers vary considerably. Therefore, we propose two new trading schemes, which are based on pricing. One uses explicit price information whereas the other scheme uses the download rates from other peers as the price. For both distributed algorithms the stable point provides a fair resource allocation as well as a Nash equilibrium. Thus, fairness is preserved although peers behave selfishly and try to maximize their own download rates only. We compare both pricing schemes with BitTorrent in simulations of static and dynamic networks. In BitTorrent peers receive different download rates even if they provide the same upload bandwidth. Furthermore, peers with small upload capacities compared to others receive considerably more than what they contribute. The pricing algorithms outperform BitTorrent with respect to fairness. With both algorithms a peer receives a download performance proportional to its upload capacity. With explicit prices the download rates converge faster to the fair equilibrium than with implicit ones.