W. Wiesbeck

Bio: W. Wiesbeck is an academic researcher. The author has contributed to research in topics: Network planning and design & Cellular network. The author has an hindex of 1, co-authored 1 publications receiving 49 citations.

Automatic base station placement and dimensioning for mobile network planning

Abstract: This paper presents an innovative algorithm for automatic base station placement and dimensioning. A highly efficient optimization strategy forms the core of the proposed algorithm that determines the number of base stations, their sites, and parameters to achieve a high-quality network that meets the requirements of area coverage, traffic capacity, and interference level, while trying to minimize system costs, including the frequency and financial costs. First, the hierarchical approach is outlined and it is applied to place base stations (BSs) for a large-scale network design. Also a fuzzy expert system is developed to exploit the expert experience to adjust BS parameters, e.g., the transmitted power, to improve the network performance. Simulation results are presented and analyzed.

Genetic approach with a new representation for base station placement in mobile communications

Abstract: In this paper, we find the best base station placement using a genetic approach. A new representation describing base station placement with a real number is proposed, and new genetic operators are introduced. This new representation can describe not only the locations of the base stations but also the number of those. Considering both coverage and economic efficiency, we also suggest a weighted objective function. Our algorithm is applied to an obvious optimization problem and then is verified. Moreover, our approach is tried in an inhomogeneous traffic density environment. The simulation result proves that the algorithm enables one to find near optimal base station placement and the efficient number of base stations.

Relay Station Placement in IEEE 802.16j Dual-Relay MMR Networks

Abstract: Cooperative relaying is one of the most effective techniques in coverage extension and capacity enhancement by virtue of spatial diversity. To fully explore the benefits of adopting relay stations (RSs), a vital issue is the placement of RSs by jointly considering an advanced coding scheme. In this paper, we aim to provide a general framework for solving the minimum cost RS placement problem in 802.16J Mobile Multi-hop Relay (MMR) networks. We first introduce a novel dual-relay architecture, where all the users, i.e., the mobile stations (MSs) and the fixed subscriber stations (SSs), are connected to the BS via two active RSs through decoded-and-forwarding scheme. We will then demonstrate that the most significant advantages of the dual-relay architecture lie in the ability of achieving high throughput for the systems. In addition, the users can be subject to better fault tolerance, robustness, and power saving. We formulate the dual- relay RS placement problem, and solve it through a two-phase algorithm to deal with the NP-hardness. Numerical analysis is conducted to evaluate the performance gain due to cooperative RS placement in the proposed framework, and demonstrate that the proposed approach can lead to a well acceptable solution compared with that by exhaustively searching.

Globally optimal transmitter placement for indoor wireless communication systems

Abstract: A global optimization technique is applied to solve the optimal transmitter placement problem for indoor wireless systems. An efficient pattern search algorithm - DIviding RECTangles (DIRECT) of Jones et al.- has been connected to a parallel three-dimensional radio propagation ray tracing modeler running on a 200-node Beowulf cluster of Linux workstations. Surrogate functions for a parallel wideband code-division multiple-access (WCDMA) simulator were used to estimate the system performance for the global optimization algorithm. Power coverage and bit-error rate are considered as two different criteria for optimizing locations of a specified number of transmitters across the feasible region of the design space. This paper briefly describes the underlying radio propagation and WCDMA simulations and focuses on the design issues of the optimization loop.

The determination of base station placement and transmit power in an inhomogeneous traffic distribution for radio network planning

Abstract: In this paper, the base station placement is automatically determined using genetic approach, and the transmit power is estimated considering the interference situation in the case of interference-dominant systems. For applying a genetic algorithm to the base station placement problem, a new representation scheme with real numbers is proposed. And, corresponding operators such as crossover and mutation are introduced. A weighted objective function is designed for performing the cell planning coverage, cost-effectively. To verify the proposed algorithm, the situation where the optimum positions and number of base stations are obvious is considered. The proposed algorithm is applied to an inhomogeneous traffic density environment, where a base station's coverage may be limited by offered traffic loads. Simulation result proves that the algorithm enables us to find near optimal base station placement and the efficient number of base stations.

Particle swarm optimization for base station placement in mobile communication

Abstract: The tremendous growth in the demand for mobile services results in an explosion in base station (BS) density and network complexity, making the conventional manual planning processes highly inefficient. In this paper, we give some novel adaptation to the recent bio-inspired optimization approach, Particle Swarm Optimization (PSO), to form a suitable algorithm for the base station placement problem. Considering the two most important factors simultaneously, coverage and economy efficiency, we can get a Pareto optimal set by using the Divided Range Multiobjective Particle Swarm Optimization (DRMPSO) which is performed in distributed computing. The Pareto optimal set is a set of solutions which are optimal with respect to constrained conditions and non-inferior to each other. The simulation results show that the proposed approach is efficient and effective, especially for large-scale network design.