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This paper studies two of the available heuristic algorithms to optimize the digital broadcasting network's planning. Particle Swarm Optimization (PSO) and Simulated Annealing (SA) are compared working in different OFDM modes. These algorithms manipulate the information of the network with static delays in order to maximize the covered area as well as possible at minimum cost. Particle Swarm Optimization...
This paper presents and compares different configurations of several heuristic optimization methods with the aim of seeking the one with the best performance when applied to phase synthesis of reflectarray antennas. This phase synthesis is a hard task and improving the synthesis method can result in significant reductions in the associated computational cost. The performance of algorithms such as...
Terrestrial digital broadcasting networks for digital video broadcasting (DVB) systems, such as DVB-T or DVB-T2, can be either multi-frequency (MFN) or single frequency (SFN). Regarding the SFN, the use of the spectrum is more efficient, and receiving locations can be served by several transmitters working at the same frequency. Moreover, DVB receivers based on OFDM modulation schemes can succeed...
Population-based optimization algorithms are widely used in multiple research areas to optimize different kinds of problems. Commonly, they have been successfully applied to low and medium size search spaces in order to tune or adjust several design parameters. Unfortunately, population-based algorithms can require too much CPU time to find a nearly optimal solution as the number of dimensions of...
One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in IR such as Precision at n, Mean Average Precision and Normalized Discounted Cumulative Gain. In this work we propose a new learning-to-rank method, referred as RankPSO. This algorithm is based on Particle Swarm Optimization...
In this work, classical Particle Swarm Optimization (PSO) based schemes have been appropriately modified by introducing a selection operator commonly used in Genetic Algorithms (GA), the tournament selection strategy, and the hybrid approaches proposed have been successfully applied to planar arrays complex synthesis, considering two different situations for the antennas: planar arrays divided or...
A planning tool that combines the strengths of a propagation prediction tool, CINDOOR, and a particle swarm optimization algorithm (PSO) is presented in this work when applied to optimize wireless networks resources prior to their deployment. For an arbitrary scenario, the approach proposed performs channel allocation, choosing the best set of access points (APs) to be used, including their activation...
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