In this semi-tutorial paper, a comprehensive survey of closest-point search methods for lattices without a regular structure is presented. The existing search strategies are described in a unified framework, and differences between them are elucidated. An efficient closest-point search algorithm, based on the Schnorr-Euchner variation of the Pohst method, is implemented. Given an arbitrary point x ∈ R m and a generator matrix for a lattice Λ, the algorithm computes the point of Λ that is closest to x. The algorithm is shown to be substantially faster than other known methods, by means of a theoretical comparison with the Kannan algorithm and an experimental comparison with the Pohst algorithm and its variants, such as the recent Viterbo-Boutros decoder. Modifications of the algorithm are developed to solve a number of related search problems for lattices, such as finding a shortest vector, determining the kissing number, computing the Voronoi-relevant vectors, and finding a Korkine-Zolotareff reduced basis.

A comparative study of state-of-the-art behavioral models for microwave power amplifiers (PA) is presented in this paper. After establishing a proper definition for accuracy and complexity for power amplifier behavioral models, a short description on various behavioral models is presented. The main focus of this paper is on the modeling accuracy as a function of computational complexity.Data is collected from measurements on two PA's -a general purpose amplifier and a Doherty PA designed for WiMAX -and at different output power levels. The models are characterized in terms of accuracy and complexity for both in-band and outof-band error. The results show that the generalized memory polynomial behavioral model has the best tradeoff for accuracy vs complexity.

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