In this paper switched beam smart antenna systems are investigated to improve the performance of wireless networks. The microstrip technology of antenna arrays with Butler matrix topology as a beam-former is used to implement the switched beam smart antenna system. The optimum design of a 8×8 planar Butler matrix array, operating at 2.4 GHz for WLAN applications. Systems design and optimization was based on computer simulations.

An efficient moment-method algorithm for analyzing helix antenna is presented. This algorithm is developed based on solving the helix integral equations using two categories of continuous wavelets-like basis functions, Biorthogonal and Orthogonal wavelets. In the first part, the current in the helix antenna is obtained using the method of moments with the triangle basis and pulse testing functions. Secondly, the orthogonal (Daubechies and Symlets) and the biorthogonal (spline generated biorthogonal) wavelets are used and compared in solving the helix integral equation. The grounds of comparison between the two categories are accurate in characterizing the induced current, matrix sparsity, relative error and computation time. The advantages and limitations of solving integral equations with each of the two wavelet categories are discussed. The numerical example is provided to demonstrate the validity and applicability of our proposed algorithm which can be easily implemented to produce a desired accuracy.

Using Daubechies wavelet with one, two, three, and four vanishing moments, basis functions for the efficient solution of electromagnetic integral equations are studied. Due to the vanishing moments, the moment matrices resulting in these problems are sparsified by wavelet, and consequently, the solution can be obtained rapidly. The microstrip line is examined in order to demonstrate the advantages of this suggested wavelet-moments method over the traditional moment method. To demonstrate the effectiveness and accuracy of the proposed technique, numerical results for error relative for different vanishing moments of Daubechies wavelets are presented. It is found that Daubechies wavelets with larger number of vanishing moments generally give higher accuracy. NOMENCLATURE MoM Method of Moments TEM Transverse electromagnetic dbN Daubechies wavelet with N vanishing moments nfb Number of basic functions nfe Number of testing functions Thr Threshold IM Impedance Matrix CPU Central Processing Unit

The relentless evolution of communication systems, driven by the demands of 5G and the impending 6G networks, necessitates heightened data rates and spectral efficiency. orthogonal frequency division multiplexing (OFDM), a form of multicarrier modulation employed in multi-input multi-output (MIMO) systems, stands as a pivotal technology. Yet, OFDM grapples with challenges, notably the peak-to-average power ratio (PAPR) issue. Selective mapping (SLM) has been a favored technique for mitigating PAPR in OFDM, albeit challenged by computational complexities in its pursuit of discovering optimal phase factors. This paper pioneers a transformative approach by integrating metaheuristic algorithms genetic algorithm (GA), particle swarm optimization (PSO), and the innovative fireworks algorithm (FWA) into SLM for PAPR reduction while minimizing computational complexity. Simulation results not only affirm the efficacy of SLM-based techniques but also spotlight the potential of metaheuristic algorithms in addressing PAPR challenges in modern communication systems. The study transcends single-antenna systems, extending to MIMO-OFDM systems based on WiMAX standards, validating the efficacy of these techniques in multi-antenna configurations. Crucially, the FWA, proposed for the first time in this paper, emerges as a robust candidate, striking an enviable balance between computational efficiency and performance, achieving a notable PAPR reduction with a favorable search number.

In this paper, it is attempted to approach a fast efficient algorithm for solving the famous Hallen's and Pocklington's integral equations, regarding the current distribution on a finite-length linear thin wire antenna. Here, the conventional moment method in conjunction with wavelet basis functions was used to obtain the current distribution of the antenna. The aim of this work is first to introduce the application of wavelet in electromagnetic scattering, secondly a comparison of the two method of analysis the thin wire antenna. By using the wavelet expansion, wavelets as basis and testing functions, a sparse matrix is generated from the previous moment method dense matrix. A sparsely filled matrix is easier to store and invert. The result extracted from Pocklington's integral equation gives better convergence at the feeding point, though it takes more time to be computed because of the complexity in Pocklington's equation. Results are compared to the previous work done and published, excellent results are obtained.