Biogeography-Based Optimization Applied to Wireless Communications Problems

Biogeography-Based Optimization Applied to Wireless Communications Problems

Sotirios K. Goudos (Aristotle University of Thessaloniki, Greece)
Copyright: © 2018 |Pages: 14
DOI: 10.4018/978-1-5225-2255-3.ch519
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Introduction

The Evolutionary Algorithms (EAs) mimic behaviour of biological entities and they are inspired from Darwinian evolution in nature. The EAs have been extensively studied and applied to several real-world engineering problems. Biogeography-based optimization (BBO) (Simon, 2008) is a recently introduced evolutionary algorithm. BBO is based on mathematical models that describe how species migrate from one island to another, how new species arise, and how species become extinct. The way the problem solution is found is analogous to nature’s way of distributing species. In the BBO approach there is a way of sharing information between solutions (Simon, 2008), similar to the other evolutionary algorithms such as GAs, DE, and PSO. This feature makes BBO suitable for the same types of problems that the other algorithms are used for, namely high-dimensional data. Additionally, BBO has some unique features, which are different from those found in the other evolutionary algorithms. For example, quite different from GAs, DE and PSO, the set of the BBO’s solutions is maintained from one generation to the next and is improved using the migration model, where the emigration and immigration rates are determined by the fitness of each solution. These differences can make BBO outperform other algorithms (Simon, 2008). BBO has been applied successfully to several real world engineering problems (Ashrafinia, Pareek, Naeem, & Lee, 2011; Bhattacharya & Chattopadhyay, 2010; Boussaïd, Chatterjee, Siarry, & Ahmed-Nacer, 2011; S. K. Goudos et al., 2012; Jamuna & Swarup, 2011; Kankanala, Srivastava, Srivastava, & Schulz; Mandal, Bhattacharya, Tudu, & Chakraborty, 2011; Rathi, Agarwal, Sharma, & Jain, 2011; Silva, dos S Coelho, & Freire, 2010).

The purpose of this chapter is to briefly describe the BBO algorithm and present its application to antenna and wireless communications design problems. This chapter presents results from design cases that include patch antenna, linear antenna array, and a Partial Transmit Sequence (PTS) scheme for OFDM signals based on BBO. The chapter is supported with an adequate number of references. This chapter is subdivided into five sections. The “Background” Section presents the issues, problems, and trends with BBO. Then we briefly present the main BBO algorithm. In the next Section, we describe the design cases and present the numerical results. An outline of future research directions is provided in the following Section while in the “Conclusion” Section we conclude the chapter and discuss the advantages of using a BBO-based approach in the design and optimization of wireless systems and antennas. Finally, an “Additional Reading Section” gives a list of readings to provide the interested reader with useful sources in the field.

Key Terms in this Chapter

Orthogonal Frequency-Division Multiplexing (OFDM): A method of encoding digital data on multiple carrier frequencies.

Genetic Algorithms: A stochastic population-based global optimization technique that mimics the process of natural evolution.

Digital Audio Broadcasting (DAB): A digital radio technology for broadcasting radio stations.

Wireless Local Area Network (WLAN): A network in which a mobile user can connect to a local area network (LAN) through a wireless (radio) connection. Most modern WLANs are based on IEEE 802.11 standards, marketed under the Wi-Fi brand name.

Sidelobe Level (SLL): The ratio, usually expressed in decibels (dB), of the amplitude at the peak of the main lobe to the amplitude at the peak of a side lobe.

Mainlobe Beamwidth: In a radio antenna's radiation pattern, the main lobe, or main beam is the lobe containing the maximum power. The beamwidth of the main lobe is the width of the main lobe specified by the angles between the points on the side of the lobe where the power has fallen to zero.

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