Cent. Eur. J. Comp. Sci. • 2(1) • 2012 • 1-14 DOI: 10.2478/s13537-012-0001-0 Central European Journal of Computer Science Beam forming in smart antenna with improved gain and suppressed interference using genetic algorithm Research Article T. S. Ghouse Basha1∗, M. N. Giri Prasad2, P.V. Sridevi3 1 K.O.R.M.College of Engineering, Kadapa, Andhra Pradesh, India 2 J.N.T.U.College of Engineering, Anantapur, Andhra Pradesh, India 3 Department of ECE, AU College of Engineering, Andhra University, Visakha Patnam, Andhra Pradesh, India Received 21 September 2011; accepted 18 November 2011 Abstract: The most imperative process in smart antenna system is beam forming, which changes the beam pattern of an antenna for a particular angle. If the antenna does not change the position for the specified angle, then the signal loss will be very high. By considering the aforesaid drawback, here a new genetic algorithm based technique for beam forming in smart antenna system is proposed. In the proposed technique, if the angle is given as input, the maximum signal gain in the beam pattern of the antenna with corresponding position and phase angle is obtained as output. The length of the beam, interference, phase angle, and the number of patterns are the factors that are considered in our proposed technique. By using this technique, the gain of the system gets increased as well as the interference is reduced considerably. The implementation result exhibits the efficiency of the system in beam forming. Keywords: smart antenna • beam forming • genetic algorithm (GA) • phase angle • main beam © Versita Sp. z o.o. 1. Introduction Smart antenna system contains multiple antenna elements connected to a digital signal processor where a spatial filtering is performed [11, 15]. Smart antenna technology increases the directivity of the antenna beam to improve the signal at the desired receiver without causing any impedance to other radio users, or using multiple receive/transmit antenna channels simultaneously in order to enhance reliability for increasing the data capacity of the link [12]. Direction of arrival estimation and beam steering are the two important additional functions need to be satisfied by smart antennas or adaptive antennas along with their main function of effectively transmitting and receiving radio signals [5]. ∗ E-mail: [email protected] 1 Beam forming in smart antenna with improved gain and suppressed interference using genetic algorithm The gain of a smart antenna is normally greater than that of an Omni-directional antenna. Also, when compared to an omni-directional antenna, smart antenna has higher reachability i.e., a larger directional range [8]. Beam forming is the term used to define the application of weights to the inputs of an array of antennas to steer the reception of the antenna array in a particular direction, called the look direction or the main lobe [6, 22]. Beam forming techniques aims at enhancing the captured sound quality by using the diversity in the received signals of the microphone array depending on the location of the source and the hindrance [23]. The two significant functions of smart antennas are Direction of Arrival and Adaptive Beam forming [9, 16]. Adaptive beam forming systems uses an adaptive array processing for the creation of nulls in the direction of interference as well as powerful beams in the direction of desired user [13]. Due to the evolution of digital circuit design, the ultrasound beam forming system has moved from the analog era to the digital era. The computational flexibility of digital system allows the dynamic receive focusing to be performed in order to obtain better image quality [7]. Beam forming provides many advantages to antenna design. Space division multiple access (SDMA) is achieved since a beamformer can steer its look direction towards a particular signal. Other signals from diverse directions can reuse the same carrier frequency [5]. Smart antennas are utilized in performance analysis of MUSIC and LMS algorithms [4], Mobile and Base Stations in an OFDM/TDMA System [21]. In this paper a new technique was proposed using genetic algorithm that considers all essential factors for allocating signal in the particular position and angle with maximum signal gain. The rest of the paper is organized as follows. The related works are briefly reviewed in Section 2; proposed technique with sufficient mathematical models and illustrations are detailed in Section 3; implementation results are discussed in Section 4 and Section 5 concludes the paper. 2. Related works Some of the recent works related to beam forming in smart antenna are reviewed in this section. Haardt et al.[10] have utilized realistic channel and interference models for constructing and analyzing the space timing processing method with multiple antennas at the base station and/or mobile terminal. In addition to reliable evaluation of the link level performance of the smart antenna techniques, a more accurate spectral efficiency enhancement evaluation at the system level has been possible from the mapping between system and link level result. Shubair et al. [18] have proposed an adaptive beam forming and direction-of-arrival estimation based practical design of a smart antenna system. The MUSIC algorithm for recognizing the directions of the source signals falling on the sensor array containing smart antenna system has been used as the basis for assessing the direction-of-arrival (DOA). The LMS algorithm for directing the most important beam towards the preferred source signals has been used and deep nulls have been produced in the directions of interfering signals for achieving adaptive beam forming The real data measurements of the incident signals received by the sensor array has been provided by a hardware part involved in the smart antenna system design. Bahri et al. [3] have proposed a flexible beam forming algorithm using downlink multiple-input multiple-output multi- carrier code division multiple access system (MIMO MCCDMA) for smart antennas. Least mean square based algorithm has been used, the receiver has incorporated pilot channel estimation and zero forcing equalizer and reference signal and no knowledge channel has been required. Robustness against multi path effects and multi-user flexibility multi-carrier code division multiple access and channel diversity provided by multiple-input multiple-output systems for radio mobile channels have been efficiently exploited by learning multi-carrier code division multiple accesses in a multiple antenna setting. Abdallah [2] have discussed the use of Butler matrix which is a distinctive type of beam former in a switched beam smart antenna system’s antenna array. Their system has been developed and evaluated for use in the 11.25-12.85 GHz satellite communication band. Compactness has been achieved by constructing the technique that incorporates a 4x4 Butler matrix and a 4-element micro strip patch antenna array, entirely by using micro strip printed circuit technique. Wang et al. [20] have proposed a complex-valued genetic algorithm (GA) for optimizing linear array antenna beam forming. Unlike traditional GA, the array excitation weighting vectors have been directly signified by their method as complex number chromosomes by means of binary coding, and complex-valued encoding based genetic operator methods have been improved. Both remarkable improvement in searching efficiency and successful prevention of premature convergence have been achieved by their algorithm. Recioui et al. [14] have proposed a genetic algorithm for producing evenly spaced linear array geometries with potential 2 T. S. Ghouse Basha et al. to achieve decrease in side lobe level and beam forming. The objective of the iterative process has been to adapt the preferred pattern to the desired one and in addition reduce the side lobe level by optimizing the element excitations. The design usefulness and adaptability for switched smart antenna systems applications have been established by including several examples. Abdolee et al. [1] have proposed a decimal genetic algorithm for simultaneous minimization of side lobe and generation of nulls toward interferers and jammers. Their technique has accelerated the optimization process by exploiting Chebyshev coefficients window as an initial weight vector. The capability of their technique to simultaneously minimize the side lobe power and produce the nulls in the direction of interferers by identifying the most appropriate weights vector has been made evident by the simulation results. Uniform Linear Array (ULA) structure has been validated. While reviewing the recent researches explained above in [18], beam forming is obtained using MUSIC algorithm but main beam and deep nulls in the direction of interfering signal only considered; in [3], beam forming is obtained using RLS and LMS algorithm by considering interference, but result is not up to the level; in [2], beam forming in smart antenna using micro strip printed circuit technique; in [20], beam forming in smart antenna obtained using genetic algorithm; in [14], beam forming obtained using GA considering only side lobe level and beam pattern and in [1], beam forming in smart antenna obtained using decimal GA by considering side lobe level and null towards interference. From the above description, it is clear that in most of the works one or two factors are considered for beam forming in smart antenna. 3. Beam forming in smart antenna using GA The factors used for computing beam forming in smart antenna are interference, length of the beam, number of patterns, phase angle, position, gain etc. By using the above factors the beam pattern, main beam and side lobe are calculated. So it is clear that, the above factors will directly affect the performance of the smart antenna. While investigating the existing works, it is found that one or two factors are utilized for beam forming in smart antenna. Hence, by considering the aforementioned drawbacks, here a hybrid technique for beam forming in smart antenna is proposed using the parameters such as interference, length of the beam, number of patterns, phase angle, and gain.