Available online at www.sciencedirect.com Procedia Technology 6 ( ) 856 863 Non-Uniform Concentric Circular Antenna Array Design Using IPSO Technique for Side Lobe Reduction Durbadal Mandal, Md. Asif Iqbal Ansari, Rajib Kar, S. P. Ghoshal Department of Electronics and Comm. Engineering, Department of Electrical Engineering National Institute of Technology Durgapur, West Bengal, India- 739 Email: durbadal.bittu@gmail.com, asif.iqbalece3@gmail.com Abstract In this paper the optimal design for maximum sidelobe level (SLL) reduction of three-ring Concentric Circular Antenna Array (CCAA) is deterned using a novel Particle Swarm Optization (PSO) technique namely Improved Particle Swarm Optization (IPSO) algorithm. Standard PSO is also adopted for the comparative optization. The present text assumes non-uniformly excited and non-uniform inter-element spacing array with a design goal of maxizing SLL reduction using the above two evolutionary optization techniques. It is shown that among all the designs, the three-ring structure containing (N =4, N =6, N 3 =8) elements proves to be the optimal design owing to the highest SLL reduction achieved by each technique. IPSO yields grand nimum SLL (-3.86 db) for the above optimal set. Published by Elsevier Ltd. The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Department of Computer Selection and/or peer-review under responsibility of the Department of Computer Science & Engineering, National Science & Engineering, National Institute of Technology Rourkela Open access under CC BY-NC-ND license. Institute of Technology Rourkela Keywords: Concentric Circular Antenna Array; Non-uniform Excitation; Sidelobe Level; Particle Swarm Optization; IPSO. Introduction An antenna array consists of multiple stationary antenna elements, which are often fed coherently. Recently, varied applications of antenna array have been suggested to improve the performance of mobile and wireless communication systems through efficient spectrum utilization, increasing channel capacity, extending coverage area, tailoring beam shape etc. [-3]. However, arbitrary array design may lead to increment in pollution of the electromagnetic environment and more importantly, wastage of precious power, which may prove fatal for power-lited battery-driven wireless devices. This explains the presence of abundant open technical literatures [4-4], bearing a common target - bridging the gap between desired radiation patterns having nil SLL with what is practically achievable. The primary method in all these research works is improvement of array pattern by manipulating the structural -73 The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Department of Computer Science & Engineering, National Institute of Technology Rourkela Open access under CC BY-NC-ND license. doi:.6/j.protcy...4
Durbadal Mandal et al. / Procedia Technology 6 ( ) 856 863 857 geometry to suppress the SLL while preserving the gain of the main beam. The goal in such antenna array geometry synthesis techniques is to deterne the physical layout of the array that produces the radiation pattern closest to the desired pattern. As the shape of the desired pattern can vary widely depending on the application, many synthesis methods coexist. Among the different types of antenna arrays CCAA [4-] have become most popular in mobile and wireless communications. This very fact has inspired the design of CCAA and evaluation of the performance of corresponding antenna arrays. In this paper optization of CCAA design having a uniform element separation and a non-uniform excitation is performed with the help of evolutionary optization techniques. Contribution of the paper is two-fold. Firstly, the outcome of non-uniform excitation in various CCAA design structures is exaned to find the best possible design structure by two evolutionary techniques, PSO [5-6] and IPSO [7-8]. Secondly, regarding the comparative effectiveness of the techniques, the newly proposed IPSO technique proves to be the best in attaining nimum SLL, reduction of major lobe in the optization of various CCAA design problems. The rest of the paper is arranged as follows: in section II, the general design equations for the nonuniformly excited CCAA are stated. Then, in section III, brief introductions for the PSO and IPSO are presented. Numerical results are presented in section IV. Finally the paper concludes with a summary of the work in section V.. Design Formulation Fig. shows the general configuration of CCAA with M concentric circular rings, where the m th (m =,,, M) ring has a radius r m and the corresponding number of elements is N m. If all the elements (in all the rings) are assumed to be isotopic sources, the radiation pattern of this array can be written in terms of its array factor only. Referring to Fig., the array factor, AF, I, d for the CCAA in x-y plane may be written as []: AF M N m, I, d I exp j kr sin cos () m i m where N m kr m d i d is inter-element spacing between the elements. I denotes current excitation of the i th element of the m th ring, k / ; being the signal wave-length. If the elevation angle, = 9 then () may be written as a periodic function of is the element to element angular separation measured from the positive x-axis. The elements in each ring are assumed to be nonuniformly distributed. and are also obtained from [3] as: i N N m i d d () m cos Kr (3)
858 Durbadal Mandal et al. / Procedia Technology 6 ( ) 856 863 is the value of where peak of the main lobe is obtained. After defining the array factor, the next step in the design process is to formulate the objective function which is to be nized. The objective MF may be written as (4): AF msl, I, AF msl I MF WF WF BWFN computed BWFN I (4) AF, I BWFN is the angular width between the first nulls on either side of the main beam. MF is computed only if BWFN BWFN and the corresponding solution of current excitation weights is retained computed I in the active population otherwise not retained. W F and W F are the weighting factors. Minization of MF means maximum reductions of SLL both in lower and upper bands and lesser BWFN as computed compared to BWFN I. The evolutionary techniques employed for optizing the current excitation weights resulting in the nization of MF and hence reductions in both SLL and BWFN are described below. 3. Evolutionary Techniques Employed Figure. Concentric circular antenna array (CCAA). PSO and IPSO as implemented for the optization of current excitation weights and radii of the rings of the CCAA are given in [7-8]. So, the steps of PSO and IPSO are not described due to litation in space. 4. Simulation Results This section gives the experimental results for various CCAA designs obtained by PSO and IPSO techniques. For each optization technique ten three-ring (M=3) CCAA structures are assumed, each maintaining a non-uniform excitation and non-uniform inter-element spacing with a design goal of maxizing SLL reduction. For obtaining the best non-uniform spacing and non-uniform excitations sets in each ring, 5 trial generalized optization runs are used for each structure. For all sets of experiments, the number of elements of the inner most circle is N, for outermost circle is N 3, whereas the ddle circle consist of N number of elements. For all the cases, = is considered so that the centre of the main
Durbadal Mandal et al. / Procedia Technology 6 ( ) 856 863 859 lobe in radiation patterns of CCAA starts from the origin. After experimentation, best proven values of W F and W F are fixed as 8 and respectively. Since PSO techniques are sometimes quite sensitive to certain parameters, the simulation parameters should be carefully chosen. Best chosen maximum population pool size, n p =, maximum iteration cycles for optization, N m =. Lesser number of cycles is found to be sufficient for the convergences PSO and IPSO with C = C =.5 is experimentally found to be very effective. The predefined probability of craziness is introduced to maintain the diversity of the particles. Results obtained with this technique prove to be the better compared to other technique considered. This novel technique has very rapidly converged to the correct optimal solution unlike PSO. PSO and IPSO with C = C =.5 is experimentally found to be very effective. The predefined probability of craziness is introduced to maintain the diversity of the particles. Results obtained with this technique prove to be the better compared to other technique considered. This novel technique has very rapidly converged to the correct optimal solution unlike PSO. TABLE I. SLL AND BWFN FOR UNIFORMLY EXCITED ( I =) CCAA SETS Set No. No. of elements in each rings (N,N,N 3 ) SLL (db) BWFN (deg) I, 4, 6 -.56 8.4 II 3, 5, 7-3.8 7. III 4, 6, 8 -.3 9.3 IV 5, 7, 9 -. 78. V 6, 8, -.34 68.4 VI 7, 9, -. 6. VII 8,, -9.6 54.8 VIII 9,, 3-9.8 5. IX,, 4-9.6 46. X, 3, 5-8.9 4. Each of PSO and IPSO techniques generates a set of normalized non-uniform current excitation weights and non-uniform spacing for all sets of CCAA. I = corresponds to uniform current excitation. Sets of three-ring CCAA (N, N, N 3 ) designs considered are (,4,6), (3,5,7), (4,6,8), (5,7,9), (6,8,), (7,9,), (8,,), (9,,3), (,,3), (,3,5). Partial results for PSO and IPSO are shown in Tables II-III. Table I depicts SLL values and BWFN values for all corresponding CCAA structures but uniformly excited. 4.. Analysis of Radiation Patterns of CCAA Sets and Optimal CCAA Figures -4 show the radiation patterns for a uniformly excited CCAA having different number of elements, with fixed spacing of between elements and for non-uniformly and optimally excited and spaced CCAA, using PSO and IPSO optization techniques respectively. From the figures it is clearly visible that the SLL reduction is marginal for the uniformly excited set, although the number of elements is the same.
86 Durbadal Mandal et al. / Procedia Technology 6 ( ) 856 863 TABLE II. EXCITATION DISTRIBUTION AND THE RESULTING ELEMENT DISTRIBUTIONS FOR NON- UNIFORM CCAA USING STANDARD PSO Set ( I, I I ); No. (d, d, d 3..., d ) III.557.768.66.7445.57.5956.988.643.576..566.7886.434.433.4454.857.5834.887;.586.5.5.586.59.599.5958.59.59.59.76.7677.767.69.777.757.774.7568 SLL (db) BWFN (deg) -8.6 76.68 V.8693.7976.9947.888.5867..8466.387.93.96.676.5.4578.6694.64.864.6485.5356.556.677.7949.6356.4987.937;.55.55.55.55.55.533.635.64.64.6345.696.64.6349.63.7576.7547.7559.755.7537.77.7583.793.7474.745 VII.8445.5636.98..8779.97.847..87..56..7438.544.3.847.363.4866.657...357.63.5448.499.9977.4998.6545.7746;.5555.5555.5555.5555.5555.5555.5555.5555.6.6.684.6.6.6.6.5968.6.6.7555.7555.7555.7555.7555.7555.7555.7555.7555.7555.7555.7555 -.8 58.5-3. 47.88 Side lobe level relative to the main beam (db) - - -3-4 -5-6 Uniform PSO IPSO -5 - -5 5 5 Angle of arival (degrees) Figure. Radiation patterns for a uniformly excited CCAA and corresponding standard PSO and IPSO based nonuniformly excited CCAA for N =4, N =6, N 3=8 elements.
Durbadal Mandal et al. / Procedia Technology 6 ( ) 856 863 86 Side lobe level relative to the main beam (db) - - -3-4 -5-6 Uniform PSO IPSO -5 - -5 5 5 Angle of arival (degrees) Figure 3.Radiation patterns for a uniformly excited CCAA and corresponding PSO and IPSO based non-uniformly excited CCAA for N =6, N =8, N 3= elements Side lobe level relative to the main beam (db) - - -3-4 -5-6 Uniform PSO IPSO -5 - -5 5 5 Angle of arival (degrees) Figure 4.Radiation patterns for a uniformly excited CCAA and corresponding PSO and IPSO based non-uniformly excited CCAA for N =8, N =, N 3= elements 4.. Comparative effectiveness and convergence profiles of PSO and IPSO The nimum MF values against number of iteration cycles are recorded to get the convergence profile of each technique. Figures 5-6 portray the convergence profiles of nimum MF of PSO and IPSO respectively. From these figures it is clear that PSO yields suboptimal higher values of MF. IPSO yields near optimal (least) MF consistently in all cases. With a view to the above facts, it may finally be inferred that IPSO yields true optization. The programng has been written in Matlab language using MATLAB 7.5 on core (TM) duo processor, 3. GHz with GB RAM. Misfitness 5.5 5 4.5 4 3.5 3.5.5 3 4 5 6 7 8 9 Iteration Cycle Figure 5. Convergence curve for standard PSO in case of non-uniformly excited CCAA (N =4, N =6, N 3=8 elements). Misfitness 9 8 7 6 5 4 3 5 5 Iteration Cycle Figure 6. Convergence curve for IPSO in case of nonuniformly excited CCAA (N =4, N =6, N 3=8 elements).
86 Durbadal Mandal et al. / Procedia Technology 6 ( ) 856 863 TABLE III. EXCITATION DISTRIBUTION AND THE RESULTING ELEMENT DISTRIBUTIONS FOR NON- UNIFORM CCAA USING IPSO Set ( I, I I ); No. (d, d, d 3..., d ) III.557.768.66.7445.57.5956.988.643.576..566.7886.434.433.4454.857.5834.887;.586.5.5.586.59.599.5958.59.59.59.76.7677.767.69.777.757.774.7568 V.37.9.446.38.343.59.973.35.479.3936.387.3764.95.5.65.353.783.536.47.36.3899.999.69;.5455.5455.5455.5459.555.557.5955.6.693.598.5955.64.63.5955.7475.746.7455.75.7457.7464.7455.7455.7478.7487 VII.4964.3733.693.556.395.3734.64.5964.746.8.89.4677.763.753.738.538.596.794.3549.446.43.364.5.373.79.638.49.3597.38;.5.5.5.5.5.5.533.5.59.5947.59.59.66.5936.59.59.59.69.69.734.733.69.69.7.69.69.694.693.764.69 SLL (db) BWFN (deg) -3.86 76.5-4.44 59.58-8.56 59.76 5. Conclusions In this paper, the design of a non-uniformly excited concentric circular antenna array with non-uniform spacing between the elements has been described using the techniques of PSO and IPSO. Comparing with the other techniques reported in the work, IPSO technique gives near global nimum values of SLL for all sets of CCAA designs. Experimental results reveal that non-uniform CCAA offers a considerable SLL reduction along with the reduction of BWFN with respect to corresponding uniform CCAA. Contribution of the paper is twofold: first, for two techniques the CCAA having N =4, N =6, N 3 =8, gives grand maximum SLL reduction compared to all other sets, which one is the optimal set among three-ring structures, and second, comparing the performance of both techniques IPSO shows the better optization performance compared to PSO. References [] R. L. Haupt, and D. H. Werner, Genetic Algorithms in Electromagnetics, IEEE Press Wiley-Interscience, 7. [] on's Inc., New York, 997. [3], Revised edition, John Wiley, New Jersey, 3. [4] IEEE Trans. Antennas Propag., vol. 3(6), pp. 856 863, Nov. 965. [5] IEEE Trans. Antennas Propag., vol. 4(3), pp. 398 4, May 966. [6] - IEEE Proc., vol. 58(5), pp. 839 84, May 97.
Durbadal Mandal et al. / Procedia Technology 6 ( ) 856 863 863 [7] L. Biller and G. IEEE Trans. Audio Electroacoust., vol. (), pp. 57 6, Feb. 973. [8] M Proc. IEEE AP-S Symp., 978, pp. 455 458. [9] M Proc. IEEE AP-S Symp.,, pp. 8 83. [] Optized element s IEEE Trans. Antennas Propag., vol. 56(), pp. 66 68, Jan. 8. [] -sized concentric circular Progress In Electromagnetics Research, vol. PIER 65, pp. 87, 6. [] R. L. Haupt, "Thinned concentric ring arrays," Antennas and Propagation Society International Symposium, 8. AP-S 8. IEEE, pp.-4, 5- July 8. [3] M. A. Panduro, A. L. Mendez, R. Donguez and -uniform circular antenna arrays for side lobe Int. J. Electron. Commun. (AEÜ) vol. 6 pp. 73 77, 6. [4] K. - -Pattern Synthesis Us IEEE Trans. Antennas Propag., vol. 45(7), pp. 7-, July 997. [5] R.C. Eberhart and Y. lutionary Computation, vol. pp. 8 86,. [6] D. Mandal, Design of Concentric Circular Antenna Array With Central Element Feeding Using Particle Swarm Optization With Constriction Factor and Inertia Weight Approach and Evolutionary Prograng Technique Journal of Infrared Milli Terahz Waves, vol. 3 (6), pp. 667 68,. [7] D. Mandal, S. P. Ghoshal, and A. K. Bhattacharjee, IEEE Applied Electromagnetics Conference (AEMC 9), pp. -4, 9. [8] D. Mandal, Swarm Intelligence Based Optimal Design of Concentric Circular Journal of Electrical Engineering, vol., no. 3, pp. 3 39,.