Adaptive Antenna System consists of Beamforming techniques in which the beam generated in the direction of desired signal and nulls are placed in the direction of undesired signal (interference). The analysis of two such algorithms - Least Mean Square and Normalized Least Mean Square Algorithms are discussed in this paper. These algorithms have the ability to change the amplitude and phase values that are passed to the individual elements in the Antenna Array. The simulation results suggest that the Normalized Least Mean Square Algorithm converges much faster than the Least Mean Square Algorithm. The Adaptive Beamforming Algorithms are simulated and verified using Matlab software.

Performance Analysis of Adaptive Beamforming Algorithms

Incorporation of Defected Ground Structure (DGS) into the Microstrip Phased Array Antenna (PAA) provides
desirable changes to the direction of the main beam. In this paper, investigation on the development of 2 x 1 rectangular
patches which operates at 9 GHz is presented. The two rectangular patches are separated at 0.258 and the microstrip line
is feeding to the center of the patches to provide impedance matching. Then, an orthogonal-I-shaped DGS is inserted in
between the two patches at the ground plane. It is found that by changing the dimension of the DGS, the main lobe of the
PAA increases from 39 to 137, however, the directivity of the arrays maintains about 6 dBi. This demonstrates the
potential of employing DGS to steer the main beam of PAA instead of using additional phase shifter which is bulky and
more complicated to connect to the antenna’s feeding line.

http://www.arpnjournals.org/jeas/research_papers/rp_2015/jeas_1015_2775.pdf

Defected ground structure for beam steering array antenna applications

For enhancing data rate Smart Antennas have been gaining prominence in the recent times where the main beam is steered towards direction of interest via phase shifter. The sense behind this development is the availability of high-end processors to handle the complex computations involved. The phase shifting and array weighing can be performed on digital data rather than in hardware is the major advantage of digital beam former. This paper gives comparative study of five adaptive algorithms -Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Sample Matrix Inversion (SMI), Recursive Least Square (RLS) and Conjugate Gradient Method (CGM) for computing the array weights. This adaptive algorithm assures very high rate of convergence & highly reduced mean square error. The weights obtained by the above algorithms are then used to steer the antenna array beam in the direction of interest, thereby enhancing SNR.

/pdf/algorithms-of-adaptive-beam-forming-for-smart-antenna-a-3c26ijhnlg.pdf

Algorithms of Adaptive Beam Forming for Smart Antenna: A Comparative Study

This paper proposes an optimized multilayer planar inverted-F antenna (PIFA) with an electromagnetic bandgap (EBG) at personal communication services band for specific absorption rate (SAR) reduction. The EBG structure, which has bandgap capability and acts as a perfect magnetic conductor surface, can suppress surface waves and reduce undesired radiation from an antenna. Thus, the EBG structure is capable of preventing electromagnetic (EM) fields being emitted in the direction of the human head. To optimize the multilayer PIFA structure for SAR reduction, the EBG structure between the printed circuit board and antenna layer is designed first. Second, a parameter study about the EBG cell numbers, height, and location of the PIFA with the EBG structure is performed. Finally, the optimized multilayer PIFA with the EBG is investigated and the S-parameters, radiation patterns, total radiated power values, and SAR values are presented. The results demonstrate the reduction of SAR values while maintaining the antenna performance. Thus, the human head can be protected from hazardous EM fields using the EBG structure.

Design of optimized multilayer PIFA with the EBG structure for SAR reduction in mobile application

This paper proposes an adaptive digital beamforming (ADBF) algorithm to realize non-contact multi-person vital sign detection using a frequency modulated continuous wave (FMCW) radar. The 77 GHz FMCW radar multiple input multiple output (MIMO) mode is used to collect the vital sign echo signal of multi-human targets. At the receiving antennas, the ADBF algorithm is used to suppress the direction of arrival (DOA) interference on the vital sign signals. Then it combines 3-dimensional fast Fourier transform (3D-FFT) rangeangle algorithm to achieve multi-person target separation. The experimental results show that the proposed method is effectively for non-contact multiple people vital sign detection.

A Novel Vital Sign Sensing Algorithm for Multiple People Detection Based on FMCW Radar

Electromagnetic Band-Gap (EBG) Structures are periodic structures with an obvious frequency band gap, which can suppress the propagation of surface-wave; these structures can help to reduce the mutual coupling of antenna array. As a result, they can be used to optimize the performance of antenna array. At the same time, the Defected Ground Structure (DGS), which is developed on the basis of the EBG structure, is simpler than EBG structure and also has the ability to decrease the mutual coupling of antenna array. In this paper, the reflected phase method and suspended microstrip line method are used to respectively measure the stop band of EBG structures and a DGS. Then, two designed EBG structure and DGS are applied to antenna arrays with the help of the professional software HFSS. The results confirm the fact that these two structures can suspend the mutual coupling effectively, as well as optimize the radiation patterns.

Application of EBG and DGS structure on antenna array

Adaptive beamforming is a key technology of smart antenna; the core is to obtain the optimum weights of the antenna array by some adaptive beamforming algorithms, and finally adjust the main lobe to focus on the arriving direction of the desired signal, as well as suppress the interfering signal. By these ways, the antenna can receive the interesting signal efficiently. In practical application, the speed of convergence, complexity, and robustness are the main factors to be considered when choosing an adaptive beamforming algorithm. This paper focuses on the Least Mean Squares (LMS) algorithm and the Sample Matrix Inversion (SMI) algorithm, analyzes their performance and applies these two algorithms to adaptive beamforming with the help of Matlab.

Qiu Dong-dong

Papers

Application of EBG and DGS structure on antenna array

Research on adaptive beamforming algorithm