Luận án tiến sĩ về bộ định dạng búp sóng thích nghi - Tôn Văn Luyện

VIETNAM NATIONAL UNIVESITY, HANOI UNIVERSITY OF ENGINEERING AND TECHNOLOGY TONG VAN LUYEN RESEARCH AND DEVELOPMENT OF ADAPTIVE BEAMFORMERS FOR INTERFERENCE SUPPRESSION IN SMART ANTENNAS Dissertation for the Degree of Doctor of Philosophy in Communication Engineering Hanoi - 2018 VIETNAM NATIONAL UNIVESITY, HANOI UNIVERSITY OF ENGINEERING AND TECHNOLOGY TONG VAN LUYEN RESEARCH AND DEVELOPMENT OF ADAPTIVE BEAMFORMERS FOR INTERFERENCE SUPPRESSION IN SMART ANTENNAS Dissertation for the Degree of Doctor of Philosophy in Communication Engineering Major: Communication Engineering Code: 9510302.02 Supervised by Assoc. Truong Vu Bang Giang Hanoi - 2018 Declaration I confirm that: - This dissertation represents my own work; - The contribution of my supervisor and others to the research and to the dissertation was consistent with normal supervisory practice; - External contributions to the research are acknowledged. Date: September 26", 2018 Tong Van Luyen Acknowledgement First of all, I would like to express my sincere thanks to my supervisor, Assoc. Truong Vu Bang Giang, for his supervision, his support and assessment comments in the work, and what he has done for me at VNU University of Engineering and Technology.

He believed me in my scientific ability, challenged my work, and encouraged me to pursue my ideas during the time we worked together. I would like to thank Faculty of Electronic Engineering, Hanoi University of Industry, and Faculty of Electronics and Telecommunications, VNU University of Engineering and Technology for their support for me to do PhD course. My special thanks to M. Nguyen Minh Tran for his discussions and comments, and his technical support in our lab to my dissertation.

I highly appreciate the help from Dr. Hoang Manh Kha, Dr. Dao Thanh Hai, and thank them for their helpful discussions in nature-inspired optimization, and their kind encourages to the success of this work. I would like to thank M.

Pham Thi Quynh Trang for her kind support at both the simulation technique in my dissertation and the work in my office. I am grateful to my dear colleagues, Nguyen Viet Tuyen, Duong Thi Hang, Bo Quoc Bao, Vu Thi Phuong Quynh, and the other colleagues of HaUI Faculty of Electronic Engineering, for their practical support during my work. Finally, my beloved thanks and my deepest gratitude to my parents of both sides, my wife Duyen, my daughter My Quyen, and my son Minh Duc for their love and encouragement. Thanks to your sharing and sacrifice and to you I dedicate this dissertation.

ii Contents D€CÌATAEÏOTN.ccssccsssccssscssscccssccssccessccsscccsccsessccsssccssscsssccssssccssccscscssesssnseees ii CCOIIẨ€TIÉS. SH Họ TH TT. 0005000100600 1 000900096000 iii List of ADDreviations.ccccscscscssscssssccrssscsssssssssscsscsssscesscssssssecsscsssessssssoesseees 1 List of the Symbols and Notations .ccsscccssscsssssssscsssscsssscsssssssscsssscsssscssssssssoes 2 List Of E]ÏØUITF€S.96 3 List Of Tables. Rationale for the Study 01 ậộ‡›s›s¿s-.

Objectives, Subjects, Scope, and Methodology of the Study. Q0 TH HH nh 10 IIL2. Subjects, Scope, and MethodOÏOgØV. nh ng ng ng ngư 11 TIL.

Significance of the Study.- 5 s1 ng HH 11 IV.- - s9 HH HH HH 13 Chapter 1: Overview of BeamfOTImỈNØE. Beamforming for Smart Antennas. Mathematic Basis of Smart Anf€ni4S. Geometric Relations nh ẽ.

The Model of Smart Antennas with Linear ATTaWS. Optimal Beamforming Techniques. Classical Optimization Techniques. Nature-inspired Optimization Techniques.

-- -- 6 5E E1 211231 91 911 119v HT ng ng nếp 30 Chapter 2: General Process to Develop BA-based Adaptive Beamformers for Interference SŠUJDT€SSÏOIA. Problem Defterm1nafIOIn.- --- «6 119191 911911930 1H vn gu TH nh nh ng kg 31 2. Array Factor BulÏd1ng.- --- ---- «<< 1x91 1 1 111 vn TH HT ng ng 32 2. Pattern Nulling TechniQUe€s.-- 5 5 + 11 9311111 TT ng ng 33 2.

Amplitude-only Control. Phase-only Control 0. Complex-weight COTIẨTOÌL. Formation of Objective FUnCfIOTI.v HH ng nếp 35 2.

Building of BA-based Adaptive Beamforming Algorithms. Development of Adaptive Beamformets. Proposals of General Process to Build Adaptive Beamformers. 41 11 Chapter 3: Developments of BA-based Adaptive Beamformers for Interference XÖUDDDF€SSÏOIH.

nọ lọ họ TH. Common Items of BA-based Adaptive Beamformets. The Beamformer Based on Phase-only Control. Diagram of the BearmfOTIN€T.---- + + %5 E +1 E*kE*#E*vE*EE Hng n rưkp 45 3.

Penalty Parameter c in the Objective EuncfION. Numerical Results and [DISCuSSIONS. The Beamformer Based on Amplitude-only ContrOÏ. Diagram of the Be€aITnfOTTN€T.- 5 2E 5 E1 E3 E S3 VE+3VES KV crkt 51 3.

Numerical Results and Discussions. The Beamformer Based on Complex-weight ContfrOÏ. Diagram of the B€aImfOTIN€T. Numerical Results and Discussions.

Effect of Mutual Coupling. - -- c6 119911991 91 19v 9 1g HH rệt 61 Kha .ceeccseccssseesessseeeneceseceseceseesseesseesaeesseesseeeseeeeeseesseeeseeeseeees 72 Conclusions and Future Works .cccsccsssscsssssssccsssccsssscsssssssscssscssssssssssssscsssseoes 73 List of Publications.ccsccscsccsssssssscsssccsssssscssccscsscsssscssscsssccsssscssccsssccsesscscssesscssssecssseeees 77 ADD€TICÍÌX. Application Model of Smart Ante'nnas. Classical Optimization Techniques.

Adaptive Beamforming Algorithms. Dolph-Chebyshev Weighting Method. Software for Modeling Adaptive Beamforming in Smart Antennas. Supported Simulation Results.

Additional Results for Patterns with Single and Multiple NuÌls. Some Sets of Weights for the Investigated Scenar1oS.- --- --«+s<+s<2 110 iV List of Abbreviations ABF Adaptive Beamformer ADC Analog-to-Digital Converter AF Array Factor AMP_BA_ABF Amplitude-only Control and Bat Algorithm-based Adaptive Beamformer APSO Accelerated Particle Swarm Optimization BA Bat Algorithm CW_BA_ABF Complex-weight Control and Bat Algorithm-based Adaptive Beamformer DBF Digital Beamforming DOA Direction-Of-Arrival DSP Digital Signal Processor FNBW First-Null Beamwidth GA Genetic Algorithm HPBW Half-Power Beamwidth LMS Least Mean Square MC Mutual Coupling MMSE Minimum Mean Square Error MSE Mean Square Error NDL Null Depth Level PHA_BA_ABF Phase-only Control and Bat Algorithm-based Adaptive Beamformer PSO Particle Swarm Optimization RF Radio Frequency RLS Recursive Least Square SDMA Space Division Multiple Access SLL Sidelobe Level SMI Sample Matrix Inversion SNOI Signal-Not-Of-Interest SOI Signal-Of-Interest ULA Uniform Linear Array 1/112 List of the Symbols and Notations In-phase channel in of binary baseband signals Quadrature-phase channel in of binary baseband signals Sum The real vector space (n-dimensional space of the variables) Subset of or equal to An element of Elevation angle in the coordinate system for antenna analysis Azimuth angle in the coordinate system for antenna analysis Wavelength Unit vector on the x axis Differential value of x Wavenumber Vector and its components Maxtrix and its components Complex conjugate of x Transposition of a matrix Hermitian transpose of a matix Cross correlation of x(n) and r(n) Covariance of x(n) Estimation of X Real part of {.} Imaginary part of {.} Cosine integral Sine integral Infinity 3.1415926535897932385 Bat algorithm: Position of bat (i) corresponding to a solution of the weights for array elements Velocity of bat (i) Frequency of bat (1) Loudness of bat (1) Rate of emission pulse of bat (i) 2/112 List of Figures Figure 1. Beamforming for smart anf€T49.- 6 SE Esvsseseersee 15 Figure 1. Applications of bearmfOTIInE.-- 5+ + + £++EE+seeEeeeeeeeeseeers 15 Figure 1.

Block diagram of analog beamforming in smart antennas. Block diagram of DBF in smart anfennas. Simple block diagram of adaptive beamformer at the receiving end. The analyzed linear afTAy.- --- s1 kg rên 19 Figure 1.

Linear-array smart antennas at the receiving end. Radiation pattern of 20-element ULA.-- --««++-««+++se++se+ssexs 22 Figure 1. Flowchart of Bat algorithm. eee eeeeeseeseeseesececseeseseeeeeeeeseseeaseneeas 29 Figure 2.

Geometry of ULAs of 2N eleme€nIfs. Block diagram of adaptive beamformers for interference suppression. Flowchart of the proposed beaInformers. General process to build adaptive beatmfOrmers.

Diagram of PHA_BA_ABF. NDL and maximum SLL with different c in the case of pattern with Single NULL. Objective function comparisons of BA, PSO, and GA. Optimized pattern with a single null at Í4”.

Optimized pattern with three nulls at -48°, 20°, and 40°. Optimized pattern with a broad null from 30° to 40°. Diagram of AMP_BA_ ABE. Objective function comparisons of BA, PSO, and GA.

Optimized pattern with single symmetric null at 14P. Optimized patterns with three symmetric multiple nulls at 14°, 26°, and se. Optimized patterns with a symmetric broad null from 20° to 50°, unchanged main lobe beamwidth and peak SLL = -18. Optimized pattern with a symmetric broad null from 20° to 50°, broaden main lobe beamwidth and SLL < -30 đB.

Diagram of CW_BA_ ABIE. LH HH HH ng ngư 57 Figure 3. Objective function of BA with different population s1zes. Objective function between BA and APSO.

Optimized patterns with single null at 14°. Optimized pattern with three nulls at -33°, -26°, and -14?. Optimized pattern with three nulls at -40°, 20°, and 40°. Optimized pattern with a broad null from -50° to -207.

Optimized pattern with a broad null ([-30°, -20°] and [45°, 60°). Optimized pattern with a broad null ([-30°, -20°] and [45°, 60°]) and SLE Of 0 -. Optimized pattern (nulls: -48°, 20°, 40°) with mutual coupling. Radiation pattern of a twenty-element ULA.

Coordinate system for antenna analysis. Different array geometries for smart antennas: (a) uniform linear array, (b) circular array, (c) two-dimensional grid array and (d) three-dimensional grid Figure A. Switched-beam System. Comparison of (a) switched-beam system, and (b) adaptive array 1.

Relative coverage area comparison among sectorized systems, switched-beam systems, and adaptive array systems in (a) low interference environment, and (b) high interference enVITORIMN€IIE.- 5-5 «+ £+£+s£+se+sx2 88 Figure A. Functional block diagram of a smart antenna using DOA-based adaptive beamforming aÏØOTItÏINS. -- ¿<< E1 1311821118911 91 1911191 9v ng ng ng re 89 Figure A. Radiation pattern of a smart antenna.

Functional block diagram of a smart antenna using training-based adaptive beamforming algorithms. Geometry of ULA antennas of 2N elemenfs. Normalized array factor for 20-element Chebyshev arrays with Sidelobes at 00); n5. The main lobes of the 8-element ULA have been steered to the desired directions as 0 = 49°, -30°, 30°, 60°.

ues ceeeccccccccceccccescesseessessssssssssssssaeeeeess 101 Figure C. Five nulls have been set at elevation angles of -55°, -35°, -15°, 20°, and "dd: 101 Figure C. The main beam is steered to Ø = 30° and 5 nulls are set at Ð = -55°, -35°, -15°, 0°,45° at the SAME tIMe. ee eececceesesssssssscccceeeeeeecceeecceseeeseeceeeetststtssaseeeeeeess 102 Figure C.

The optimized pattern with all side lobe levels are suppress to -30dB by Dolph-Chebyshev weighting method. The optimized pattern by applying both LMS algorithm and Dolph- Chebyshev weighting methOd.- - ---- + + 13199 19 19 1 ng ng việt 103 Figure C. The optimized pattern of 1x8 ULA using LMS algorithm. The optimized pattern of 1x8 ULA using both LMS algorithm and Dolph-Chebyshev weighting method.

Pattern with a single symmetric null in the range of 0: a) (-90°, 90°); D) (13°, 16°). Pattern with three symmetric nulls in the range of 0: a) (-90°, 90°); 0001-50. Pattern with a single null in the range of 0: a) (-90°, 90°); b) (13°, 16°). Pattern with three nulls in the range of 0: a) (-90°, 90°); b) (-50°, -46°); c) (18°, 22°); d) (38°, 42°).

Pattern with a single symmetric null in the range of 0: DI C 0001000 6i. Pattern with three nulls in the range of 0: a) (-90°, 90°); b) (-34°, -13°). LH HH Hà TT HT HT TH TT Hàn 109 Figure D. Pattern with three nulls in the range of 0: E000) 1)nG “2v.

109 5/112 List of Tables Table 3. Common parameters for all proposed beamfOrmers. NDL and maximum SLL of the patterns in all scenarios with or without 01011021890)ì10)0) 50701077. Summary of the prODOSaÌS.

G6 SG 311191 vn re 67 Table 3. Comparisons between the proposals in this dissertation and the proposal Table B. Resulting weights computed by Dolph-Chebyshev weighting method. Some sets of weights consisting amplitudes (a,,) and phases (ổ„) of the patterns shown in Figures 3.- Ăn HH HT TH HH kg 110 Table D.

Some sets of weights for the patterns shown in Figures 3. Some sets of weights for the patterns shown in Figures 3. Rationale for the Study Beamforming is a signal processing technique in sensor arrays to directionally transmit or receive signals in space-time. In order to do that, the signals corresponding to array elements are combined in the interest of boosting the desired signals in particular directions and minimizing the undesired signals (interferences) in the others.

Beamforming can be applied for both transmitting and receiving ends in order to achieve spatial selectivity, thus, it is also called spatial filtering technique.