Luận án tiến sĩ Tong Van Luyen - Kỹ thuật beamformer thích nghi tại Đại học Bách khoa Hà Nội

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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 26th, 2018 Tong Van Luyen i LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Contents Declaration. iii List of Abbreviations.1 List of the Symbols and Notations .2 List of Figures .3 List of Tables. Rationale for the Study. Objectives, Subjects, Scope, and Methodology of the Study.

Subjects, Scope, and Methodology. Significance of the Study. 13 Chapter 1: Overview of Beamforming. Beamforming for Smart Antennas.

Mathematic Basis of Smart Antennas. The Model of Smart Antennas with Linear Arrays. Optimal Beamforming Techniques. Classical Optimization Techniques.

Nature-inspired Optimization Techniques. 30 Chapter 2: General Process to Develop BA-based Adaptive Beamformers for Interference Suppression. Array Factor Building. Pattern Nulling Techniques.

Amplitude-only Control. Phase-only Control. Complex-weight Control. Formation of Objective Function.

Building of BA-based Adaptive Beamforming Algorithms. Development of Adaptive Beamformers. Proposals of General Process to Build Adaptive Beamformers. 41 iii LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com Chapter 3: Developments of BA-based Adaptive Beamformers for Interference Suppression.

Common Items of BA-based Adaptive Beamformers. The Beamformer Based on Phase-only Control. Diagram of the Beamformer. Penalty Parameter in the Objective Function.

Numerical Results and Discussions. The Beamformer Based on Amplitude-only Control. Diagram of the Beamformer. Numerical Results and Discussions.

The Beamformer Based on Complex-weight Control. Diagram of the Beamformer. Numerical Results and Discussions. Effect of Mutual Coupling.

72 Conclusions and Future Works .73 List of Publications. Classification of Beamforming. Application Model of Smart Antennas. 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 Nulls. Some Sets of Weights for the Investigated Scenarios. 110 iv LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com 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 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com List of the Symbols and Notations I In-phase channel in of binary baseband signals Q 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 axis Differential value of Wavenumber Vector and its components Z, Zij Maxtrix and its components * x Complex conjugate of x Transposition of a matrix Hermitian transpose of a matix Cross correlation of and Covariance of ̃ 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 (i) Loudness of bat (i) Rate of emission pulse of bat (i) 2/112 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com List of Figures Figure 1. Beamforming for smart antnenas.

Applications of beamforming. Block diagram of analog beamforming in smart antennas. Block diagram of DBF in smart antennas. Simple block diagram of adaptive beamformer at the receiving end.

The analyzed linear array. Linear-array smart antennas at the receiving end. Radiation pattern of 20-element ULA. Flowchart of Bat algorithm.

Geometry of ULAs of 2N elements. Block diagram of adaptive beamformers for interference suppression. Flowchart of the proposed beamformers. General process to build adaptive beamformers.

Diagram of PHA_BA_ABF. NDL and maximum SLL with different in the case of pattern with single null. Objective function comparisons of BA, PSO, and GA. Optimized pattern with a single null at 14°.

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

Optimized pattern with single symmetric null at 14°. Optimized patterns with three symmetric multiple nulls at 14°, 26°, and 33°. 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 dB.

Diagram of CW_BA_ABF. Objective function of BA with different population sizes. 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°.62 3/112 LUAN VAN CHAT LUONG download : add luanvanchat@agmail. Optimized pattern with a broad null from -50° to -20°. Optimized pattern with a broad null ([-30°, -20°] and [45°, 60°]).

Optimized pattern with a broad null ([-30°, -20°] and [45°, 60°]) and SLL of -30 dB. 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 array. Switched-beam system. Comparison of (a) switched-beam system, and (b) adaptive array system. Relative coverage area comparison among sectorized systems, switched-beam systems, and adaptive array systems in (a) low interference environment, and (b) high interference environment.

Functional block diagram of a smart antenna using DOA-based adaptive beamforming algorithms. 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 elements.

Normalized array factor for 20-element Chebyshev arrays with sidelobes at -30 dB. The main lobes of the 8-element ULA have been steered to the desired directions as θ = 49°, -30°, 30°, 60°. Five nulls have been set at elevation angles of -55°, -35°, -15°, 20°, and 45°. The main beam is steered to θ = 30° and 5 nulls are set at θ = -55°, -35°, -15°, 0°,45° at the same time.

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. The optimized pattern of 1×8 ULA using LMS algorithm. The optimized pattern of 1×8 ULA using both LMS algorithm and Dolph-Chebyshev weighting method.

Pattern with a single symmetric null in the range of θ: a) (-90°, 90°); b) (13°, 16°).105 4/112 LUAN VAN CHAT LUONG download : add luanvanchat@agmail. Pattern with three symmetric nulls in the range of θ: a) (-90°, 90°); b) (12°, 35°). Pattern with a single null in the range of θ: a) (-90°, 90°); b) (13°, 16°). Pattern with three nulls in the range of θ: a) (-90°, 90°); b) (-50°, -46°); c) (18°, 22°); d) (38°, 42°).

Pattern with a single symmetric null in the range of θ: a) (-90°, 90°); b) (13°, 16°). Pattern with three nulls in the range of θ: a) (-90°, 90°); b) (-34°, -13°). Pattern with three nulls in the range of θ: a) (-90°, 90°); b) (-42°, 42°).109 5/112 LUAN VAN CHAT LUONG download : add luanvanchat@agmail.com List of Tables Table 3. Common parameters for all proposed beamformers.

NDL and maximum SLL of the patterns in all scenarios with or without mutual coupling. Summary of the proposals. Comparisons between the proposals in this dissertation and the proposal in. Resulting weights computed by Dolph-Chebyshev weighting method.

Some sets of weights consisting amplitudes (an) and phases (δn) of the patterns shown in Figures 3. Some sets of weights for the patterns shown in Figures 3. Some sets of weights for the patterns shown in Figures 3.111 6/112 LUAN VAN CHAT LUONG download : add luanvanchat@agmail. 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. In fact, it can be used for radio or sound waves and has been widely applied for various applications such as Radar, Sonar, Wireless communications, Radio Astronomy, Seismology, and Topography [6, 18, 26, 56]. Over the last decades, wireless technology has been developed at a remarkable rate, which has brought new and high-quality services at lower costs.

This has resulted in an increase in airtime usage, and in the number of subscribers. As a result, this leads to new challenges for next generations of wireless communications networks. The most practical solution to this problem is to use spatial processing [11]. As Andrew Viterbi, one of Qualcomm’s founders, stated: “Spatial processing remains as the most promising, if not the last frontier, in the evolution of multiple access systems” [42].