Wireless Communications - advanced topics

Wireless Communications

1. Reconfigurable Intelligent Surfaces & Holographic Massive MIMO: Vision, Fundamentals & Open Problems Authors – Muhammad Ahmed Mohsin, Muhammad Saad, Muhammad Jazib Advisor –Prof.Dr Jen Yi Pan 1

2. Outline Introduction Beamforming and Wave Propagation Evolution of multiantenna Technology Reconfigurable Intelligent Surfaces Fundamentals and Vision System Model and Optimization Holographic Massive MIMO Properties and Benefits Spatial Channel Modeling 2

3. Fixed Beam vs. Intelligent Surface Control Stronger signal to users within the beam's coverage area Coverage to "unlucky users" who are outside the fixed beam's coverage area, ensuring they also benefit from improved signal strength

4. Beamforming 4

5. Beamforming and Reflection One Antenna Two Antennas Same Signal Two Antennas Same Signal different delays Increasing the number of antennas in an array can improve signal gain Dividing antennas between multiple beams impacts signal distribution and overall gain . Direction Determined by geometry  

6. 6 Evolution of MIMO

7. MIMO Communication Multi-user MIMO (LSTA) Motivation was data rate grows with increase Antenna M and users K With increase in M/K ratio the Data rate also increases and vice versa Multi-user MIMO (SDMA) Same Motivation to increase data rate Maximizing the capacity at receiving location having multiple propagation paths

8. Massive MIMO Base Station Development in 5G Manny Antennas M per base Station M≥64 Spatial Multiplexing of many users K≥8 Antenna-user ratio M/K ≥ 1 One large gain Antenna 64 small gain Antenna

9. Performance of Massive MIMO Realization of Truly Massive MIMO If we ignore spatial correlation Spectral efficiency tends to constant with further increase in horizontal antennas. If consider correlation fading Spectral Efficiency tends to increase with increase in horizontal antennas

10. Active and Semi-Passive Arrays Active Arrays Semi Passive Arrays Reconfigurable Intelligent Surface To build Massive MIMO there exist two methods Active Arrays Semi-Passive Arrays

11. Reconfigurable Intelligent Surfaces General idea remains the same! Can control reflection of electromagnetic waves by changing electric and magnetic properties Strategically placed in the radio channel between transmitter and receiver Takes control of the propagation path 11 Transmitter Receiver Controller Metasurface Many names in literature regarding intelligent surfaces! Large intelligent surfaces, Intelligent reflecting surface, software-controlled metasurfaces , …

12. 12 Size of the Elements Discretized Reflection Ideal Continuous Reflection Change in Impedances of each element resulting in the redirecting the signal Each element scatters signal isotopically Constructive interference in the direction we desire RIS can control Scattered Signal Directivity Signal Absorption Change Polarization

13. 13 System Model of RIS Aided Communication

14. 14 Basics of Signals and Systems

15. 15 Analyzing RIS Conventional Channel Models Controlled by RIS

16. Filtering of the Signal by RIS Element Reflecting-only (RIS) Patch with the bias voltage By tunning, the bias voltage minor variations in Amplitude response is observed so filtering is done in this way   16

17. Transmission of Data Transmission is carried out PAM(Pulse Amplitude Modulation) Transmit discrete sequence x[m] m=integer 17

18. 18 Maximizing Narrow Band Communication Performance

19. Maximizing Performance with a Direct Path 19 Maximize SNR

20. Basic Performance Benefit 20 Product of Pathlosses SNR Grows with square of N

21. 21 Holographic Massive MIMO

22. Massive MIMO vs Holographic MIMO 22 Holographic MIMO Utilize densely packet antenna Achieves high spatial resolution Promises lower power consumption Useful for ultra high data rates Massive MIMO Utilize large number of discrete Antennas Enhances high spectral efficiency through spatial multiplexing Manages high dimensional Matrix Channel Useful for broad band coverage

23. Near field and Far field of Antenna 23 Fraunhofer Distance Near Field : Strong, reactive fields. High sensitivity to nearby objects and mutual coupling. Used for short-range applications like NFC and wireless charging. Far Field : Stable, radiative fields. Characterized by a clear radiation pattern. Used for long-range communication and sensing applications.

24. Near field and Far field of Antenna 24 Determines Spatial Resolution and Directionality Signal Strength and Coherence Beam Steering and Adaption

25. Near Field Focusing and Array Gain 25

26. Holographic Beamforming 26 Utilizes principles of holography to synthesize precise and adaptive beams in space Employs a dense array of individually controllable elements to manipulate electromagnetic wavefronts. . Employs a dense array of individually controllable elements to manipulate electromagnetic wavefronts. No Pathloss between surface a nd RF Generator Invisible deployment Thin form factor

27. Towards Continuous Aperture 27 Fixed Surface Dimensions   Beamwidth Unaffected as d approaches to zero Determined by L and H Sidelobes reduces Small gain below  

28. Spatial Degrees of Freedom Represents the number of independent direction in which signals can be transmitted in communication system Determines System Capacity to exploit spatial diversity Represented by “ η ” One Dimension Uniform near array length Two Dimension 28

29. Array Response Vector 29 Input/Output Plane going wave determined by

30. Multi Channel Model 30 Channel Vector for L plane Wave Rayleigh Fading Achieved as L approaches to Infinity

31. Isotropic Scattering 31 Uniform Distribution in one Half Space Spatial Correlation Matrix Angles of arrival of the signals are uniformly distributed in one half-space, with a higher probability density near the horizon The correlation depends on the distance between the elements and follows a sinc function, which implies that elements farther apart have lower correlation.

32. Natural Spatial Correlation 32 Two Contributing Factors Sub-Wavelength Antenna Spacing Two-Dimensional Surface Channel Sparsity Square Array and Isotropic Scattering

33. Sparse Channel with RIS 33 Sparse Channel From RIS Sparse Channel to RIS Controllable Vectos

34. Near Field Channel Modeling 34 Near Field Phenomenon Distances to Antenna Changes Effective areas Changes Polarization Losses Channel Gain Far Field

35. 35 Ways to Increase Capacity

36. Channel Model Ways to Increase Capacity 36 Multiplexed more Layers To one or more multiple users Three Ways to increase it Use More Bandwidth Must be Associated with higher Power Gain Reduce Range Improve Pathloss

37. Comparison 37 Holographic Massive MIMO Reconfigurable Intelligent Surfaces Spatial Multiplexing Utilize Near field Effects Can be used in any propagation environment Improved Coverage and Reduced Fading Improved Channel Rank Deploy to get LOS Channels

38. 38 Thank you! Questions?