ECSE610 Winter 2016 Term-Project Presentation, 15 April 2016, McGill University

3D BEAMFORMING

syed.hussain3@mail.mcgill.ca

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Outline: INTRODUCTION 5G MOTIVATION OBJECTIVE SCOPE LITERATURE SURVEY RESULTS CONCLUSION

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Introduction:

5G – (LTE-A) Multi Gigabit Wireless communication to meet the enormous multi-media traffic

growth.

To Achieve 5G Goal underutilized 60 GHz spectrum is considered with Large Number of Antennas i.e.

Massive MIMO.

Beamforming key performance enhancer of cellular systems

if large Antennas are used.

manipulation of Transmit aperture to increase SNR and reduce Interference.

NARROW BEAM

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Introduction:

Steer and Focus the Transmit Beam.

aperture weighting (a choice of Window type e.g. Hanning, Hamming, Taylor window, Dolph-chebychev).

window is used to control side-lobes , grating lobes.

number of Antennas are Inversely proportional to Beam width (Narrow Beam). null

s

side lobes

Main lobe

Illustration Of Beam Pattern

21 /φ

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5G (Service Vision)

5G

Peak Data-Rate

Cell-Edge Data Rate

Cell Spectral Efficiency LatencyMobility

Upto 100 Gbps

Upto 1000 Mbps

Upto 10 bps/Hz

Upto 1 ms

Upto 1000 km/h

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5G

Key Enabling Technologies

mm-wave higher Bandwidth Advanced Carrier aggregation Advanced Modulation and coding (Higher Modulation, FQAM, Advanced channel coding) Large scale antennas (3D Beamforming, Massive MIMO) Advanced Multiple Access Cognitive Radio Device-to-Device Communication Co-ordinated Multi-Point (CoMP)

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Motivation:

Till LTE…. Beamforming is done in horizontal plane Tilt is adjusted either Manually/Remotely

Challenges for 5G. Excess Inter-user Interference in case of multiple narrow beams from multiple

eNodeB antennas. coverage in UMa scenario(high-rise buildings) and near the cell edge. Throughout and capacity is limited.

These challenges can be achieved utilizing the elevation domain results in 3D Beamforming.

Weights are applied on elements of a port account for both horizontal and vertical beam.

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Objective:

Issues highlight In Term-Project

Analyze the challenges and performance of forming a Narrow Beam at predefined Azimuth and Elevation.

Considering Array Geometries (like Linear, Planar & Cylindrical) for narrow beam and propose their suitability for different environment.

Track the user movement with known user locations in both horizontal and vertical direction to mimic the Uma scenario.

Under this scenario, explore the HO possibilities using CoMP feature of LTE-A.

Considering the 3D channel model to account for better realization of 3D Beamforming.

Planar Array Linear ArrayCylindrical Array

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Scope:

Scope is limited to simulations only. Assumptions

Antennas are AAS. User-locations are known. LOS

Adaptation of 3D channel model.

X

(x,y,z)

Z

YAzimuth

Elevation

Source

Array Elements

3D CHANNEL MODELDemonstration Of Active Antenna Array

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Literature survey : (Previous work)

In Ref [1], Lab and field trial measurements has been performed using AAS in a single cell Results indicate high performance of 3D beamforming Algorithm for beamformer weights through UE feedback. For future work, CoMP and network MIMO algorithm will be use together in

multi cell setting.

In Ref [2], Algorithm for reduced inter-user interference through e-tilt assignment and multi-

user selection algorithm. Low-complexity user-scheduling algorithm provides enhanced capacity.

In Ref [3], A scheme for cell sectorization is proposed Sectorization is dynamic , such that it uniformly distributed traffic load in a cell. Sectorization boundaries are function of EL & Az.

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Literature survey : (Previous work) Optimal 3D beam pattern is achieved using convex optimization (max. Main lobe

s.t Side-lobes reduced) UE position determination algorithm is also proposed (so that BS knows UE lies

in which sector)

In Ref [4], An Information-theoretic 3D channel model that incorporates elevation angle

also is proposed. Random parameters in channel model equation makes theoretical analysis

difficult and thus analytical channel model based on principal of maximum entropy is also presented.

In Ref [5], Some measurements has been carried out for dynamic tilt adaptation. Different cases, like cell splitting, UE specific and cell specific beam is considered. Two scenarios, Noise-limited and Interference limited, is considered.

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Literature survey : (Previous work) In Ref [6],

Current status and challenges of FD-MIMO are presented.

Status : 2D-AAS and 3D channel models are implemented with improve

performance. Challenges :

Wide beam formation (Ant virtualization) in large antenna regime for control signal and CQI measurement

Frame-work of FD-MIMO for LTE/LTE-A. High complexity of antenna calibration. Feedback and codebook design in FDD. Accurate channel estimation with low-complexity. User-scheduling

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Results :

We simulate narrow beam in Large Antenna case using Taylor window and Dolph chebychev in Linear, Planar and Cylindrical array with assumption of AAS, known user-location and LOS.

Narrow Beam Pattern of ULA (32×1)

Using Taylor Window (Az=0 , El=0) Using Chebychev Window (Az=45 , El=-20)

User Tracking (Az=0, El=0) to (Az=45, El=-20)

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Results :

Narrow Beam Patterns of URA (32×32) :

Using Taylor Window (Az=0 , El=0) Using Chebychev Window (Az=45 , El=-20)

Horizontal Beam Pattern Vertical Beam Pattern

User Tracking (Az=0, El=0) to

(Az=45, El=-20) :

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Results :

Narrow Beam Patterns of Cylindrical Array (8×128)

Using Taylor Window (Az=60 , El=0) Using Chebychev Window (Az=170 , El=0)

User Tracking (Az=0, El=0) to (Az=70, El=0)

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Conclusion 3D Beamforming is one of the key feature of 5G, as mm-wave is used so narrow beam is highly

needed and thus it becomes necessary to consider elevation domain.

Through measurements and proposed algorithm in different research papers, it is established that 3D Beamformer significantly enhances cellular system efficiency.

AAS is the enabling technology of 3D Beamforming.

Suggested future work in 3D Beamforming Incorporating 3D channel model for more practical realizations. Incorporating more features of LTE-A like CoMP, User-scheduling algorithm , network

MIMO algorithm with 3D Beamforming.

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References

[1] Koppenborg, Johannes, et al. "3D beamforming trials with an active antenna array." Smart Antennas (WSA), 2012 International ITG Workshop on. IEEE, 2012.

[2] Zhang, Yiyan, et al. "Antenna Tilt Assignment for Three-Dimensional Beamforming in Multiuser Systems." 2015 IEEE Global Communications Conference (GLOBECOM). IEEE, 2015.

[3] Lee, Chang-Shen, et al. "Sectorization with beam pattern design using 3D beamforming techniques." Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific. IEEE, 2013.

[4] Nadeem, Qurrat-Ul-Ain. 3D Massive MIMO Systems: Channel Modeling and Performance Analysis. Diss. 2015.

[5] Godara, Lal C. "Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations." Proceedings of the IEEE 85.8 (1997): 1195-1245.

[6] Xu, Gary, et al. "Full-dimension MIMO: Status and challenges in design and implementation." 2014 IEEE Communication Theory Workshop (CTW). 2014.