Auxiliary Beam Pair Enabled AoD Estimation for Large-scale mmWave MIMO Systems

www.profheath.org

Dalin Zhu, Junil Choi and Robert W. Heath Jr.

Wireless Networking and Communications Group Department of Electrical and Computer EngineeringThe University of Texas at Austin

This work is funded by a research gift from Huawei Technologies, Inc.

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Hybrid precoding in mmWave MIMO

Most prior work assumes a channel estimate is available for configuration

A combination of digital and analog beamforming/combining

BasebandPrecoding

1-­bitADC

DAC

1-­bitADCDAC

RFChain

RF Precoding

1-­bitADCADC

1-­bitADCADC

BasebandCombining

RF Combining

FBB FRF WBBWRF

RFChain

RFChain

RFChain

channel

Effective channel at baseband

Prior work on channel estimation in mmWave MIMO

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* A. Alkhateeb, O. E. Ayach, G. Leus, and R. W. Heath Jr., ̀ `Channel estimation and hybrid precoding for millimeter wave cellular systems,'' in IEEE J. Sel. Top. Signal Process, vol. 8, pp. 831-846, Oct. 2014** H. Ghauch, T. Kim, M. Bengtsson, and M. Skoglund, ̀ ` Subspace estimation and decomposition for large millimeter-wave MIMO systems,'' submitted to IEEE J. Sel. Top. Signal Process., arXiv preprint arXiv:1507.00287, Jul. 2015*** C. Kim, T. Kim, and J.-Y. Seol, ̀ ` Muti-beam transmission diversity with hybrid beamforming for MIMO-OFDM systems,'' in IEEE Global Telecomm. Conf. (GLOBECOM’13), pp. 61-65, Dec. 2013.

u Compressed sensing based approaches *ª Assumes sparsity in the angular domain of the channelª Requires a prior knowledge of the number of the propagation paths

u Subspace based methods **ª Echo-based subspace estimation between the transmitter and receiverª Requires a lot of training between the transmitter and receiver

u Exhaustive search based approaches ***ª Searches for the best pairs of analog transmit and receive steering vectorsª Training overhead is high

High-resolution estimate of channel

information

Low training and feedback overhead

Feasible channel estimation method is required

Contributions: Path-based channel estimator based on auxilary beam pairs (ABPs)

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Exhuastive search via grid of beams

Each beam is probed

Receiver determines which beams have the strongest signals

The resolution for AoD angle is limited by grid sizeTransmitter

Receiver

Index of preferred beams are sent to the transmitter

Quantization error

True AoD

Quantized AoD

Angle estimation in monopulse radar systems

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Receive beam pair

Signal detectionAmplitude comparison

Angle estimation

Echo signal

Custom designed analog receive beams

Projections of on and

S. M. Sherman, ``Monopulse principles and techniques,'' Artech House, 1984

Beams distinguished by sending with different polarization,

code, or time

Basic design principle of auxiliary beam pairs (1/2)

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. . .

. . .

scatter

: boresight angle of n-th ABP

: steering angle of

: steering angle of

: dominant path’s AoD

: n-th ABP

Transmit array response vector:

System setup

Auxiliary beam pair that covers the AoD:

Pairs of analog transmit beams are formed to cover a given angular range

Exact  AoD can  be  extracted  from  the  ABP  that  covers  the  AoD

Basic design principle of auxiliary beam pairs (2/2)

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is invertible with respect to

If

. . .

. . .

Amplitude comparison

Angle estimation

Calculate received signal strengths

Quantized version of

Quantization options

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Distribution of the ratio metric Distribution of the estimated AoD

More codewords can be allocated in densely distributed portions

Quantizing the ratio metric provides more quantization resolution

Uniformly distributed codewords

Procedure for estimating the AoD using ABP

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Auxiliary beam pairs are probed

A set of ratio metrics are calculated, each corresponds to a ABP

The AoD is estimated using the quantized ratio metric

Transmitter

ReceiverThe ratio metric with the highest

received signal strength is quantized

Deployment scenarios using ABP-based method (1/3)

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Beam finding for control channels

Base station Base station Base station

UE

UE UE

UE UE

UE

Layer-1: system-specific information Layer-2: cell-specific information Layer-3: user-specific information

Beam finding process for control channels is facilitated via ABP design

Beamforming range for the next layer is optimized

using the estimated AoD

Deployment scenarios using ABP-based method (2/3)

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Beam finding for control channelsAn example of control channels beamforming using ABP

Base station

UEbeam-a

beam-b The UE decodes system-specific control information from beam-a

The UE calculates a ratio metric with respect to the ABP formed by

beam-a and beam-b

Base station

UE

The UE quantizes the ratio metric and sends it back to the base station

Base station

UE

Using the quantized ratio metric, the base station estimates the AoD

Base station

UE

1

2 3

The probing range for layer-II beamforming is determined around

the estimated AoD

Base station

UE

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beam-a

beam-b

Layer-I

Layer-II

Deployment scenarios using ABP-based method (3/3)

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Hybrid precoding for data channels

. . .

. . .

. . . . . .

. . . . . .

Base

band

Pre

code

r

DAC

Mixers Phase shifters

PA

Antenna array

Phase shifters Mixers

ADC

Base

band

Com

bine

rDAC

ADC

Antenna array

Multi-path’s AoDs/AoAs can be estimated via ABP

Analog and digital precoder and combiner are optimized using the high resolution estimates of AoDs/AoAs via ABP design

Numerical results (1/2)

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MSE of AoD estimation

: total # of transmit antennas

Parameters

: total # of receive antennas: total # of transmit RF chains

: total # of receive RF chains

: total # of data streams

Channel assumption

: total # of channel paths (6)

ª AoDs/AoAs take continuous valuesª AoDs/AoAs are uniformly distributed

Performance metric: MSE of AoD estimation

In radians

With increase in the number of antennas, more and narrower auxiliary beams are probed, which improves

the estimation performance

Promising MSE performance of AoD estimation can be obtained

Numerical results (2/2)

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Spectral efficiency performance

: total # of transmit antennas

Parameters

: total # of receive antennas: total # of transmit RF chains

: total # of receive RF chains

: total # of data streams

Channel assumption

: total # of channel paths (6)

ª AoDs/AoAs take continuous valuesª AoDs/AoAs are uniformly distributed

Assume , the performance gap is marginal

Multi-path’s AoDs/AoAs estimation performance via ABP design is promising

Conclusionsu High-resolution AoD/AoA estimation method via ABP is possible

ª Suited for mmWave MIMO with directional beamformingª Quantizing the ratio metric results in better performanceª Applicable to beamformed control channels and data channels design in practice

u Future workª ABP-based AoD/AoA estimation assuming arbitrary antenna array geometryª Exploiting TDD channel’s reciprocity to enable mmWave MIMO precodingª Simultaneously employing multiple RF chains to facilitate the estimation

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Questions?

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Backup Slides

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System model for hybrid precoding

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Steering angle

transmit signal vector,

baseband precoder,

Complex Gaussian noise vector

baseband combiner,

analog precoder :analog combiner

similarly defined to

Analog precoder and combiners are simple spatial matched filters

Spatial channel model

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Total number of propagation paths

channel matrix Path-r’s gain

AoD (spatial frequency) to be estimated

AoA (spatial frequency) to be estimated

Assuming ULA

u Received signal with respect to each beam in the ABP (noiseless)

u Received signal strength with respect to each beam in the ABP

u A ratio metric via the difference and sum of and

Detailed derivations of ABP design principle

20is invertible with respect to

If

Performance evaluation of quantization options

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MSE of quantizing the estimated AoD:

MSE of quantizing the ratio metric:

The performance gap between two quantization options is marginal

The receiver requires knowledge of ABP parameters from the transmitter to estimate and quantize the AoD

In radians

Estimation of multiple angles using multiple RF chains (1/2)

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Beam finding for control channelsAn example of multiple AoDs estimation

u Multiple analog beams can be simultaneously probed by the TX and RX

u Consider noiseless reception and a given receive probing ,

u Assume that path-r’s AoD , and

Total number of transmit probings Total number of receive probings

Desired transmit ABP that covers path-r’s AoD Their positions in

Estimation of multiple angles using multiple RF chains (2/2)

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Beam finding for control channelsAn example of multiple AoDs estimation

u The ratio metric that characterizes path-r’s AoD is calculated as

u The quantized version of the ratio metric is fed back to the transmitteru Path-r’s AoD is estimated by the transmitter using the ratio metricu The above process iterates until all paths’ AoDs have been estimated