Wideband Channel Tracking for mmWave MIMO System with ...cores.ee.ucla.edu/images/e/ef/CAMSAP_final_version.pdf · Wideband Channel Tracking for mmWave MIMO System with Hybrid Beamforming

Wideband Channel Tracking for mmWave MIMO

System with Hybrid Beamforming Architecture

Han Yan, Shailesh Chaudhari,

and Prof. Danijela Cabric

Dec. 13th 2017

D. Markovic / Slide 2

Intro: Tracking in mmW MIMO

MMW network features massive arrays– Beamforming gain in Tx & Rx to

compensate propagation loss

– Multiplexing gain for throughput boost

– Reduced interference

– Vulnerable to beam misalignment

2

BS sector

Fig. BS and UE needs to adaptively change beamformer for reliable communication in mmW MIMO system

t0

t1

Channel state information (CSI) is crucial in mmW MIMO – Channel estimation: training w/o using priori knowledge

● Widely used in sub-6GHz band

● High training overhead in mmW

– Channel tracking: updates CSI w/ priori knowledge

● Potentially reduce overhead

Rx beam

Tx beam

D. Markovic / Slide 3

Outlines

Mobile channel model for algorithm design & evaluation– 3GPP narrowband mobile model for above-6GHz band

– Wideband mmW mobile model

CSI tracking algorithm design– Propagation angle tracking

– Compressive sensing based narrow-band channel tracking

– Proposed wideband channel tracking

Performance-complexity study on tracking algorithms – SINR and achievable rate

– Training overhead

– Computational complexity

3

D. Markovic / Slide 4

DSP

...

mmW UE

ADCDSP

...

mmW BS

DAC

...

Rx ULATx ULA

System Model

Symbol Description Symbol Description

𝑁R, 𝑁T Rx/Tx antenna size𝐰𝑚, 𝐯𝑚

Beamformer of 𝑚𝑡ℎ channel probing in Tx and Rx𝜙, 𝜃 Angle of arrival (AOA); Angle of departure (AOD)

𝐚R(𝜙)𝐚T(𝜃)

Spatial response of ULA of specific angle;

𝑔𝑚

Post-Beamforming channel

4

Precoder 𝐰𝑚 Combiner 𝐯𝑚MIMO

Channel 𝐇

2D narrow band mmW channel model (𝐿 paths)

Post-BF Channel 𝑔𝑚

D. Markovic / Slide 5

3GPP spatially-consistent UT mobility modelling [G17]

– Channel variation 𝐇(𝑛) determined by 𝛼𝑙(𝑛)

, 𝜃𝑙(𝑛)

, and 𝜙𝑙(𝑛)

– At 𝑡0: set BS, UE scatterer location; channel coefficient initialization

– At 𝑡𝑛: update channel coefficient from 𝑡𝑛−1

Narrowband Dynamic Channel Model

5

2D moving trajectory

UE Location

Speed: 𝑣[cos(𝛽) sin(𝛽)]T

BS Location

Channel coeff. at 𝑡𝑛−1{𝜙𝑙

𝑛−1, 𝜏𝑙

𝑛−1, 𝛼𝑙

(𝑛−1)}

Channel coeff. at 𝑡𝑛{𝜙𝑙

(𝑛), 𝜏𝑙

(𝑛), 𝛼𝑙

(𝑛)}

ScattererAOA

Gain (from delay)

Channel Coefficients updates (𝛥𝑡 = 𝑡𝑛-𝑡𝑛−1)

𝛽

𝝓𝒍

D. Markovic / Slide 6

Wideband Dynamic Channel Model

6

ScattererCluster

UE Location

Channel coeff. at 𝑡𝑛−1{𝜙𝑙,𝑟

𝑛−1, 𝜏𝑙,𝑟

𝑛−1, 𝛼𝑙,𝑟

(𝑛−1)}

Channel coeff. at 𝑡𝑛{𝜙𝑙,𝑟

(𝑛−1), 𝜏𝑙,𝑟

(𝑛−1), 𝛼𝑙,𝑟

(𝑛−1)}

Modified model for wideband channel– 𝑅 rays within each of 𝐿 multipath clusters

– Pulse shaping function 𝑝c(𝑡) due to band-limited nature in T/Rx

– UE 2D moving: channel parameters evolve with similar manner

– UE rotation: AOA of all rays incremented by 𝑣r ⋅ Δ𝑡

D. Markovic / Slide 7

Wideband Dynamic Channel Model

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Time & freq. domain WB mobile channel

Frequency Domain (subcarrier 𝑘)Discrete Time Domain (delay 𝑑)

[WSH+16] Y. Wang, Z. Shi, L. Huang, Z. Yu, and C.Cao, “An Extension of Spatial Channel Modelwith Spatial Consistency,” in Proc. IEEE 84thVehicular Technology Conference (VTC-Fall),2016, pp. 1–5.

Top: Simulated results of delayprofile & AOA versus time 𝑡𝑛 usingproposed model

Bottom: Measured results in denseurban environment (at 73 GHz)[WSH+16]

Illustration of mobile channel simulation

D. Markovic / Slide 8

Problem Statement

Tracking procedure at 𝑡𝑛– BS sends 𝑀 beacons with

– UE measures post-BF channel

𝑔𝑚(𝑛)

[𝑘] with

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Update chan. parameters

{𝜶𝒍,𝒓(𝒏−𝟏)

, 𝝓𝒍,𝒓(𝒏−𝟏)

, 𝝉𝒍,𝒓(𝒏−𝟏)

}

Chan. measurement

using 𝐖𝒎(𝒏−𝟏)

and 𝐕𝒎(𝒏−𝟏)

Update chan. parameters

{𝜶𝒍,𝒓(𝒏), 𝝓𝒍,𝒓

(𝒏), 𝝉𝒍,𝒓

(𝒏)}

Chan. measurement

using 𝐖𝒎(𝒏)

and 𝐕𝒎(𝒏)

𝑡𝒏−𝟏 𝑡𝒏

𝑔𝑚(𝑛−1)

[𝑘] 𝑔𝑚(𝑛)

[𝑘]

Rx ULATx ULA

DSP

...

mmW UE

ADCDSP

...

mmW BS

DAC

... ..

.

...

𝐯𝑚(𝑛)

𝐇f(𝑛)

[𝑘]

𝒈𝒎(𝒏)[𝒌]

𝐰𝑚(𝑛)

Tracking objective– Given probing beamformer 𝐖 𝑛 and 𝐕 𝑛 , design tracking algorithm to

update channel parameters

D. Markovic / Slide 9

Prior-Art: AOA Tracking

Tracking via angle refinement – Probing beams: narrow beams

– Previous CSI*: 𝜃 and 𝜙(𝑛−1)

– Algorithm: RSS measurement into neighbor angles

9

Fig. UE refines steer angle based on pointing direction from previous time slot

Steering angle at 𝑡𝑛−1

Neighbor steering angle trial at tn

Adopted in IEEE802.11ad (Beam Refinement Protocol) [NCF+14]– Low computational complexity: energy measurement & comparison

* Dominant propagation angle is tracked and subscription 𝑙 is omitted; Can be extension to all angles[NCF+14] Nitsche et al, “IEEE 802.11ad: directional 60 GHz communication for multi-Gigabit-per-second Wi-Fi [Invited Paper],” IEEE Commun. Mag., vol. 52, no. 12, p. 132, 2014.

D. Markovic / Slide 10

Compressive narrowband (NB) chan. probing procedure – Probing beams: quasi-omni beams

● Fixed over 𝑛

● Pseudorandom value {±1 ± 1𝑗} in elements of 𝐖 and 𝐕

● Probe all angles in a compressed manner

– Previous CSI: መ𝜃𝑙, 𝜙𝑙(𝑛−1)

and ො𝛼𝑙(𝑛−1)

– Measured post-BF channel

Prior-Art: NB Channel Tracking

10

[MRM16] Z. Marzi, D. Ramasamy, and U. Madhow, “Compressive Channel Estimation and Tracking for Large Arrays in mm-Wave Picocells,” IEEE J. Sel. Topics Signal Process., vol. 10, no. 3, pp. 514–527, Apr. 2016.

𝜃𝑙 is assumed to be known and constant; Such constant (Tx gain) is absorbed in 𝛼𝑙

Post beamforming noise

– Adapted from [MRM16]

D. Markovic / Slide 11

Prior-Art: NB Channel Tracking

Parameter updating algorithm for NB channel

– Alternative update estimated path gain 𝛼𝑙(𝑛)

and AOA 𝜙𝑙(𝑛)

based on 𝐠(𝑛)

– Each step can be approximately solved by LS

– Moderate complexity: pseudo-inverse of a 𝑀 ×𝑁t matrix

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Gain update step for all 𝑙

AOA update step for all 𝑙

next tracking slot

D. Markovic / Slide 12

Proposed wideband (WB) channel probing procedure – Probing beams: 𝐿 narrow beams for each of the cluster

– Previous CSI*: 𝜃𝑙,𝑟, 𝜙𝑙,𝑟(𝑛−1)

, 𝜏𝑙,𝑟(𝑛−1)

, and 𝛼𝑙,𝑟(𝑛−1)

– Measured effective channel (1st probing beam for example)

WB Channel Tracking Procedure

𝐚T( ഥ𝜃𝑙) 𝐚R ത𝜙𝑙(𝑛−1)

𝑙 ≤ 𝐿

ഥ𝜃𝑙 ത𝜙𝑙(𝑛−1)

𝑙

12

From other multipath cluster & AWGN; Treated as effective noise

D. Markovic / Slide 13

WB Channel Tracking Algorithm

Channel coefficients update algorithm

13

Delay Refinement: update delay coeff. via

where and is the post-BF channel w/ estimated channel coeff at 𝑡𝑛−1

Angle Refinement: updates AOA coeff. via

where with other coeff. at 𝑡𝑛−1

Gain Refinement: solve for

where and is matrix with other coeff. at 𝑡𝑛−1

D. Markovic / Slide 14

Channel Parameter Initialization

Tracking requires channel coeff. estimation at 𝑡0– Assuming rough angle estimation ҧ𝜃1 and ത𝜙1 are reached

– Use 𝐚T(𝜃1) and 𝐚R ത𝜙1(𝑛−1)

for post-BF channel probing 𝐠1(0)

– Orthogonal matching pursuit (OMP) based initialization

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Dictionary

The 𝑝th column contains freq-domain support due to delay pΔ𝜏

The post-BF channel probing results

𝒈1(0)

consists of up to 𝑅 supports

Set of selected index 𝒯

Contains selected 𝜏1,𝑟 items

D. Markovic / Slide 15

Metric: spectral efficiency (SE) after beamforming– Scenario of transmission 1 stream

Performance Metrics

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𝐰data[𝑘] 𝐯data[𝑘]

𝒂t(𝜃) 𝒂r(𝜙) 𝜃 𝜙

𝐇

𝐇f[𝑘]𝑘th

𝐇f[𝑘]𝑘th

𝑡0

𝐇f[𝑘]𝑘th 𝑡0

– SVD based beamforming 𝐰data and 𝐯data as primary eigenvector of MIMO channel

– As SE upper bound for actual hybrid architecture

– BF w/ NB CSI: same BF for all sub-carriers

– BF w/ WB CSI: unique BF for each sub-carrier

D. Markovic / Slide 16

Simulation: SE v.s. Time

16

Fig. spectral efficiency over time with CSI from tracking;

𝑁T = 𝑁R = 16

• 𝐿• 𝑅

•

•

• 𝐾

• 𝑁s

D. Markovic / Slide 17

Training Overhead

Re-estimation

(w/o Tracking)

Prop. Angle

Tracking

NB Channel

Tracking

WB Channel

Tracking

Interval btw

Channel Est. 100 ms 500 ms* 500 ms 500 ms

Channel Est.

Frame Num.256** 256 256 256

Interval btw

Tracking- 10 ms 10 ms 4 ms

Tracking Frame

Num.- 6 10 2

Overhead*** 3.84% 1.67% 2.23% 1.52%

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Overhead

* Multipath scatterers may significantly change after moving beyond coherence distance, which is assumed to be 10m (1 s w/ 10m/s speed)** Advanced channel estimation approach may significantly reduces required channel estimation frames*** A frame length is assumed to be 15𝜇𝑠; Results are conservative since additional higher layer overheads are not considered

D. Markovic / Slide 18

Conclusions & Future Works

We have proposed a wideband mmWave mobile channel model– Facilitate tracking algorithm evaluating

We have proposed a wideband channel tracking algorithm– Improved performance over narrowband tracking approach by using lower

training overhead

Future works– Study the impact of probing beamformer in tracking performance

– Study the overhead & capacity trade-off in channel tracking

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D. Markovic / Slide 19

Thanks for your attention!

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D. Markovic / Slide 20

References

[G17] 3GPP, “TR38.900 Study on channel model for frequency spectrum above 6 GHz (Release 14),” Jul. 2017 [online available] http://www.3gpp.org/DynaReport/38-series.htm

[M17] 5GPPP, “mmMAGIC project D2.2 Measurement Results and Final mmMAGIC Channel Models,” May. 2017 [online available] https://5g-mmmagic.eu/results/#deliverables

[NCF+14] Nitsche et al, “IEEE 802.11ad: directional 60 GHz communication for multi-Gigabit-per-second Wi-Fi [Invited Paper],” IEEE Commun. Mag., vol. 52, no. 12, p. 132, 2014.

[WSH+16] Y. Wang, Z. Shi, L. Huang, Z. Yu, and C. Cao, “An Extension of Spatial Channel Model with Spatial Consistency,” in Proc. IEEE 84th Vehicular Technology Conference (VTC-Fall), 2016, pp. 1–5.

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