Wideband Channel Tracking for mmwave MIMO System with Hybrid Beamforming Architecture

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Wideband Channel Tracking for mmwave MIMO System with Hybrid Beamforming Architecture Han Yan, Shailesh Chaudhari, and Prof. Danijela Cabric Dec. 13 th 2017

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 BS sector Tx beam Rx beam Fig. BS and UE needs to adaptively change beamformer for reliable communication in mmw MIMO system t 1 t 0 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 D. Markovic / Slide 2 2

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 D. Markovic / Slide 3 3

System Model......... Precoder w m MIMO Channel H Combiner v m DSP DAC ADC DSP mmw BS Tx ULA Post-BF Channel g m Rx ULA 2D narrow band mmw channel model (L paths) mmw UE Symbol Description Symbol Description N R, N T φ, θ Rx/Tx antenna size Angle of arrival (AOA); Angle of departure (AOD) w m, v m Beamformer of m th channel probing in Tx and Rx a R (φ) a T (θ) Spatial response of ULA of specific angle; g m Post-Beamforming channel D. Markovic / Slide 4 4

Narrowband Dynamic Channel Model 3GPP spatially-consistent UT mobility modelling [G17] Channel variation H (n) determined by α l (n), θl (n), and φl (n) At t 0 : set BS, UE scatterer location; channel coefficient initialization At t n : update channel coefficient from t n 1 Scatterer Channel coeff. at t n 1 {φ l n 1, τ l n 1, α l (n 1) } φ l 2D moving trajectory BS Location Channel Coefficients updates (Δt = t n -t n 1 ) AOA Gain (from delay) UE Location β Channel coeff. at t n {φ l (n), τl (n), αl (n) } Speed: v[cos(β) sin(β)] T D. Markovic / Slide 5 5

Wideband Dynamic Channel Model Modified model for wideband channel R rays within each of L multipath clusters Pulse shaping function p c (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 v r Δt Scatterer Cluster Channel coeff. at t n 1 {φ l,r n 1, τ l,r n 1, α l,r (n 1) } UE Location Channel coeff. at t n (n 1) (n 1) (n 1) {φ l,r, τl,r, αl,r } D. Markovic / Slide 6 6

Wideband Dynamic Channel Model Time & freq. domain WB mobile channel Discrete Time Domain (delay d) Frequency Domain (subcarrier k) Illustration of mobile channel simulation Top: Simulated results of delay profile & AOA versus time t n using proposed model Bottom: Measured results in dense urban environment (at 73 GHz) [WSH+16] [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. D. Markovic / Slide 7 7

Problem Statement............... w m (n) H f (n) [k] v m (n) DSP DAC ADC DSP mmw BS g m (n) [k] Tx ULA Rx ULA mmw UE Tracking procedure at t n BS sends M beacons with UE measures post-bf channel g m (n) [k] with t n 1 Chan. measurement using W m (n 1) and Vm (n 1) g m (n 1) [k] Update chan. parameters (n 1) (n 1) (n 1) {α l,r, φl,r, τl,r } t n Chan. measurement using W m (n) and Vm (n) gm (n) [k] Update chan. parameters (n) (n) (n) {α l,r, φl,r, τl,r } Tracking objective Given probing beamformer W n and V n, design tracking algorithm to update channel parameters D. Markovic / Slide 8 8

Prior-Art: AOA Tracking Tracking via angle refinement Probing beams: narrow beams Neighbor steering angle trial at t n Previous CSI * : θ and φ (n 1) Algorithm: RSS measurement into neighbor angles Fig. UE refines steer angle based on pointing direction from previous time slot Steering angle at t n 1 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 9 9

Prior-Art: NB Channel Tracking 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: መθ l, φ l (n 1) and αl (n 1) Measured post-bf channel Post beamforming noise θ l is assumed to be known and constant; Such constant (Tx gain) is absorbed in α l Adapted from [MRM16] [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. D. Markovic / Slide 10 10

Prior-Art: NB Channel Tracking Parameter updating algorithm for NB channel Alternative update estimated path gain α l (n) and AOA φl (n) based on g (n) Gain update step for all l next tracking slot AOA update step for all l Each step can be approximately solved by LS Moderate complexity: pseudo-inverse of a M N t matrix D. Markovic / Slide 11 11

WB Channel Tracking Procedure Proposed wideband (WB) channel probing procedure Probing beams: L narrow beams for each of the cluster ഥθ l തφ l (n 1) a T ( ഥθ l ) a R തφ l (n 1) l L l Previous CSI * (n 1) (n 1) (n 1) : θ l,r, φ l,r, τl,r, and αl,r Measured effective channel (1 st probing beam for example) From other multipath cluster & AWGN; Treated as effective noise D. Markovic / Slide 12 12

WB Channel Tracking Algorithm Channel coefficients update algorithm Gain Refinement: solve for where and is matrix with other coeff. at t n 1 Delay Refinement: update delay coeff. via where and is the post-bf channel w/ estimated channel coeff at t n 1 Angle Refinement: updates AOA coeff. via where with other coeff. at t n 1 D. Markovic / Slide 13 13

Channel Parameter Initialization Tracking requires channel coeff. estimation at t 0 Assuming rough angle estimation ҧ θ 1 and തφ 1 are reached Use a T (θ 1 ) and a R തφ 1 (n 1) for post-bf channel probing g 1 (0) Orthogonal matching pursuit (OMP) based initialization Dictionary The p th column contains freqdomain support due to delay pδτ The post-bf channel probing results g 1 (0) consists of up to R supports Set of selected index T Contains selected τ 1,r items D. Markovic / Slide 14 14

Performance Metrics Metric: spectral efficiency (SE) after beamforming Scenario of transmission 1 stream SVD based beamforming w data and v data as primary eigenvector of MIMO channel As SE upper bound for actual hybrid architecture BF w/ NB CSI: same BF for all subcarriers BF w/ WB CSI: unique BF for each sub-carrier t 0 w data [k] v data [k] a t (θ) a r (φ) θ φ H H f [k] k th k th H f [k] H f [k] k th t 0 D. Markovic / Slide 15 15

Simulation: SE v.s. Time N T = N R = 16 L R Fig. spectral efficiency over time with CSI from tracking; K N s D. Markovic / Slide 16 16

Training Overhead Overhead Interval btw Channel Est. Channel Est. Frame Num. Interval btw Tracking Tracking Frame Num. Re-estimation (w/o Tracking) Prop. Angle Tracking NB Channel Tracking WB Channel Tracking 100 ms 500 ms* 500 ms 500 ms 256** 256 256 256-10 ms 10 ms 4 ms - 6 10 2 Overhead*** 3.84% 1.67% 2.23% 1.52% * 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 17 17

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 D. Markovic / Slide 18 18

Thanks for your attention! D. Markovic / Slide 19 19

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. D. Markovic / Slide 20 20