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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016 Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 1 Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks

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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 1

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks

Antti T¨

  • lli

with Praneeth Jayasinghe, Ganesh Venkatraman, Jarkko Kaleva, Markku Juntti, Matti Latva-aho and Le-Nam Tran, e-mail: atolli@ee.oulu.fi Centre for Wireless Communications, University of Oulu, Finland 2016 IEEE Communication Theory Workshop, Nafplio, Greece 16 May, 2016

  • G. Venkatraman, A. T¨
  • lli, L-N. Tran & M. Juntti, ”Traffic Aware Resource Allocation Schemes for Multi-Cell

MIMO-OFDM Systems”, IEEE Transactions on Signal Processing, vol. 64, no. 11, pp. 2730–2745, June 2016.

  • P. Jayasinghe, A. T¨
  • lli & M. Latva-aho, Bi-directional Signaling Strategies for Dynamic TDD Networks in Proc. IEEE

SPAWC 2015, Stockholm, Sweden, July, 2015

  • G. Venkatraman, A. T¨
  • lli, M. Juntti & L-N. Tran ”Queue Aware Precoder Design via OTA Training”, in Proc. 2016

IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Edinburgh, UK, July 3–6, 2016

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 2

Heterogeneous Network Setting

Heterogeneous network composed of

◮ Large macro cells with (massive) MIMO antenna arrays, ◮ Small cells and relays with (distributed) MIMO arrays, and ◮ D2D communication with base station coordination

Backhaul / control Data

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 3

Dynamic TDD

UL and DL control channels UL or DL data channels time frequency

Figure: Flexible TDD frame structure1

Significant load variation between adjacent cells Flexible UL/DL allocation provides large potential gains in spectral efficiency2 More challenging interference management

1Nokia Networks, ”5G radio access system design aspects”, Nokia white paper, Aug. 2015. Available:

http://networks.nokia.com/file/37611/5g-radio-access

23GPP TSG RAN WG1, ”Study on scenarios and requirements for next generation access technologies TR 38.913,” 3rd

Generation Partnership Project 3GPP, www.3gpp.org, 2016

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 4

Dynamic TDD

Figure: UL-DL/DL-UL interference in Dynamic TDD

Additional UL-to-DL and DL-to-UL interference associated with the dynamic TDD Interference mitigated by coordinated beamforming. More measurements and info exchange also at the terminal side Similar interference scenarios in underlay D2D transmission3

  • 3A. T¨
  • lli, J. Kaleva & P. Komulainen, ”Mode Selection and Transceiver Design for Rate Maximization in Underlay D2D

MIMO Systems”, in Proc. IEEE ICC 2015, London, UK, June, 2015

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 5

System Model & Problem Formulation

Interference signal Desired signal

𝑅1 𝑅2 𝑅3 𝑅4 𝑅5 𝑅6 𝑉1 𝑉2 𝑉3 𝑉4 𝑉5 𝑉6

OFDM system with N sub-channels and NB BSs, NT TX antennas per BS K users each with NR antennas Goal: minimize the number of packets in BS queues via joint TX/RX design and resource allocation over spatial and frequency resources

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 6

Queueing Model

Each user is associated with backlogged packets of size Qk packets. Queued packets Qk of each user follows dynamic equation at the ith instant as Qk(i + 1) =

  • Qk(i) − tk(i)

+ + λk(i) (1) where tk = N

n=1

L

l=1 tl,k,n denotes the total number of

transmitted packets corresponding to user k λk represents the fresh arrivals of user k at BS bk

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 7

JSFRA Formulation4

The optimization objective of joint space-frequency resource allocation (JSFRA) to design transmit precoders is minimize

tl,k,n

  • k∈U

ak

  • Qk −

N

  • n=1

L

  • l=1

tl,k,n

  • q

(2) where ak are arbitrary weights used to control the priorities Exponent q = 1, 2, . . . , ∞ plays different role based on the value it assumes Inherent maximum rate constraint: N

n=1

L

l=1 tl,k,n ≤ Qk

Special cases (when Qk > N

n=1

L

l=1 tl,k,n ∀ k):

◮ q = 1: Sum rate maximization ◮ q = 2: Queue-Weighted Sum Rate Maximization (Q-WSRM)

  • 4G. Venkatraman, A. T¨
  • lli, L-N. Tran & M. Juntti, ”Traffic Aware Resource Allocation Schemes for Multi-Cell

MIMO-OFDM Systems”, IEEE Transactions on Signal Processing, vol. 64, no. 11, pp. 2730–2745, June 2016.

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 8

JSFRA Formulation (MSE Reformulation)

The queue minimization problem can be solved by utilizing the relation between the MSE and the SINR as ǫl,k,n = (1 + γl,k,n)−1 (3) Equivalence is valid only when the receivers are designed with the mean squared error (MSE) objective, i.e., using MMSE receivers tl,k,n = − log2(ǫl,k,n) (4a) ǫl,k,n = E

  • (dl,k,n − ˆ

dl,k,n)2 =

  • 1 − wH

l,k,nHbk,k,nml,k,n

  • 2

+

  • (j,i)=(l,k)
  • wH

l,k,nHbi,k,nmj,i,n

  • 2 + `

N0 (4b)

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 9

JSFRA Formulation (MSE Reformulation)

Queue minimization via MSE reformulation

minimize

tl,k,n,ml,k,n, ǫl,k,n,wl,k,n

˜ vq (5a) subject to tl,k,n ≤ − log2(ǫl,k,n) ∀ l, k, n (5b) ǫl,k,n ≥

  • 1 − wH

l,k,nHbk,k,nml,k,n

  • 2

+

  • (j,i)=(l,k)
  • wH

l,k,nHbi,k,nmj,i,n

  • 2 + `

N0 ∀ l, k, n (5c)

N

  • n=1
  • k∈Ub

L

  • l=1

tr (ml,k,nmH

l,k,n) ≤ Pmax ∀b.

(5d)

where ˜ vk a

1 q

k (Qk − N n=1

L

l=1 tl,k,n)

The nonconvex (difference of convex) rate constraints are approximated via successive convex approximation (SCA) method Receive beamformers are designed by the MMSE receivers using the converged TX precoders

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 10

Dynamic Traffic Scenario - Centralized Performance

Time Slots 50 100 150 200 250 Total backlogged bits after each tx slot, Σk (Qk(i) - tk(i))+ 20 40 60 80 100 120 140 JSFRA with q=∞ JSFRA with q=2 JSFRA with q=1 Q-WSRM Q-WSRME Sum arrivals Σk λk (i)

Figure: Queue dynamics for {N, NB, K, NT , NR, Ak} = {4, 2, 12, 4, 1, 6} [G.

Venkatraman, A. T¨

  • lli, L-N. Tran & M. Juntti, ”Traffic Aware Resource Allocation Schemes for Multi-Cell MIMO-OFDM

Systems”, IEEE Transactions on Signal Processing, vol. 64, no. 11, pp. 2730–2745, June 2016.]

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 11

Distributed Methods

Interference signal Desired signal

𝑅1 𝑅2 𝑅3 𝑅4 𝑅5 𝑅6 𝑉1 𝑉2 𝑉3 𝑉4 𝑉5 𝑉6

Overhead of the centralized design is large as the network size grows Distributed approaches based on primal decomposition or ADMM can be used to reduce the signaling Precoder design by solving the KKT expressions of the JSFRA problem (5) via MSE reformulation Practical approach to design precoders with minimal backhaul usage

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 12

KKT Expressions for (5)

m(i)

l,k,n = x∈U L

  • y=1

α(i−1)

y,x,nHH bk,x,nw(i−1) y,x,nwH (i−1) y,x,n

Hbk,x,n + δbINT −1 α(i−1)

l,k,n HH bk,k,nw(i−1) l,k,n

w(i)

l,k,n = x∈U L

  • y=1

Hbx,k,nm(i)

y,x,nmH (i) y,x,nHH bx,k,n + N0INR

−1 Hbk,k,n m(i)

l,k,n

ǫ(i)

l,k,n =

  • 1 − wH (i)

l,k,nHbk,k,nm(i) l,k,n

  • 2

+

  • (x,y)=(l,k)
  • wH (i)

l,k,nHby,k,nm(i) x,y,n

  • 2

+ wl,k,n2N0 t(i)

l,k,n = − log2(ǫ(i−1) l,k,n ) −

  • ǫ(i)

l,k,n−ǫ(i−1) l,k,n

  • log(2) ǫ(i−1)

l,k,n

σ(i)

l,k,n =

  • ak q

log(2)

  • Qk −

N

  • n=1

L

  • l=1

t(i)

l,k,n

(q−1)+ α(i)

l,k,n = α(i−1) l,k,n + ρ(i)

  • σ(i)

l,k,n

ǫ(i)

l,k,n

− α(i−1)

l,k,n

  • c

Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 13

Decentralized Precoder Design - Strategy A

Over-the air (OTA) based iterative algorithm5 with Bi-directional training (BiT)6

m(i)

l,k,n= x∈U L

  • y=1

α(i−1)

y,x,nHH bk,x,nw(i−1) y,x,nwH (i−1) y,x,n

Hbk,x,n + δbINT −1 α(i−1)

l,k,n HH bk,k,nw(i−1) l,k,n

w(i)

l,k,n = x∈U L

  • y=1

Hbx,k,nm(i)

y,x,nmH (i) y,x,nHH bx,k,n + N0INR

−1 Hbk,k,n m(i)

l,k,n

Transmit precoders ml,k,n depend on HH

bk,x,nwy,x,n, i.e., effective

uplink channel Receive beamformers wl,k,n depend on Hbx,k,nmy,x,n, i.e., effective downlink channel Can be measured locally at each node in TDD using precoded pilots

  • 5P. Komulainen, A. T¨
  • lli & M. Juntti, Effective CSI Signaling and Decentralized Beam Coordination in TDD Multi-Cell

MIMO Systems, IEEE Transactions on Signal Processing, vol. 61, no. 9, pp. 2204 – 2218, May 2013

6Changxin Shi; Berry, R.A.; Honig, M.L., ”Bi-Directional Training for Adaptive Beamforming and Power Control in

Interference Networks,” IEEE Transactions on Signal Processing, vol.62, no.3, pp.607–618, Feb.1, 2014

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 14

Signaling Requirement for OTA based Updates7 8

Data

𝑹𝑙 𝜷𝑙𝒙𝑙

∗ Data

𝜷𝑙𝒙𝑙

∗

𝒏𝑙 𝒏𝑙 𝜷𝑙𝒙𝑙

∗ Bi-directional training phase Strategy A Strategy B Forward pilots Backward training pilots

Figure: TDD frame structure with bidirectional signaling

  • 7P. Komulainen, A. T¨
  • lli & M. Juntti, Effective CSI Signaling and Decentralized Beam Coordination in TDD Multi-Cell

MIMO Systems, IEEE Transactions on Signal Processing, vol. 61, no. 9, pp. 2204 – 2218, May 2013

  • 8P. Jayasinghe, A. T¨
  • lli & M. Latva-aho, Bi-directional Signaling Strategies for Dynamic TDD Networks in Proc. IEEE

SPAWC 2015, Stockholm, Sweden, July, 2015

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 15

Assumptions and Evaluation Model

Every BS and user terminal uses orthogonal pilots in UL and DL

  • ver-the-air (OTA) signaling

For simplicity, pilot transmissions used to convey the equivalent channel information in one BiT iteration - consume η resource share.9 Under this assumption, the effective rate by considering the signaling overhead is given as ˜ tl,k,n = (1 − Imax η) × tl,k,n (6) Total number of backlogged packets is evaluated as - χ = K

k=1 [Qk − ˜

tk]+ In all simulations, we consider η = 1%

9In practice, the performance depends on the amount of available pilots and the size of coherence block. c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 16

Average Backlogged Packets - Distributed Design

1 2 3 4 5 6 7

  • avg. arrival pkts per user

500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500

  • avg. backlogged pkts for all users

Centralized Design Uncoordinated Design Strategy A (OTA-3 with Mem) Strategy A (OTA-5 with Mem) Strategy B (OTA-3) Strategy B (OTA-5)

Figure: Average backlogged packets for {N, NB, K, NT , NR} = {3, 2, 12, 4, 2} evaluated over 250 slots with fdTs ≈ 0.1 [G. Venkatraman, A. T¨

  • lli, M. Juntti & L-N. Tran ”Queue

Aware Precoder Design via OTA Training”, in Proc. 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Edinburgh, UK, July 3–6, 2016]

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 17

OTA Signalling in Dynamic TDD10

Downlink Cells Uplink Cell DL channel DL-DL interference UL-DL interference BS1 BS2 BS3

Figure: Interference at DL terminal

DL cell forward phase Users measure DL cell BS pilots and UL cell user pilots DL cell backward phase BSs measure UL cell BS pilots and DL cell user pilots

  • 10P. Jayasinghe, A. T¨
  • lli & M. Latva-aho, Bi-directional Signaling Strategies for Dynamic TDD Networks in Proc. IEEE

SPAWC 2015, Stockholm, Sweden, July, 2015

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 18

OTA Signalling in Dynamic TDD

Downlink Cell Uplink Cells UL channel DL-UL interference UL-UL interference BS1 BS2 BS3

Figure: Interference at UL BS

UL cell forward phase BSs measure UL cell user pilots and DL cell BS pilots UL cell backward phase Users measure DL cell user pilots and UL cell BS pilots

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 19

Bi-directional Signalling: Simulation Setup

4-antenna BSs, 4 2-antenna UEs per BS

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 20

Comparison of Different Signalling Strategies - Sum Rate

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 10 12 14 16 18 20 22 24 26 28

Overhead Actual Rate at SNR = 20 dB

Strategy A Strategy B Strategy C Uncoordinated method

Figure: Actual sum rate at SNR = 20dB vs overhead for different bi-directional signaling strategies, {α, β, γ} = {0, 3, 6}dB. [P. Jayasinghe, A. T¨

  • lli & M. Latva-aho, Bi-directional

Signaling Strategies for Dynamic TDD Networks in Proc. IEEE SPAWC 2015, Stockholm, Sweden, July, 2015]

c Antti T¨

  • lli, CWC
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2016 IEEE Communication Theory Workshop, Nafplio, Greece , 16 May, 2016

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 21

Conclusions

Cross layer design of transmit and receive beamformers based on the number of residual packets was studied

◮ An iterative solution is found by solving a series of convex

subproblems

◮ A practical approach via iterative computation of KKT expressions ◮ Extensions of the proposed work in time-correlated fading scenario

with limited information exchange

Iterative OTA signalling methods can be used in Dynamic TDD and/or underlay D2D to handle the interference due to cross-user channels Future/current work: pilot allocation/decontamination, dynamic cell mode (UL/DL) selection

c Antti T¨

  • lli, CWC