Ravi Tandon Osvaldo Simeone

ISIT 2016, Barcelona

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Cloud-Aided Wireless Networks withEdge Caching: Fundamental Latency Trade-Offs

in Fog Radio Access Networks

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• Content delivery, e.g., video, is driving growth in wireless traffic

Introduction

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• Content delivery, e.g., video, is driving growth in wireless traffic

Introduction

• Edge- vs cloud-based solutions

Introduction

EN ENEN EN

ENCache

EN: Edge Node

• Cache-aided wireless network (or edge caching): storage of popular content at wireless edge nodes [Golrezaei et al ‘12]

• Reduces latency due to backhaul usage

Introduction

• Information-theoretic analysis of cache-aided interference channels

- Achievable 1/DoF for 3 3 system [Maddah-Ali and Niesen ‘15]

- Bounds on 1/DoF for more general models with caching also at the receiver [Naderializadeh et al ‘16] [Hachem et al ‘16] [Xu et al ’16]

• Cloud-aided wireless network (or C-RAN): Centralization of baseband processing at the cloud

cloud

EN ENEN EN

EN EN: Edge Node

fronthaul

Introduction

Introduction

• (Digital) fronthauling approaches:

- Hard fronthaul transfer [Patil and Yu ‘14]- Soft fronthaul transfer: Fronthaul compression [Simeone et al ‘14]

• Centralized interference management

cloud

EN EN EN EN

EN

fronthaul

Fog-RAN (F-RAN)

cloud

fronthaul

EN ENEN EN

EN

CacheEN: Edge Node

• Fog Radio Access Network (F-RAN): Cloud and cache-aided wireless network for content delivery

• Optimal operation of an F-RAN: complex design problem over fronthaul, cache and spectral resources

• Fundamental trade-off between delivery latency and system resources

Fog-RAN (F-RAN)

System Model

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System Model

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System Model

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System Model

• Quasi-static channel model with continuous distribution• Power constraint P 13

System Model

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System Model

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System Model

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Cache-Fronthaul-Edge Policy

Time

Tx interval

• Cache storage policy: What to cache

- No knowledge of instantaneous users’ requests and CSI

- No inter-file coding (intra-file coding allowed)

file cached content at EN k ,

TimeCaching interval

Tx interval

Cache-Fronthaul-Edge Policy

Time

Tx interval

Cache-Fronthaul-Edge Policy

• Cache storage policy: What to cache

• Fronthaul policy: What to transmit on the fronthaul links

- Based on instantaneous users’ requests and CSI

Time

Tx interval

Cache-Fronthaul-Edge Policy

• Cache storage policy: What to cache

• Fronthaul policy: What to transmit on the fronthaul links

• Edge transmission policy: What to transmit on the wireless channel

- Based on instantaneous users’ requests and CSI

• Delivery time per bit (e.g., [Liu and Erkip ’11])

Fronthaul Wireless Time

Tx interval

FT ET

Normalized Delivery Latency• Serial fronthaul-edge transmission

user's requests( , , ) limmax F EF L

T TC PL

• Delivery time per bit (e.g., [Liu and Erkip ’11])

Fronthaul Wireless Time

Tx interval

FT ET

Normalized Delivery Latency• Serial fronthaul-edge transmission

user's requests( , , ) limmax F EF L

T TC PL

( , log , )( , ) lim1/ logP

r P PrP

• Normalized Delivery Time (NDT):

Ideal system: interference-free and unlimited caching

Normalized Delivery Latency• Pipelined fronthaul-edge transmission

FronthaulWireless

Time

Tx interval

T• Delivery time per bit and NDT

and

• Practical implications in, e.g., [Leconte et al ‘16]

user's requests( , , ) limmaxF L

TC PL

( , log , )( , ) lim1/ logP

r P PrP

Main Result: NDT for 2 2 of F-RANs

Theorem: The minimum NDT for the 2 2 F-RAN with is given as

*

1 2max 1 ,2 for 0 1( , r)

11 for 1

rr

rr

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Main Result: NDT for 2 2 of F-RANs

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Main Result: NDT for 2 2 of F-RANs

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Main Result: NDT for 2 2 of F-RANs

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Full caching:Cooperative zero-forcing beamforming

at the ENs

Main Result: Achievability

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No caching:Zero-forcing

beamforming at the cloud + soft-

transfer fronthauling

(compression with bits/

sample)

Main Result: Achievability

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Caching of half file:Interference

alignment on an “X-channel”

[Motahari et al ‘14] [Cadambe and

Jafar ‘09]

Main Result: Achievability

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Main Result: Converse

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Main Result: Converse

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Main Result: Converse

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Main Result: Converse

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Main Result: Converse

• Information cut 1:

• Information cut 2:

• Information cut 3:

• Linear combinations of the inequalities above yield the desired result

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Conclusions and Outlook• F-RAN leverages the synergy and complementarity of

cloud processing and edge caching

• Definition of NDT as high-SNR worst-case latencyrelative to an ideal system

• Characterized the NDT for a 2×2 system

• Extensions (see arXiv w/ Avik Sengupta):- General lower and upper bounds- Characterization of NDT for a general

F-RAN within a multiplicative gap of 2- Extension to pipelined model

• Open problems: partial connectivity, imperfect CSI, …