Andrea Goldsmith

Stanford University

Accelera, Inc.

IEEE SCV ComSoc meeting May 8, 2013

Wireless networks are everywhere, yet…

- Connectivity is fragmented

- Capacity is limited (spectrum crunch

and interference)

- Roaming between networks is ad hoc

TV White Space &

Cognitive Radio

Software Defined Wireless Networking (SDWN): Accelera’s Architecture

WiFi AP Small Cell Dual Mode

Wifi/LTE

ACCELERA “MAESTRO” UNIFIED CONTROL PLANE

Wireless HW

Cloud-Based Control, Management, and Radio Resource Management Plane

Careful what you wish for…

Growth in mobile data, massive spectrum deficit and stagnant revenues require technical and political breakthroughs for ongoing success of cellular

“Sorry, America: Your wireless airwaves are full” CNNMoneyTech – Feb. 2012

The “Spectrum Crunch”

Are we at the Shannon limit of the Physical Layer?

Time-varying channels with memory/feedback.

We don’t know the Shannon capacity of most wireless channels

Channels with interference or relays.

Uplink and downlink channels with frequency reuse, i.e. cellular systems.

Channels with delay/energy/$$$ constraints.

Rethinking “Cells” in Cellular

Traditional cellular design “interference-limited” MIMO/multiuser detection can remove interference Cooperating BSs form a MIMO array: what is a cell? Relays change cell shape and boundaries Distributed antennas move BS towards cell boundary Small cells create a cell within a cell Mobile cooperation via relaying, virtual MIMO, analog network coding.

Small Cell

Relay

DAS

Coop MIMO

How should cellular systems be designed?

Will gains in practice be big or incremental; in capacity or coverage?

Are small cells the solution to increase cellular system capacity?

Yes, with reuse one and adaptive techniques (Alouini/Goldsmith 1999)

A=.25D2p

Area Spectral Efficiency

S/I increases with reuse distance (increases link capacity). Tradeoff between reuse distance and link spectral efficiency (bps/Hz).

Area Spectral Efficiency: Ae=SRi/(.25D2p) bps/Hz/Km2.

The Future Cellular Network: Hierarchical Architecture MACRO: solving initial coverage issue, existing network

FEMTO: solving enterprise & home coverage/capacity issue

PICO: solving street, enterprise & home coverage/capacity issue

10x Lower HW COST

10x CAPACITY Improvement

Near 100% COVERAGE

Macrocell Picocell Femtocell

Today’s architecture • 3M Macrocells serving 5 billion users

Managing interference between cells is hard

Traditional Macro vs. SON Enabled H-RAN

Macro BS Only H-RAN: Macro + Pico BS

H-RAN advantage

10x CAPACITY

10x lower $/Mbps

~100%

COVERAGE

Chicago Downtown Modeling Assumptions:

1. Chicago Downtown model (Calculation area: 64.5 km2)

2. 38 Macro BS sites (3 sectors)

3. 340 Pico BS (3 sectors)

4. ~66000 users were simulated with Monte Carlo method

Macro BS Macro + Pico optimized Users trying to connect 66680 66680 Connected users 31023 50902 Effective MAC Aggregate Throughput (DL) 1020 Mbps 12 060 Mbps Effective MAC Aggregate Throughput (UL) 389 Mbps 4 204 Mbps

12x

Macro BS - Cost Per Mbps $1,341/Mbps

Pico BS - Cost Per Mbps $111/Mbps

CapEx Reduction Factor (no backhaul/site acq)

Deployment Challenges

Deploying One Macrocell Effort

(MD – Man Day)

New site verification 1

On site visit: site details verification 0.5

On site visit: RF survey 0.5

New site RF plan 2

Neighbors, frequency, preamble/scrambling code plan

0.5

Interference analyses on surrounding sites

0.5

Capacity analyses 0.5

Handover analyses 0.5

Implementation on new node(s) 0.5

Field measurements and verification 2

Optimization 2

Total activities 7.5 man days

5M Pico base stations in 2015 (ABI)

• 37.5M Man Days = 103k Man Years

•Exorbitant costs

•Where to find so many engineers?

Small cell deployments

require automated self-

configuration via software

Basic premise of self-

organizing networks (SoN)

SON for LTE small cells

Node

Installation

Initial

Measurements

Self

Optimization

Self

Healing

Self

Configuration Measurement

SON

Server

SoN

Server

Macrocell BS

Mobile Gateway Or Cloud

Small cell BS

X2

X2 X2

X2

IP Network

Small cells cause low interference to macrocells

On DL, UE associates with macrocell only if power higher

On UL, channel gain from UE to small cell large, hence lower power required minimal interference.

Standards-based ICIC protects large cells

On DL, small cell avoids transmission on PRBs when macrocell transmits at high power, typically to cell-edge users.

Small cell causes low interference to other PRBs due to their low power.

On UL, small cell lowers transmit power cell when macrocell indicates high interference via an HII message or an OI message.

Will small cells “destroy” large ones?

Can trade off aggressive frequency reuse against interference

Algorithmic Challenge: Complexity

Optimal channel allocation was NP hard in

2nd-generation (voice) IS-54 systems

Now we have MIMO, multiple frequency

bands, hierarchical networks, …

But convex optimization has advanced a lot

in the last 20 years

Stage 3 Use genetic search to find further improvements by mutating some “genes”

Innovation needed to tame the complexity

Small cells/SoN improve robustness

SON algorithm detects failures in macro/pico/femto BSs

Dynamically adjusts TX power and antenna tilt of to

cover “orphaned” mobiles

Similar algorithm used to shut down BSs to save energy

Macrocell BS Failure Small Cell BS Failure

Can 802.11 solve the spectrum

crunch? “The Good” & “The Bad”

Ubiquitous

Free [unlicensed] spectrum

Standards based [sort of]

Established silicon

ecosystem

Large ODM base

Not “Carrier-Grade”

Poor and variable Quality-of-

Experience

No seamless handoffs

Enterprise Grade very

expensive and not scalable for

massive deployments

WiFi provides high-speed connectivity in the home, office, and in public hotspots.

WiFi protocols based on the IEEE 802.11 family of standards: 802.11a/b/g/n

Next-gen 802.11ac offers peak rate over 1 Gbps.

Designed based on access points (APs) with 50ft range and for low-density deployments.

Severe interference in dense deployments.

WiFi Networks Today

The WiFi standard lacks good mechanisms to mitigate interference in dense AP deployments Static channel assignment, power levels, and carrier sensing

thresholds

In such deployments WiFi systems exhibit poor spectrum reuse and significant contention among APs and clients

Result is low throughput and a poor user experience

Problem Statement

Why not use SoN for WiFi?

SoN-for-WiFi: dynamic self-organization network software to manage of WiFi APs.

Allows for capacity/coverage/interference mitigation tradeoffs.

Also provides network analytics and planning.

SoN Controller

- Channel Selection - Power Control - etc.

SoN-for-WiFi Challenges Algorithm complexity

Cloud-based interface to WiFi chipsets

Lack of synchronization

Lack of control over some APs and other ISM-band devices

WiFi spectrum complements scarce

and bifurcated cellular spectrum

Current solution is device-driven Wi-Fi offload

• User sessions are disrupted during Offload

• Require software on clients (handset, tablets,…) • Requires supporting innumerable number of hardware &

software combinations

• Quality-of-Service (QOS) is not guaranteed

• Ad-hoc offload generally ad-hoc

Solution: Network-Initiated Offload:

Benefits of Network-Initiated HO

Exploits all-IP backbone of LTE and WiFi Seamless offload between LTE and WiFi No client on handset needed Simultaneous access to LTE and WiFi network

services Intelligent handoff LTEWiFi and WiFiLTE

based on load and network conditions Preserve connections on both networks and

visibility into user activity

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Summary Future wireless networks will divorce HW and SW, with

commodotized HW and cloud SW to manage it

Cellular networks must support explosive data growth through small cells and WiFi handoff

WiFi must “grow up” to provide a better user experience through centralized (SoN) control

Seamless handoff between networks is required to enable the wireless cloud demanded by users