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WIRELESS INTERNET CENTER FOR ADVANCED TECHNOLOGYNSF INDUSTRY/UNIVERSITY COOPERATIVE RESEARCH CENTER

Increasing cellular capacityusing cooperative networks

Shivendra S. PanwarJoint work with Elza Erkip, Pei Liu, Sundeep Rangan, Yao Wang

Polytechnic Institute of NYU


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Outline Motivation for Cooperation Robust Cooperative MIMO Design

Randomized Space Time Coding Randomized Spatial Multiplexing

Cooperation in Heterogeneous Network Cooperative Handover Cooperative Interference Coordination

Combating Macrocell Backhaul Bandwidth Shortage Implementation Efforts Conclusions


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Cellular Networks are becoming heterogeneous

Macrocell based network architecture isexpensive and cannot keep up with user demand (Cisco’s 66X traffic increase prediction)

Heterogeneous networks enableflexible and low-cost deployments andprovide a uniform broadband experience The network becomes a mix of macro, pico, femto base

stations and operator deployed relay stations The dense deployment greatly improves network capacity,

and provides richer user experience and in-building coverage

Reduces operating cost, such as backbone cost, site acquisition cost, and utility cost for operators


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Emerging trends and our research

The future network architecture is heterogeneous, with macro-, pico- and femto-cells, along with WiFi and (some) ad hoc nodes

A large part of the 66x increase predicted by Cisco will be drained by increased deployment of WiFi, femto/picocells for stationary or slow moving users

Femtocells, in particular, are the carrier’s Trojan Horses!

Macrocell bandwidth is precious and should be used only when there is no alternative (like satellite networks are today)

Cooperative networking can be used in such emerging environments by using user end devices, femtocells, WiFi access points, picocells, and macrocell infrastructure as the devices that constitute the cooperating nodes


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Cooperation and Heterogeneity Cooperation performs much better if the number of

relays is large In a macrocell based deployment, the number of operator

deployed relay stations will be limited In traditional networks, the performance gain for cooperation

is limited unless user (MS) cooperation is enabled But user cooperation gives rise to the following problems:

battery consumption, synchronization, security and incentive

The proliferation of pico/femto base stations will provide enough relays (“femtorelays”) They do not have the battery consumption problem They are easier to synchronize:

stationary, backbone connection and better radio design They are more secure because they are part of the

operator’s network


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Motivation for Cooperation Wireless channel by nature is a broadcast one.

The broadcast channel can be fully exploited for broadcast traffic. But it is considered more as a foe than a friend, when it comes to

unicast. Cooperative communications allow the overheard information be

treated as useful signal, instead of interference. Relays process this overheard information and forward to

destination. Network performance improved because edge nodes transmit at

higher rate thus improving spectral efficiency. Candidate relays?

Mobile user, macro/pico-cell BS, fixed relays, femtocell BS, etc. What are the incentives? Throughput, power, interference.

A cross-layer design encompassing physical, MAC, network and application layers is required to address this problem.


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Relaying in commercial systems Cooperative / multihop communications have been

adopted in the next generation wireless systems.

IEEE 802.11sEnables multihop and relays at MAC layer, does not provide for joint PHY-layer combining.

IEEE 802.16jExpands previous single-hop 802.16 standards to include multihop capability. Integrated into IEEE 802.16m draft.

3GPP LTECooperative multipoint is supported with joint transmissions and receptions to enable cost-effective throughput enhancement and coverage extension.


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Robust Cooperative MIMO Design Limitations of previous cooperative methods:

Single relay: low spatial diversity gain Multiple relays: consume more bandwidth resource when several

relays sequentially forward signal Any alternative?

Distributed Space-Time Coding (DSTC) How does DSTC work?

Recruit multiple relays to form a virtual MIMO Each relay emulates an indexed antenna Each relay transmits encoded signal corresponding to its antenna index

Pros: Spatial diversity gains Cons:

Tight synchronization required Relays need to be indexed, leading to considerable signaling cost Global channel state information needed Good DSTC might not exist for an arbitrary number of relays Unselected relays cannot forward, sacrificing diversity gain


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Robust Cooperative MIMO Randomized cooperation strategies provide powerful PHY layer

coding techniques that alleviate the previous problems and allow robust and realistic

cooperative transmission with multiple relays. randomize distributed space-time coding (R-DSTC) for diversity. randomized distributed spatial multiplexing (R-DSM) for spatial

multiplexing. Highlights of randomized cooperation:

Relays are not chosen a-priori to mimic particular antennas Multiple relays can be recruited on-the-fly Relays are used opportunistically according to instantaneous fading

levels Signaling overheads and channel feedback greatly reduced Performance comparable to centralized MIMO is attained


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R-DSTC: A New Solution Randomized Distributed Space-Time Coding (R-DSTC) How does R-DSTC work in PHY?

Two-hop network: source station, relays, destination station. Relays re-encode the first-hop signals and forward over the second hop

Unlike DSTC, R-DSTC relay does NOT transmit the signal from a specific indexed antenna

Instead, each relay transmits a weighted linear combination of all streams of an underlying STC codeword of size L x K.

As long as the number of relays N>L-1, a diversity order of L is achieved.


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R-DSTC Advantages

DSTC R-DSTCOnly selected relays forward. Low diversity gain.

All relays that overhear first hop signal can relay.High diversity gain.

Global and latest channel information REQUIRED for rate selection.

Detailed channel information NOT REQUIRED; outdated estimates can be used.

STC codeword allocation REQUIRED. STC codeword allocation NOT REQUIRED; transmissions can simply be randomized.

Tight synchronization among relays REQUIRED.

Tight synchronization among relays NOT REQUIRED.

Received power unbalanced. Average received power from all relays balanced.

Performance degrades whenever any selected relay fails to relay.

Full diversity order of L is reached when N>L .

Performance Comparison


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• Underlying orthogonal STBC codeword size: 2, 3, 4.• PHY layer rates: 6, 9, 12, 18, 24, 36, 48, 54 • BPSK, QPSK, 16-QAM, 64-QAM; Convolutional code 1/2, 2/3, 3/4• 20 MHz bandwidth • Contention window: 15 -1023• Transmit power: 100mW

16 32 48 64 80 961

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3

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Number of Subscriber Stations

Thro

ughp

ut (M

bps)

Single-hopTwo-hop Single-helper (CoopMAC)Two-hop R-DSTC Channel StatisticsTwo-hop R-DSTC User Count

8 16 24 32 40 480

0.02

0.04

0.06

0.08

0.1

Number of Subscriber Stations

Del

ay (s

econ

ds)

Single-hopTwo-hop Single-helper (CoopMAC)Two-hop R-DSTC Channel StatisticsTwo-hop R-DSTC User Count

R-DSTC Performance (WiFi)


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CoopMAX: A Cooperative Relaying Protocol in Mobile WiMAX Network CoopMAX enables robust cooperation in a mobile environment

with low signaling overheads. It is robust to mobility and imperfect knowledge of channel state. Simulation shows 1.8x throughput gain for a single cell with

mobility, and 2x throughput gain for multicell deployment.

Single cell deployment Multicell deployment


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R-DSM for spatial multiplexing Mismatch in the number of antennas on BS and MS

Assuming each mobile station has only one antenna and the base station has L antennas

Randomized Distributed Spatial Multiplexing (R-DSM) is based BLAST scheme

The channel capacity between the relays and the destinations scales linearly with min(N,L), where N is the number of relays

How does R-DSM work in PHY? Two-hop network: SISO transmission from source to relays first, followed by

relays transmitting together to the destination using R-DSM. Each relay independently generates a random coefficient and then

transmits a weighted sum of the signals for each antenna in BLAST scheme


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Performance Our results demonstrate that R-DSM scheme delivers MIMO

system performance Average data rate for the second hop (relays-destination link) scales with

the number of relays For direct transmissions, the peak data rate is supported at a short range R-DSM can increase the number of stations that can transmit near the peak

data rate


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Cooperative Video Multicast

Performance of conventional video multicast schemes in an access network is limited

Source transmits atthe lowesttransmission rate

Receivers withgood channel quality unnecessarily suffer


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Cooperative Video Multicast with R-DSTC

Source station transmitsa packet

Nodes who receivethe packets become relays which re-encodethe first-hop signals and forward over the second hop

Each relay transmits aweighted linear combination of all streams ofan underlying STCwith a dimension of


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Results: Single Layer Schemes


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Outline

Motivation for Cooperation Robust Cooperative MIMO Design





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Cooperative MIMO for Heterogeneous Networks

For high mobility MSs or MSs that are covered by any femtocell, cooperative MIMO enables fully opportunistic use of all available surrounding radios. increases network capacity and helps to reduce coverage holes.


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Cooperative handoff for Pico/Femtocells

Handoffs happen much more frequentlyfor MSs in a heterogeneous network Smaller BS coverage area Loosely planned or unplanned deployment Higher signaling overheads and more dropped calls

Cooperative handoffs in Heterogeneous Networks Separate signaling and data paths

Macrocell BS orchestrates handoff and allocates radio resources for data transmissions

User data goes through surroundingpico/femtocell BSs either through their backhaul or by cooperative relaying


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Cooperative Handoff for delay tolerant applications Macrocell BS tracks the locations of the MS and makes handoff

predictions based on which pico/femtocell BSs the MS is moving to.

In the downlink Macrocell BS pre-fetches user data packets to a

cluster of pico/femtocell BSs via their backhauls Macrocell BS allocates frequency/time slots for the

downlink data transmission Pico/femtocell BSs cooperatively transmit to the MS

using R-DSTC In the uplink

Macrocell BS broadcasts the allocated frequency/time slotsfor the MSs

A pico/femtocell BS that successfully decodes an uplink user packet forwards it to the Macrocell BS via its backhaul


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Cooperative Interference Coordination

Pico/femtocell BS deployments are unplanned with vastly different power levels compared to macrocell BS deployments

The interference patterns are significantly different

−30 −20 −10 0 10 200

1

2

3

4

5

6

7

Crossover gain (dB)

Rat

e (b

ps/H

z)

Reuse 1OrthogHK

Han-Kobayashi

Orthogonalization

Treat interference as noise

Current cellular systems treat interference as noise, which is not effective for high interference levels

Dynamic orthogonalization orHan-Kobayashi is needed


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Very bad links (restricted

assoc)

Macro cell - planned

Short-range model

Very good links

(SNR>10 dB)

Changing Interference Conditions

Macro - unplannedLoss from randomness

(~2dB)


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Belief Propagation Solution Iterative message passing algorithm

Widely used in coding, non-Gaussian estimation, machine learning

Pass “beliefs” along edges of graphs representing estimates of the marginal distribution

Natural distributed implementation for wireless. Similar methods used in many approximate BP

algorithms for CDMA multiuser detection & non-Gaussian estimation: Caire, Boutros (’02), Guo-Wang (‘06), Tanaka-Okada (‘05),

Neirroti-Saad (‘05), Kabashima (‘05), Donoho, Maleki, Montanari(‘09), Bayati-Montanari (‘10), Rangan (’10)


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BP Multi-Round Protocol

TX1RX1RX2 TX2

Desired linkInterference Interference

TX vector x2(0)

Sensitivity D2(0)

TX vector x1(0)

Interference z1(0) and sensitivity D1(0)

TX vector x2(1)

Sensitivity D2(1)

TX vector x1(1)

Interference z1(1) and sensitivity D1(1)

Data scheduled along TX vector

x1

Round 0

Round 1

Data transmission


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Interference Coordination with Relays

Still an open problem What are the optimal strategies for transmitters, relays and

receivers to maximize spectrum efficiency? What is the best strategy for relays -

Forwarding signal or forwarding interference? Preliminary information theoretical results show both signal

relaying and/or interference forwarding could be optimal under certain regimes (Elza Erkip)

Missing Components: Practical coding and signal processing schemes for

cooperative interference coordination MAC design that handles the signaling between different

entities participating in the cooperative interference coordination


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Outline






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The Second-Last Mile Problem Explosively growing traffic demand

More than 5 billion cell phones by 2010 Increasing number of data intensive applications 3G/4G standards are pushing up the macrocell data rates

(~100 Mbps)

Poor cellular infrastructure Most of the BS backhauls use four to six T1/E1 lines (~8 Mbps) Adding BSs or updating data lines is expensive

(more than $10,000 per line and $50,000 per site annually)

Macrocell backhaul has become the bottleneck!


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Solution: FemtoHaul System Architecture for FemtoHaul

FemtoHaul is a novel solution to the macrocell backhaul problem.

In FemtoHaul, the femtocell backhaul is used to carry non-femto user traffic by forwarding through a relay.

Detailed Design Channel allocation

mechanism based on OFDMA WiMAX;

Policy for base stations to schedule user transmissions.


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FemtoHaul Performance Evaluation Backhaul Supply

Rate Comparison Average Download Rate

in Stationary Scenario

Simulations demonstrate that our solution can significantly reducethe macrocell backhaul traffic while still guaranteeinga high rate to the subscribers


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Outline






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Goal: Build a large scale experimental, deployable and scalable cooperative network (Erkip, Korakis, Panwar, Liu, Wang, Bertoni) Funding from NSF (MRI, CRI), WICAT, NYU-Poly

We have taken two approaches PHY layer: Software Defined Radio (SDR) platform MAC layer: Open Source Driver Platform on Linux

Cooperative Networking Testbeds


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Implementing Cooperative PHY

Cooperative protocols require changes inthe PHY layer Commercial devices do not give access to PHY Use Wireless Access Research Platform (WARP),

a SDR by Rice University We have a basic three node system operating,

consisting of one source, one relay and one receiver

Cooperative coding using convolutional codes and soft decision decoding implemented

We also have basic R-DSTC implemented


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WARP System



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Implementing Cooperative MAC for IEEE 802.11

Use open source drivers and commercial WiFi cards Advantages

Backward compatible with 802.11 Can be used in large testbeds such as ORBIT

Disadvantages: No access to PHY

(but still gains from Cooperative MAC)



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Outline






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Conclusions Cooperation is a perfect match for the emerging

heterogeneity in wireless communications Robust cooperative schemes (R-DSTC, R-DSM) require

little overhead and well suited even for MSs with high mobility

Heterogeneous networks provide many capable relays for cooperation Cooperative handoff Cooperative interference coordination

FemtoHaul: Offload traffic from constrained macrocell backhaul to abundant femtocell backhaul


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Thank You!

Our Cooperative Research website:http://coop.poly.edu


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Backup


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Synchronization Issues Nodes cooperating without central control will encounter the

practical problem of synchronizing their access to the channel. Distributed relays have no access to a global clock. Relays need to be synchronized both in time and frequency. Synchronization accuracy affects physical layer performance of

cooperative MIMO system. How to achieve synchronization?

4G systems (LTE and WiMAX) synchronize the transmissions from UE both in time and frequency via close-loop control.

In a wireless LAN, relays can be synchronized by letting relays lock to a common reference signal. For example, the source can continuously transmit a reference carrier.

R-DSTC performs well under residual synchronization errors1.

1. M. Sharp, A. Scaglione and B. Sirkeci-Mergen, “Randomized cooperation in asynchronous dispersive links”, IEEE Transactions on Communications, vol. 57, no. 1, pp. 64-68, January 2009.


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Incentives for cooperation Cooperative relaying improves network capacity and reduces

delay. In a wireless LAN, throughput for each individual node can be

improved. In a cellular network, the BS can provide incentive for relays by

allocating more time/frequency resources to relays. Battery consumption

Average Joule/Bit performance is improved. Energy consumption for nodes acting as relays (CoopMAC) is also

reduced in wireless LANs2. By employing several relays, the energy consumption for each

individual relay is just 1/L of the case of employing one relay. It is possible that a node’s battery drains faster because it acts as a

relay for multiple sources, possibly as a result of its position. Not an issue for dedicated fixed relays, or femtocells acting as relays.

2. S. Narayanan and S. Panwar, “To Forward or Not to Forward - That is the Question”, Wireless Personal Communications, Special issue on cooperation in wireless networks, Vol.43, No.1, pp. 65-87, 2007

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