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Increasing cellular capacityIncreasing cellular capacity
using cooperative networksusing cooperative networksShivendra S. Panwar
Joint work with Elza Erkip, Pei Liu, Sundeep Rangan, Yao Wang
Polytechnic Institute of NYU
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OutlineOutline
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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OutlineOutline
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 heterogeneousCellular Networks are becoming heterogeneous
Macrocell based network architecture isexpensive and cannot keep up with user demand(Ciscos 66X traffic increase prediction)
Heterogeneous networks enable
flexible 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-buildingcoverage
Reduces operating cost, such as backbone cost, siteacquisition cost, and utility cost for operators
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Emerging trends and our researchEmerging 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 bedrained by increased deployment of WiFi, femto/picocells forstationary or slow moving users
Femtocells, in particular, are the carriers Trojan Horses!
Macrocell bandwidth is precious and should be used only whenthere is no alternative (like satellite networks are today)
Cooperative networking can be used in such emergingenvironments by using user end devices, femtocells, WiFiaccess points, picocells, and macrocell infrastructure as thedevices that constitute the cooperating nodes
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Cooperation and HeterogeneityCooperation and Heterogeneity
Cooperation performs much better if the number ofrelays 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
operators network
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Motivation for CooperationMotivation 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 tounicast.
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 athigher 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 andapplication layers is required to address this problem.
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Relaying in commercial systemsRelaying in commercial systems
Cooperative / multihop communications have beenadopted in the next generation wireless systems.
IEEE 802.11sEnables multihop and relays at MAC layer, does not providefor joint PHY-layer combining.
IEEE 802.16jExpands previous single-hop 802.16 standards to includemultihop capability. Integrated into IEEE 802.16m draft.
3GPP LTECooperative multipoint is supported with joint transmissionsand receptions to enable cost-effective throughputenhancement and coverage extension.
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OutlineOutline
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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Robust Cooperative MIMO DesignRobust Cooperative MIMO Design
Limitations of previous cooperative methods: Single relay: low spatial diversity gain
Multiple relays: consume more bandwidth resource when severalrelays sequentially forward signal
Any alternative?
Distributed Space-Time Coding (DSTC) How does DSTC work?
Recruit multiple relays to form a virtual MIMO
Each relayemulates an indexed antenna
Each relaytransmits 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 MIMORobust Cooperative MIMO
Randomized cooperation strategies provide powerful PHY layercoding 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 spatialmultiplexing.
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 instantaneousfading levels
Signaling overheads and channel feedback greatly reduced
Performance comparable to centralized MIMO is attained
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R-DSTC: A New SolutionR-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 indexedantenna
Instead, each relay transmits a weighted linear combination of all streams of anunderlying STC codeword of size L x K.
As long as the number of relays N>L-1, a diversity order ofL is achieved.
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R-DSTC AdvantagesR-DSTC Advantages
DSTC R-DSTC
Only selected relays forward.Low diversity gain.
All relays that overhear first hop signal canrelay.High diversity gain.
Global and latest channel information
REQUIRED for rate selection.
Detailed channel information NOT
REQUIRED; outdated estimates can beused.
STC codeword allocation REQUIRED. STC codeword allocation NOTREQUIRED; transmissions can simply berandomized.
Tight synchronization among relays
REQUIRED.
Tight synchronization among relays NOT
REQUIRED.
Received power unbalanced. Average received power from all relaysbalanced.
Performance degrades whenever anyselected relay fails to relay.
Full diversity order of L is reached whenN>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
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Number of Subscriber Stations
Throughput(Mbps)
Single-hop
Two-hop Single-helper (CoopMAC)
Two-hop R-DSTC Channel Statistics
Two-hop R-DSTC User Count
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Delay(seconds)
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Two-hop Single-helper (CoopMAC)Two-hop R-DSTC Channel Statistics
Two-hop R-DSTC User Count
R-DSTC Performance (WiFi)R-DSTC Performance (WiFi)
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CoopMAX: A Cooperative Relaying Protocol inCoopMAX: A Cooperative Relaying Protocol in
Mobile WiMAX NetworkMobile WiMAX Network
CoopMAX enables robust cooperation in a mobile environmentwith low signaling overheads.
It is robust to mobility and imperfect knowledge of channel state.
Simulation shows 1.8x throughput gain for a single cell withmobility, and 2x throughput gain for multicell deployment.
Single cell
deployment
Multicell deployment
W I C A T
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R-DSM for spatial multiplexingR-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 basedBLAST scheme
The channel capacity between the relays and the destinationsscales 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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PerformancePerformance
Our results demonstrate that R-DSM scheme delivers MIMOsystem 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 MulticastCooperative Video Multicast
Performance of conventional video multicastschemes in an access network is limited
Source transmits atthe lowesttransmission rate
Receivers with
good channel qualityunnecessarily suffer
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Cooperative Video Multicast with R-DSTCCooperative Video Multicast with R-DSTC
Source station transmitsa packet
Nodes who receivethe packets become relayswhich re-encodethe first-hop signals andforward over the second hop
Each relay transmits a
weighted linear combinationof all streams ofan underlying STCwith a dimension of
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Results: Single Layer SchemesResults: Single Layer Schemes
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OutlineOutline
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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Cooperative MIMO for Heterogeneous NetworksCooperative MIMO for Heterogeneous Networks
For high mobility MSs or MSs that are covered by any femtocell,cooperative MIMO enables fully opportunisticuse of all available surrounding radios.
increases network capacity and helps to reduce coverage holes.
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Cooperative handoff for Pico/FemtocellsCooperative 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 bycooperative relaying
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Cooperative Handoff for delay tolerantCooperative Handoff for delay tolerant
applicationsapplications
Macrocell BS tracks the locations of the MS and makes handoffpredictions based on which pico/femtocell BSs the MS ismoving 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 MSusing 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 CoordinationCooperative Interference Coordination
Pico/femtocell BS deployments are unplanned with vastlydifferent power levels compared to macrocell BSdeployments
The interference patterns are significantly different
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Ra
te(bps/Hz)
Reuse 1
Orthog
HK
Han-Kobayashi
Orthogonalization
Treat interferenceas noise
Current cellular systemstreat interference as noise,which is not effective for highinterference levels
Dynamic orthogonalization orHan-Kobayashi is needed
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Very bad links(restricted
assoc)
Macro cell - planned
Short-range model
Very goodlinks
(SNR>10 dB)
Changing Interference ConditionsChanging Interference Conditions
Macro - unplannedLoss fromrandomness
(~2dB)
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Belief Propagation SolutionBelief Propagation Solution
Iterative message passing algorithm
Widely used in coding, non-Gaussian estimation,machine learning
Pass beliefs along edges of graphs representingestimates of the marginal distribution
Natural distributed implementation for wireless.
Similar methods used in many approximate BP algorithmsfor 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 ProtocolBP 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 scheduledalong TX vector
x1
Round 0
Round 1
Datatransmission
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Interference Coordination with RelaysInterference 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 signalrelaying and/or interference forwarding could be optimal undercertain 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 interferencecoordination
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OutlineOutline
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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The Second-Last Mile ProblemThe 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 backhaulhas become thebottleneck!
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Solution: FemtoHaulSolution: FemtoHaul
System Architecture for FemtoHaul FemtoHaul is a novel solution to the macrocell backhaul problem.
In FemtoHaul, the femtocellbackhaul is used to carry non-
femto user traffic by forwardingthrough 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 EvaluationFemtoHaul Performance Evaluation
Backhaul SupplyRate Comparison Average Download Ratein 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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OutlineOutline
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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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 TestbedsCooperative Networking Testbeds
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W SS I C O A C T C O OG
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Implementing Cooperative PHYImplementing Cooperative PHY
Cooperative protocols require changes inthe PHY layer Commercial devices do not give access to PHY
Use Wireless Access Research Platform (WARP), aSDR 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 SystemWARP System
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Implementing Cooperative MAC forImplementing Cooperative MAC for
IEEE 802.11IEEE 802.11
Use open source drivers and commercialWiFi 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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OutlineOutline
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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ConclusionsConclusions
Cooperation is a perfect match for the emergingheterogeneity in wireless communications
Robust cooperative schemes (R-DSTC, R-DSM) requirelittle overhead and well suited even for MSs with highmobility
Heterogeneous networks provide many capable relays forcooperation Cooperative handoff
Cooperative interference coordination
FemtoHaul: Offload traffic from constrained macrocellbackhaul to abundant femtocell backhaul
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TThankhank YYou!ou!
Our Cooperative Research website:
http://coop.poly.edu
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BackupBackup
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Synchronization IssuesSynchronization Issues
Nodes cooperating without central control will encounter thepractical 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 ofcooperative 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 lockto a common reference signal. For example, the source cancontinuously 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 dispersivelinks, IEEE Transactions on Communications, vol. 57, no. 1, pp. 64-68, January 2009.
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Incentives for cooperationIncentives for cooperation
Cooperative relaying improves network capacity and reducesdelay. In a wireless LAN, throughput for each individual node can be
improved.
In a cellular network, the BS can provide incentive for relays byallocating more time/frequency resources to relays.
Battery consumption Average Joule/Bit performance is improved.
Energy consumption for nodes acting as relays (CoopMAC) is alsoreduced in wireless LANs2.
By employing several relays, the energy consumption for eachindividual relay is just 1/L of the case of employing one relay.
It is possible that a nodes battery drains faster because it acts as arelay 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 PersonalCommunications Special issue on cooperation in wireless networks Vol 43 No 1 pp 65-87 2007
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