Low Complexity Virtual Antenna Arrays Using Cooperative Relay Selection Aggelos Bletsas, Ashish...
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Low Complexity Virtual Antenna Arrays Using Cooperative Relay Selection
Aggelos Bletsas, Ashish Khisti, and Moe Z. Win
Laboratory for Information and Decision Systems (LIDS)
Massachusetts Institute of Technology
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Outline
Motivation
System Model
Protocols with Cooperative Relay Selection Zero-Feedback Single-Bit Feedback (single or multiple rounds)
Concluding Remarks
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Motivation (1) Cooperative communications
Node cooperation to improve the performance of wireless networks by coordination of terminals distributed in space.
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Motivation (2) Cooperation has been widely viewed as a
distributed, multiple relay, transmission problem: Using distributed Phased-array techniques
or Using distributed Space-Time Coding
Phased-array techniques require tracking and control of
multiple carrier-phase differences
Space-Time Coding for multiple antennas is an open area of
research
Both become less practical due to the distributed nature of the
Relay Channel
Both increase the complexity and cost of the transceiver.
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Motivation (3)
Simplification of cooperative communication to minimize the required hardware complexity and
cost
“Distributed single-relay selection”
“Can we achieve globally optimal cooperation simply by single-relay transmission?”
Phased Array and Space-Time Coding Techniques
increase the complexity and cost of the transceiver
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System Model (1) Canonical case of half-duplex, narrow-band, dual-hop
communication:
Phase I Phase II
Node “A”
Node “B”
( )CNAB AB0,
Rayleigh f ading
a W:
Received signal in a link A B:
B AB A Ba= +y x n
( )2AB AB AB
AB
1 :
exponential distribution
with hazard rate 1
g a ¡ W
W
@ :
Results has been extended to generalized fading models (e.g. Nakagami-m)A. Bletsas, A. Khisti, M. Z. Win, “Unifying Cooperative Diversity, Routing and Feedback with Select and Forward Protocols”, submitted to IEEE Transactions on Communications.
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System Model (2)
Performance metric: Diversity order-multiplexing gain tradeoff (DMT)
: Outage Probability as a function of rate, SNR
: Rate
: SNR
: Rate as a function of SNR
: SNR
Diversity order
Multiplexing gain
reliability
achievable throughput (degrees of freedom)
DMT averages out relay topology(high SNR tool)
DMT simplifies analysis
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Protocols (1) Key idea 1: among a set of K possible relays, only one will be used
Key idea 2: the selected, “best” relay will be chosen before source transmission (Proactive Relay selection)
Key idea 3: the selected relay will be used only if needed (feedback availability)
Which is the “best” relay to use? Select the relay that maximizes a function of the end-to-end channel conditions:
2 Opportunistic functions: min vs harmonic mean
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Protocols (2) Opportunistic Relay Selection based on channel conditions: fading
mitigation Proactive Relay Selection: relays not used enter idle mode and total
reception energy is minimized
Harmonic mean is a scaled version of the min
Maximum of exponentials is of the same order of the sum
Those functions are simple and carefully chosen.
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Protocols (3)
Intuition: to select the tallest student in a classroom, you don’t need to measure each of them, but instead ask all of them to stand up and have the tallest observe the class and raise her hand.
Distributed relay selection: to find out the max element in a set, you don’t need to know the individual value of all elements in the set. Distributed timer method has been proposed, analyzed and
implemented in simple radios. Without requiring global CSI at each relay or at a central
controller in the network.
A. Bletsas, “Intelligent Antenna Sharing in Cooperative Diversity Wireless Networks”, Ph.D. Dissertation, Massachusetts Institute of Technology, September 2005.
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Protocols (4) Direct (non-cooperative) communication
Proactive Relay selection and Zero-Feedback
Proactive Relay selection and single round of single-bit Feedback
The cycle source tx-feedback tx-best relay tx can be repeated L times
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Discussion
Proactive relay selection Simplify the receiver design and the overall network
operation (which is equivalent to routing). May seem that selecting a single relay before the
source transmission would degrade performance.
Results show that there is no performance loss!
Single relay transmission May seem that a single relay transmission would
degrade performance.
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Results (1)
diversity order d on the number of cooperating nodes K+1. feedback can improve rate r (from 0.5 -> 1) without requiring
simultaneous transmissions. Multiple rounds L of feedback further improve performance.
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Results (2)
analysis includes both amplify-and-forward as well as decode-and-forward relays.
recent results include generalized fading models as well as reactive protocols where relay is selected after source transmission.
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Concluding Remarks (1) Put forth simple opportunistic relay selection rules for
decode-and-forward (DaF) or amplify-and-forward relays and provided DMT analysis.
Studied the impact of feedback with multiple relays.
Showed that single relay selection is equivalent to complex space-time coding, even though simpler.
Proactive opportunistic relaying reduces the reception energy cost in the network.
Energy-efficient routing
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Concluding Remarks (2)
Our results reveal that relays in cooperative communications can be viewed not only as active re-transmitters but also as distributed sensors of the wireless channel.
Cooperative relays can be useful even when they do not transmit, provided that they cooperatively listen.
Cooperation benefits can be cultivated with simple radio implementation.
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Thank You!
This research was supported, in part, by
The Office of Naval Research Young Investigator Award N00014-03-1-0489,
The National Science Foundation under Grant ANI-0335256,
The Charles Stark Draper Laboratory Robust Distributed Sensor Networks
Program
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Models and Protocols (4)
Distributed relay selection
Distributed timer method Without requiring global CSI at each relay
or a central controller in the network