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Why Protocols? Queues have time-varying state –Might be empty sometimes In effect, # of active nodes is time varying Design for Max # of user is conservative –Underutilized network for many traffic “Active” management of queue states = Medium Access Protocols q2q2 q1q1 S1S1 S2S2 q3q3 S3S3
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General Theory of Wireless Networks with Side Information
Ahmad Khoshnevis, Debashis DashRice University
Nokia SeminarFebruary 10, 2006
Wireless Networks
• High data rate– WiMax, Mesh– 802.11x– 4G
• Irony– Current protocols such as 802.11 cause 30-50% non-data
communication (overhead)
First question: Is existence of protocols necessary?
Why Protocols?
• Queues have time-varying state– Might be empty sometimes
• In effect, # of active nodes is time varying
• Design for Max # of user is conservative– Underutilized network for many traffic
“Active” management of queue states = Medium Access Protocols
q2
q1 S1
S2
q3
S3
How Much Overhead?
Second Question: What is the minimum amount of overhead? How can it be reduced?
Observation
• If S1 knows q2 and S2 knows q1
– No need for handshaking
– TDMA scheduling– No collision
• As load increases– Probability of queue empty reduces– Network utility increases
Having the “side information” aboutQueue states, increases the utilization
1
2q2
q1 S1
S2
D
Implementation of the idea
• Perfect carrier sense no collision
• While q1 and q2 non empty– TDMA guarantees no collision
• When – q1 and q2 are empty – |t1-t2| < – Collision happens
• Collision resolution takes resources– Modeled as wasted time, c
• Probability of Collision is determined by probability of q1=q2=
q1 S11
2q2
S2
D
t
S2
S1
t1t2
c
Performance
Generalization
• In general “side information”– Queue state– Number of nodes– Battery life, …
• Catch• The “side information” is not of interest, data is• Gathering “side information” requires resources
– Perfect information causes a lot of overhead– Partial information gives more room for data, but more uncertainty
Fundamental Tradeoff
There is a tradeoff between amount of side information and total throughput of a network.
What is the maximum data rate for a given amount of side information?
New Source Model
• There are two information need to be transmitted– The actual data, M– The source state, S
• The message– Conveys useful information– Need to be sent error free
• The source state– Can’t be sent perfectly (takes all the capacity)– The rate of source information is controlled by distortion between S
and S’
M
S S’X
S.Enc
C.E
nc
New Source Model
Channel Model
• Discrete memoryless channel
• The channel is described by P{Y|X1,X2}
Formulating the Problem
Additional Insights
• Particularly in our approach– Generalization of side information & being independent of
interpretation– Addressing penalty associated with knowing side information
• Considered in earlier models– Is extendable to a network with arbitrary number of users– Simultaneously can answer both question
• Total network throughput• Per user throughput
Road Map
• Improving the Model– More interesting case is conferencing
• Find I(M1,M2;Y|S’1,S’2)• Properties of solution space and possible solution for special
cases