Radio Resource Management

1
Radio Resource Management

• Roy Yates
• WINLAB, Rutgers University
• Airlie House Workshop

2
What is Radio Resource Mgmt?

• Assign channel, xmit power for each user
• Cellular networks, packet radio networks

Receiver Technology User Services
How does it work? How well does it work?
3
Fixed Channel Allocation (FCA)

• Assign orthogonal channels to cells
• to meet coarse interference constraints
• e.g. adjacent cells cannot use same channel
• Allocation depends on offered traffic/cell
• offline measurements
• graph coloring
• OR - not radio

4
FCA Problems

• Traffic in each cell?
• Coarse interference constraints
• Interference depends on detailed propagation
• Microcells require too many measurements
• Better heuristics offer small performance benefits

5
Dynamic Channel Allocation

• Queueing network models
• No measurements, partial state information
• max packing, borrowing
• Everitt 89 Cimini, Foschini, I, Miljanic, 94
• Measurements
• Least Interference, Maxmin SIR?
• Common Wisdom
• DCA for light loads, FCA for high loads

6
Impact of Qualcomm IS-95

• 1 channel no frequency planning
• CDMA research became practical
• Existence proof that power control could work
• Any interference suppression helps
• Multiuser Detection
• Emphasis on signal measurements

7
CDMA System Model
SIR1
SIRi
SIRN
8
CDMA Signals

• Interference suppression Choose ci to max SIR
• Power Control Choose pi for SIR G

9
SIR Constraints

• Feasibility depends on link gains, receiver
  filters

10
Simple Power Control

• Algorithm
• Each user uses minimum transmit power to meet
  SIR objective
• Monotonicity
• Lowering your transmit power creates less
  interference for others
• Consequence Powers converge to a global minimum
  power solution

11
Adaptive Power Control

• SIR Balancing
• Aein 73, Nettleton 83, Zander 92,
  FoschiniMiljanic 93
• Integrated BS Assignment
• Hanly 95, Yates 95
• Macrodiversity
• Hanly 94
• Link Protection/Admission Control
• Bambos, Pottie 94, Andersin, Rosberg, Zander
  95
• Note Adaptive PC analysis is deterministic

12
CDMA and Antenna Arrays

• si CDMA signature Antenna signature
• ci Receiver filter Antenna weights
• CDMA Interference Suppression
• in signal space
• e.g. Lupas, Verdu, 89
• Antenna beamforming
• in real space
• Winters, Salz, Gitlin 94

13
Linear Filtering with Power Control

• 2 step Algorithm
• Rashid-Farrokhi, Tassiulas, Liu, Ulukus,
  Yates
• Adapt receiver filter to maximize SIR
• Given powers, use MMSE filter Madhow, Honig 94
• Given receiver, use min transmit power to meet
  SIR target
• Converges to global minimum power solution

14
Wireless Voice vs Wireless Data

• Voice
• Delay sensitive
• msec OK
• Maximum rate
• Minimize the probability of outage

• Data
• Delay insensitive
• sec OK? hours OK?
• No Maximum Rate
• Maximize the time average data rate

15
Wireless Data

• Current Data Standards
• Cellular modem, CDPD (AMPS)
• IS-99/IS-707 (for IS-95)
• GPRS (for GSM)
• Proposed Solutions
• EDGE, space time codes
• 3G WCDMA

Low rate service, cellular price
Complex solutions
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Optimizing Data Services

• Channel Quality (link gain) is stochastic
• Rayleigh and shadow Fading,
• Distance propagation
• Use more power when the channel is good
• Reduce power when the channel is bad
• Water filling in time
• Goldsmith 94

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Optimizing Wireless Data Networks

• Anytime/Anywhere is a design choice
• good for voice networks
• reduces system capacity
• users near cell borders create lots of
  interference
• Infostations Low cost pockets of high rate
  service

18
Unlicensed Bands

• FCC allocated 3 bands (each 100 MHz) around 5
  GHz
• Minimal power/bandwidth requirements
• No required etiquette
• How can or should it be used?
• Dominant uses?
• Non-cooperative system interference

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Interference Avoidance

• Old Assumption Signatures of users never change
• New Approach Adapt signatures to improve SIR
• Receiver feedback tells transmitter how to
  adapt.
• Application
• Fixed Wireless
• Unlicensed Bands

20
MMSE Signature Optimization
Iterative Algorithm Match si to
ci Convergence?
ci MMSE receiver filter
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Optimal Signatures

• N users, proc gain G, NgtG
• Signature set S s1 s2 sN
• Optimal Signatures?
• IT Sum capacity Rupf, Massey
• User Capacity Viswanath, Anantharam, Tse
• WBE sequences SSt (N/L)I are optimal
• Property MMSE filter matched filter

22
MMSE Signature Optimization

• RX i converges to MMSE filter ci
• TX i matches RX si ci
• Some users see more interference, others less
• Other users iterate in response
• Preliminary Result
• Users at 1 BS converge to optimal WBE signatures
• Interference Avoidance
• Generalizations to arbitrary systems

23
Unresolved Questions

• Multicell systems
• Capacity?
• Old Problem Interference Channel
• MMSE Effectiveness?
• Dimensionality of antenna arrays?
• Systems in unlicensed bands?
• Architectures for Data Networks?