CDMA/IP-based%20System%20for%20Interoperable%20Public%20Safety%20Radio%20Communications%20

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CDMA/IP-based System for Interoperable Public
Safety Radio Communications   

• Xin Wang
• Director Wireless Networking and Systems Lab
  (WINS)
• Department of Electrical and Computer Engineering
• Stony Brook University
• www.ece.sunysb.edu/xwang

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Problems in Public Safety Systems

• Two main factors limiting the reliability and
  availability of public safety systems
• Different agencies use incompatible systems
  (different frequencies, different modulation or
  encoding, etc).
• Spectrum is limited and fragmented.
• Problems of limited spectrum and incompatibility
• Can not interoperate
• Cannot support wideband data and video
  communications
• Real-time access to mug-shots, finger-prints,
  crime-scene
• Fire-fighting, crowd- and prison control
• Cannot share data among agencies

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Short-term Solutions

• Use dispatching or switch center to manually
  relay signals betweens systems
• Requirements
• Interfaces to all potential systems
• Coordination and involvement of all public safety
  agencies
• Challenges
• Scalability when allocating new frequency band
• Proprietary nature of public safety system

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Long-term Solutions

• Develop modular and scalable systems
• Individual agencies can acquire and expand their
  own wireless systems without compromising
  compatibility
• Cost offset sharing the radio infrastructure
  from various agencies in a region
• Use of more efficient radio technologies,
  especially for new frequency bands

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CDMA/IP-based Wireless Systems

• CDMA
• Easy of deployment, higher capacity, improved
  quality, greater coverage, increased privacy and
  talk time
• IP interface between different systems
• Allowing the interoperability of different bands
• Sharing the networks independent of access
  techniques
• Easy of supporting new radio bands and new
  IP-based technologies while supporting existing
  systems
• Deployment of off-the-shelf and third-party
  products
• Multimedia, location tracking, encryption, VPN

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Future Network Architecture
Micro Base Station
Wireless Gateways
Cellular
Base Station
Bluetooth
-
Radio Hub
-
Wireless Local Area Networks (WLANs)
Wireless Personal Area Networks (WPANs)
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A Sharing and Connection Structure
Public Switched Telephone Network
PAG
PDSN/SGSN
PDSN/SGSN
(PSTN)
(Packet Access Gateway)
(Packet Data Serving Node)
RNC
RNC
RNC
(Radio Network Controller)
BSm
BS i
Area 2
Area 1
BS j
BS k
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Benefit of IP RAN

• More scalable, reliable, and cost effectiv
• Instead of linking individual agency to switching
  center through private or leased lines
• Enable packet-based transportation
• New applications
• Statistical aggregation
• High bandwidth utilization, reduced cost
• Support both wire-line and wireless

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Requirements of Public Safety System

• Round clock availability, secure and private
  communications
• Quality of services (QoS) guarantee
• Voice (low delay and jitter)
• Data (high throughput)
• Video (QoS and throughput)
• Maximize resource usage under scarce spectrum
• Efficient resource management while guaranteeing
• Availability, emergency, QoS

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Challenges Air Interface

• Support transmission quality
• Control power and rate to achieve target Eb/Io
• Power and rate allocation for circuit-based
  transmission (e.g., multimedia)
• Adapt rate of elastic data through scheduling
• Admission control for guaranteeing quality of
  on-going transmissions
• More efficient use of spectrum
• Integrated support of various traffic
• real-time circuit-based and elastic packet-based

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Challenges IP-based Backhaul

• Traffic in RAN is different from general Internet
• Significant amount of traffic is delay sensitive
• Voice, radio frames involved in soft handoff
• Majority of handoffs involve RAN
• Interruptions during hard handoffs
• Delayed handoffs and resource wastage during soft
  handoffs
• Reservation needs to be quick
• Radio frame may contain both data and control
• Loss and delay of control impact transmission,
  and reduce air interface capacity

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Proposed Work

• Resource management for air interface
• Scalable backhaul management
• Many interactions
• Resource allocation across multiple network
  layers
• Effect of air interface management and user
  mobility on RNA
• Effect of resource management in RAN on the air
  interface
• Multicasting support group communications
• Simulator design

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Resource Management for Air Interface

• Goal
• Serve both circuit-based delay sensitive
  applications and packet-based high speed data
  application
• Support both user-to-user unicast and one-to-many
  multicast for group communications
• Approaches Cross-layer
• Physical layer power control, rate control
• Link layer scheduling
• Network layer admission control

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Rate Control

• Basic rate control methods
• Fixed channel continuous transmission
• Vary processing gain
• Assigning multiple codes
• Time-slotted scheduling
• Allocate different number of time slots
• Allocate different number of codes
• Supporting connectivity and availability
• Reduce video resolution, reduce rate of elastic
  data
• Different tradeoffs
• Combating the reduction of Eb/Io throttling the
  source-coding rate or increasing the transmission
  power
• Allowing for increasing bit error for less
  critical data
• Apply more efficient error-resilient coding
  algorithms

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Power Control

• Optimal power allocations different types of
  traffic, different transmission formats
• Power sharing among real-time and non real-time
  traffic
• Fixed rate transmission iterative power control
  to find the minimum power to guarantee the
  received quality
• Increased power for real-time traffic (increased
  load, or bad channel)
• Reduce power for elastic data traffic
• Allocate more time slots to delay sensitive
  packet scheduled data

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Packet Scheduling

• Support different QoS
• Literature work only considers maximize total
  throughput, cannot meet public safety requirement
• Study tradeoffs between time-slotted scheduling
  and fixed-channel continuous transmissions.
  Feature of scheduling
• Pros More efficient resource usage and overall
  higher throughput, throughput gains from
  multi-user diversity
• Cons complex in guaranteeing quality
• Adaptive scheduling
• Increase data rate when system load is low

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Admission Control

• Adaptive admission control for integrated traffic
• Consider both circuit and packet transmissions
• Cannot guarantee quality by purely scheduling
• Different power for different users
• Varying power for the same user due to varying
  channel conditions and traffic rate
• Prioritize handoffs
• Consider both soft handoff and hard handoff
• Study connection level performance

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Backhaul Resource Management

• Effective and scalable traffic engineering
• Efficient handoffs

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Scalable Traffic Engineering

• Aggregate resource reservation and traffic
  multiplexing
• Reservation at cell level instead of at mobile
  level
• Minimize traffic dynamics
• Reduce management overhead
• Sink-tree based aggregation at upper link
• Multicasting at downlink
• Ensure fairness different cells, different
  agencies, different users

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Efficient Handoff Management

• Handoff prediction and guard channel reservation
• Dual time scale guard capacity control
• More efficient than direct reservation
• Prediction aggregation, fairness
• Increase scalability
• Blocked-based reservation
• Packet rerouting and sequencing
• Queuing at RNC or at base stations?
• Load control and resource management at downlink
• More effective diversity control to reduce error
  rate
• Multicasting to speed up rerouting

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Multicasting Support

• Public safety agencies require talk or share
  information within a group of users
• Exploit the broadcast feature of downlink
  channels
• Multicasting for circuit-based transmission
• Multicasting for time-slotted packet-based
  transmission

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Simulator Design

• Build channel model
• Simulate functions at air interface
• Simulator functions in the backhaul
• Simulated all the proposed functions, performance
  evaluations

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Work Completed
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Work Completed So far

• Data Traffic Analysis
• Preliminary simulator design

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Traffic Analysis in CDMA Network

• Internet data traffic exhibits long range
  dependency compared to voice traffic
• Typical data users heavy tailed ON/OFF users,
  average file size 20KB (or 2.5seconds burst time
  with 64Kbps) Long Range Dependent (LRD)
• Typical voice users exponential ON/OFF users,
  average burst time 70ms.
• CDMA network performance needs to be evaluated
  and protocols need to be enhanced to accommodate
  data traffic.

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LRD Impact in CDMA Networks

• LRD Impact on
• Multi-Access Interference (MAI)
• Signal to Interference and Noise Ratio (SINR)
• Outage Probability
• Can be used for traffic prediction
• Call Admission Control (CAC)
• Rate Control

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Multi-access Interference

• MAI
• Xj is users activity indicator when user j is
  transmitting (ON), Xj1 when user is silent
  (OFF), Xj0.
• Pj is power per sampling time.
• with perfect power control,
• Ki(u) is the equivalent number of active users
  transmitting with rate Ri

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Statistics of MAI

• Distribution of MAI
• Instantaneous MAI I(u) is the sum of multiple
  independent random variables and approximates
  Gaussian distribution with variance
• Time-scaled MAI IT(t) is defined as
• is the number of samples in T which
  remains as Gaussian
• Long range dependency of MAI
• Voice users ON/OFF periods are exponentially
  distributed, then I(u) is SRD.
• Data users ON/OFF periods are heavy tailed, then
  I(t) is LRD.
• MAI has a Weibull bounded tail distribution

ST
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Instantaneous SINR

• Instantaneous SINR
• Distribution
• SINR has the distribution with impact combining
  N0 and Ki
• Long range dependency
• Voice users
• N0 and Ki are both SRD, N0 Ki -gt SRD and SINR -gt
  SRD.
• Data users
• N0 is SRD and Ki is LRD, N0 Ki -gt LRD and SINR
  -gt LRD

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Time-scaled SINR

• Time-scaled SINR average over a time window
• Noise N0T has a Gaussian distribution with
  variance
• KiT also follows a Gaussian distribution
• Voice users variance decreases fast with T
• Data users variance decreases slow with T as
  Hgt0.5
• SINR has a Gaussian likedistribution which is
  the reverse of WN0T/Pi KiT (Gaussian
  distribution)

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Outage Probability

• Outage probability
• The probability that the average SINR or time
  scaled SINR in a packet transmitting time is
  smaller than a threshold ? degraded quality
• Also decay slow.

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Prediction in CDMA Networks

• Active users K prediction
• Predict K in the next window Tm based on
  historical values
• Fixed Period (FP) vs. Variable Period (VP)
  prediction
• Prediction is useful for
• Rate control in a relatively small T
• Call admission control in a relatively large T

FP vs VP
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Fixed Period Prediction vs. Variable Period
Prediction

• Fixed Period Prediction (existing, simple)
• Predict the next value based on the average value
  in pervious m windows.
• Only count a finite number of historical values
• Historical values are added to prediction with
  the same weights.
• Variable Period Prediction (more accurate)
• Predict the next value based on all previously
  measured values with proper weights
• All historical values are added to the prediction
• Multi time-scale prediction
• Historical values are properly weighted in the
  prediction
• Recursive algorithm, consumes less memory

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Rate Control

• Adjust users sending rate based on active user K
  prediction in a relatively smaller window T
  (2-10sec.)
• Suppose the system can support at most Km
  (equivalent) active users (transmitting at
  maximum rate Rm), adjust users sending rate
  according to prediction
• If , increase each
  users rate with
• If , decrease each
  users rate with

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Call Admission Control

• Admit new users based on prediction of network
  performance in a relatively large T (e.g., 5min).
• CAC for voice users
• Based on average performance
• The users that the network can admit is at most
• is the activity indicator
• CAC for data users
• Based on number of active users
  predicted in the next period
• If , then admit, otherwise
  reject.

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User Throughput
Throughput
Rate Control
CAC
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Conclusion for Traffic Analysis

• Both MAI and SINR are LRD in a CDMA network with
  heavy tailed ON/OFF data users
• Strong auto-correlation in MAI and SINR could be
  used for prediction in rate control and CAC
• Variable period prediction scheme is proposed and
  proved to be better than the existing fixed
  period prediction in terms of
• More accurate
• Consumes less memory
• Achieves better performance in rate control and
  CAC

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Basic Simulator Design

• Language ANSI C
• The network topology
• Approximated as a square mesh.
• Event Generator (Most important is handoff event)
• Call arrival and departure are generated used
  Poisson distribution
• Handoff events are triggered on the basis of
  power measurements.
• Event queue and scheduling tree-based
• Need more efficient event scheduler

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Simulator (contd)

• Mobility model
• Random Way Point
• Power Measurement
• Calculated based on mobile location
• Channel Model
• Fading, shadowing, path loss, interference
• Network Model
• Mobile object, cell object
• UMCast major network functions with references
• ALL mobile objects
• ALL Cell objects
• Stat class
• Challenges
• How to run event generator and algorithm in
  parallel
• Trade off scalability and event granularity

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Basic Functions in Simulator

• Call initiation
• Call arrival
• Call departure
• Power measurement
• Handoff prediction
• Guard capacity management
• Admission control
• Performance statistics

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On-going Work

• Multicasting support for downlink circuit based
  transmissions (support of multimedia such as
  voice and video for group communications)
• How to address heterogeneous requirements of
  users
• How to transmit to different terminals?
• How to guarantee quality for users with different
  channel conditions?
• How to guarantee multicast traffic quality?
• How to guarantee un-interrupted communications
  for each talk group?
• How to tradeoff multicast and unicast
  transmissions?
• Admission control for integrated circuit-based
  continuous media transmission and
  slotted-packet-based data
• How to formulate resource consumption model?
• How to interact with rate control and power
  control?

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Future Work

• The remaining of the proposal