FUTURE MOBILE COMMUNICATION: LTE OPTIMIZATION · PDF fileFUTURE MOBILE COMMUNICATION: LTE...
16
FUTURE MOBILE COMMUNICATION: FUTURE MOBILE COMMUNICATION: LTE OPTIMIZATION AND MOBILE NETWORK VIRTUALIZATION VIRTUALIZATION Yasir Zaki, Andreas Timm‐Giel, Carmelita Görg ComNets University of Bremen, Technical University of Hamburg Euroview July 23 rd 2012 ComNets [email protected] Outline Motivation of Wireless and LTE Virtualization LTE Virtualization Framework LTE Virtualization Framework Simulation Model Contract Based Framework Simulation Configurations and Results Conclusion and Outlook ComNets [email protected] 2
-
Upload
nguyendieu -
Category
Documents
-
view
223 -
download
1
Transcript of FUTURE MOBILE COMMUNICATION: LTE OPTIMIZATION · PDF fileFUTURE MOBILE COMMUNICATION: LTE...
FUTURE MOBILE COMMUNICATION:FUTURE MOBILE COMMUNICATION: LTE OPTIMIZATION AND MOBILE NETWORK VIRTUALIZATIONVIRTUALIZATION
Yasir Zaki, Andreas Timm‐Giel, Carmelita Görg, , g
ComNets
University of Bremen, Technical University of Hamburg
Euroview July 23rd 2012
Outline
Motivation of Wireless and LTE Virtualization
LTE Virtualization Framework LTE Virtualization Framework
Simulation Model
Contract Based Framework
Simulation Configurations and Results
Conclusion and Outlook
Motivation of Wireless and LTE Virtualization
LTE Virtualization Framework LTE Virtualization Framework
Simulation Model
Contract Based Framework
Simulation Configurations and Results
Conclusion and Outlook
Wireless Virtualization
Wired virtualization is well‐known
A natural extension from wired to wireless virtualization
Virtualization of the wireless
air interface is a scheduling problem:air interface is a scheduling problem:
Tx/Rx power
Frequency, Time, Code
S ll ti Space allocation
Similar to the well known wireless transmission strategies: FDMA, TDMA, CDMA and SDMACDMA and SDMA
But virtualization is doing more
Motivation Behind Mobile Network Virtualization
Mobile networks are one of the fastest growing technologies has big influence on our daily activities
Often, the wireless resources of mobile networks are expensive and scarce
B i bl t h d ti i th i hi hl ti ti Being able to share and optimize the resources usage is highly motivating
Network virtualization is a good solution : reduces the number of base stations (reduce energy usage)
allows completely new value chains (mainly smaller players)
In addition, sharing the frequency resources among multiple operators is very appealing gives operators the flexibility to expand/shrink their networks on the fly
LTE Virtualization
Virtualizing the LTE network means to virtualize the infrastructure of the LTE system
This allows multiple network operators to create their own virtual network depending on their requirements and goals
The challenges are: How to virtualize the physical infrastructure?p y
What kind of changes are required to the existing LTE system?
We mainly foresee two different types of virtualization processes: We mainly foresee two different types of virtualization processes: Virtualizing LTE physical nodes (e.g. eNodeBs, routers, Ethernet links)
Virtualizing the air interface of the LTE system (focus of this presentation)
Motivation of Wireless and LTE Virtualization
LTE Virtualization Framework LTE Virtualization Framework
Simulation Model
Contract Based Framework
Simulation Configurations and Results
Conclusion and Outlook
LTE Air Interface Virtualization
In order to virtualize the LTE air interface, the eNodeB (LTE base station) has to be virtualized
Our solution is inspired by the XEN1 architecture, where mainly a “Hypervisor” is added on top of the physical resources.
The hypervisor is responsible for virtualizing the eNodeB and scheduling the air interface (OFDMA) resources among the Virtual Operators (VOs)
1 XEN is a node virtualization software
LTE Hypervisor
It is responsible for: virtualizing the eNodeB
scheduling the air interface resources among the
Physical Resources
PRBs
Physical eNB
scheduling the air interface resources among the Virtual Operators (VOs)
It collects all relevant information (from allHypervisor (2nd level Scheduler)
Virtual eNBs
Channel Conditions
It collects all relevant information (from all VOs) : users channel conditions
traffic load
Virtual eNBs
LTE MAC Scheduler
LTE MAC Scheduler
LTE MAC Scheduler
VO requirements
VO contracts
etc.
Based on that, the hypervisor tries to allocate the resources to the VO
Motivation of Wireless and LTE Virtualization
LTE Virtualization Framework LTE Virtualization Framework
Simulation Model
Contract Based Framework
Simulation Configurations and Results
Conclusion and Outlook
OPNET Simulation Model
Hypervisor
Physical eNB
yp
Virtual eNBs
Motivation of Wireless and LTE Virtualization
LTE Virtualization Framework LTE Virtualization Framework
Simulation Model
Contract Based Framework
Simulation Configurations and Results
Conclusion and Outlook
LTE Contract‐based Spectrum Management
We defined four different types of contracts that the infrastructure provider offers to the virtual operators and these are:a) Fixed guaranteesa) Fixed guarantees
b) Dynamic guarantees
c) Best effort (BE) with min guarantees
d) Best effort with no guaranteesd) Best effort with no guarantees
Continue …
In order for the hypervisor to be able to satisfy the operator requests and their predefined contracts, an estimate of the actual needed spectrum of each operator is required
The operators need to feedback this estimate value back to the hypervisor (in a predefined time interval)
The PRBs estimate of each operator can be calculated iteratively as follows:
)1(1)( nPRBsTTInEnE
Where: E(N) is the averaged required PRBs count (estimate of the required bandwidth) over N time
interval
PRBsTTI(N) is the instantaneous PRBs count at the Nth TTI calculated by summing the PRBs that were additionally needed to schedule the un‐served users within this TTI
N is the number of TTIs in the hypervisor interval
α is the smoothing factor indicating the weighting
α is the smoothing factor indicating the weighting
Motivation of Wireless and LTE Virtualization
LTE Virtualization Framework LTE Virtualization Framework
Simulation Model
Contract Based Framework
Simulation Configurations and Results
Conclusion and Outlook
Simulation Configurations
The simulation is configured with 4 virtual operators each is configured with one of the different contract types defined earlier:
Virtual Operator Contract details
VO1 (Video streaming) “fixed guaranteed contract” of 33 PRBs
VO2 (VOIP) “dynamic guaranteed contract”, with a max value of 33 PRBs
VO3 (VOIP + BE Video on demand) “best effort with min. guarantees” contract, with min. and max. value of 25 and 45 consecutively
Two scenarios are configured one without virtualization “legacy” and
VO4 (Small VOIP operator) “BE and no guarantees” contract
one with virtualization “virtualized”.
Simulation Configurations
Parameter Assumption
Number of VO 4
Number of virtual eNodeBs 4 eNodeBs (one per VO)Number of virtual eNodeBs 4 eNodeBs (one per VO)
Total number of PRBs 99 (corresponds to about ~ 20 MHz)
Number of active users VO1: 12 video usersVO2: 40 VOIP usersVO3: 16 VOIP + 16 video usersVO4: 3 VOIP users
Mobility model Random Way Point (RWP) with 5 km/h
Channel model ITU Ped-AChannel model ITU Ped A
DL VOIP traffic model Silence/Talk Spurt length = neg. exp. with 3 sec mean. Call duration = uniform (1, 3 min)Inter-repetition time = negative exponential with 90 sec mean
DL Video traffic model Video conferencing application with unlimited durationIn/Outgoing stream inter arrival time = Const (0 01 sec)In/Outgoing stream inter arrival time = Const (0.01 sec)In/Outgoing stream frame size = Const (80 Bytes)
Hypervisor resolution, estimation factor α
1 sec, with 0.5
Simulation time 1000 sec
Virtual Operator (VO) allocated number of PRBs
The figure shows the number of PRBs that each VO has been allocated over time
It can be noticed that for the first operator the PRBs allocation is fixedoperator the PRBs allocation is fixed to 33 PRBs since it is using the fixed guaranteed contract
For the other three operators we can notice that the allocated number of PRBs changes with timenumber of PRBs changes with time depending on the traffic load and the contract details of each operator
p
Virtual operator 1 (12 video users)Air interface throughput and app. end‐to‐end delay
What can be noticed is that the operator has the same performance with and withoutWhat can be noticed is that the operator has the same performance with and withoutvirtualization; this is because this operator has a contract with a guaranteed fixedallocation
Virtual operator 2 (40 VOIP users) Air interface throughput and app. end‐to‐end delay
What can be noticed is that the operator has the same performance with and withoutWhat can be noticed is that the operator has the same performance with and withoutvirtualization
Virtual operator 2Downlink used number of PRBs vs. time
The previous results showed that operator 2 has the same performance with and withoutvirtualization
But, in the “virtualized” case VO2 is not wasting the air interface resources since it only usesthe required number of PRBs to serve the users as can be seen above
This is a big advantage since the operator will be able to cut cost because he will only pay for
the resources used
Virtual operator 3 Application end‐to‐end delay
We can see that similar performance is achieved in both cases for the VOIP users (left side).As for the video users (right side), they are suffering from huge delay in the “legacy” scenarioAs for the video users (right side), they are suffering from huge delay in the legacy scenariodue to buffering; whereas in the “virtualized” scenario they are having good performance.
The reason why the VOIP users in the “legacy” scenario are not affected is the fact that theseusers are being served with higher priority and the resources are enough to serve those users,
users are being served with higher priority and the resources are enough to serve those users,but not enough to serve the video users.
Virtual operator 4 (3 VOIP users)Air interface throughput and app. end‐to‐end delay
One additional advantage that can be achieved in the “virtualized” scenario is the ability toserve small operators with relatively smaller number of users in a pure best effort manner withserve small operators with relatively smaller number of users in a pure best effort manner withwhatever resources are left rather than wasting these resources
Motivation of Wireless and LTE Virtualization
LTE Virtualization Framework LTE Virtualization Framework
Simulation Model
Contract Based Framework
Simulation Configurations and Results
Conclusion and Outlook
Conclusion and Outlook
The simulation results showed that a better performance can be achieved by using network virtualization in the LTE system.
Based on the contract configurations and the traffic load of each virtual operator the air interface resources are shared among the VOs.
The overall resource utilization is enhanced and the performance for both the network and the end‐user is better.
Both operator 2 and 3 benefited from virtualization mainly by being able to cut costs and providing better performance for their users.
The results also showed the possibility of opening the market to new players (small operators) that can serve a specific role and have small numbers of
users.
THANKS FOR LISTENINGTHANKS FOR LISTENINGANY QUESTIONS
BACKUP SLIDES
Long Term Evolution (LTE)
LTE is the latest evolution of 3GPP standard.
Its based on Orthogonal Frequency Division Its based on Orthogonal Frequency Division Multiple Access (OFDMA) in the downlink and Single Carrier FDMA (SC‐FDMA) in the uplinkuplink
Its a very good candidate to be considered for applying network virtualization
LTE’s new network architecture is based on LTE s new network architecture is based on a cost efficient two nodes architecture Enhanced NodeB (eNodeB)
Access Gateway (AGW)
Access Gateway (AGW)
BE Virtual Operators Allocation
The allocation of the left PRBs to the BE operators in step 4 will be done based on a Fair Factor (FF) which is defined as follows:
VOBEi
i
E
nEFF _#
fll i
j
jnE1
Where:
PRBsLeftFFallocPRBs ii _int_
# BE_VO is the number of best effort virtual operator
PRBs_alloci is the allocated PRBs for operator i
Left_PRBS is the number of PRBs left after allocating VO of contract type a, b and h f
the min guarantees of type c
Virtual Radio*
Defines a framework for configurable radio networks
I d h k i li i It extends the network virtualization concept into the wireless domain known as “radio virtualization”
Different virtual radio networks can Different virtual radio networks can operate on top of a common shared infrastructure and share the same radio resources
It presents how the radio resource sharing can be performed efficiently without i t f b t th diff t i t linterference between the different virtual radio networks
* J Sachs S Baucke “Virtual Radio-A Framework for Configurable
J. Sachs, S. Baucke, Virtual Radio A Framework for Configurable Radio Networks”; WICON’08, Hawaii, USA, Nov. 2008.
VANU MultiRAN*
V M ltiRAN™ Vi t l B Vanu‐MultiRAN™ Virtual Base Station is a commercial software
Taking advantage of Vanu software RAN technology, M ltiRAN d l d tMultiRAN was developed to support multiple virtual base stations (vBTS) running on a single BTS hardware platformsingle BTS hardware platform. The expense of antennas, BTS electronics, and backhaul can all be shared.all be shared.
* J. Chapin; “Overview of Vanu Software Radio”;
from http://www.vanu.com, June. 2009.
LTE Downlink Physical Resource Structure
Inter-carrier subspacing15 kHZ Sub-carrier
Frequency (Hz)12 Subcarriers12*15k=180kHz
