OFDMA resource allocation in 4G wireless networks

Information Security, 17-26 Feb, 2005

1ICICS 2007, SingaporeDecember 10-13, 2007 13th International OFDM-Workshop 2008

Arijit Ukil, Jaydip Sen, Debasish BeraInnovation Lab, Convergence and Wireless Technology,

Kolkata, India



Agenda

• MotivationMotivation• Wireless Channel DynamicsWireless Channel Dynamics• Multi User diversityMulti User diversity• Why another degree of freedom?Why another degree of freedom?• QoS-aware Resource Allocation ProblemQoS-aware Resource Allocation Problem• Long Term Proportional Fair Resource AllocationLong Term Proportional Fair Resource Allocation• Application Application • Simulation ResultsSimulation Results• ConclusionConclusion



We Want More

Apart from Voice Traffic, applications require high data rate Apart from Voice Traffic, applications require high data rate and variable QoSand variable QoS

> > e-mail> multimedia messaging> Internet browsing> video conferencing> audio and video streaming> e-commerce> mobile TV



Targets of LTE

• Peak data rate• 100 Mbps DL/ 50 Mbps UL

• Mobility• Optimized for 0 ~ 15 km/h.• 15 ~ 120 km/h supported with high performance• Supported up to 350 km/h or even up to 500 km/h.

• Coverage• Performance should be met for 5 km cells with slight

degradation for 30 km cells. • Spectrum flexibility

• 1.25 ~ 20 MHz• 2X2 MIMO



IEEE 802.16 QoS



Challenges

Limited Resources : Limited Resources : Capacity-limited mediumCapacity-limited mediumTraffic patterns, user locations, constantly changing Traffic patterns, user locations, constantly changing network conditionsnetwork conditionsHeterogeneous trafficHeterogeneous trafficHard QoS constraintsHard QoS constraints Maximize number of usersMaximize number of usersMaximize network coverage Maximize network coverage Minimize outage probabilityMinimize outage probabilityGuaranteed user satisfactionGuaranteed user satisfaction



Channel Dynamics

Wireless Channel is time-varying and frequency-selectiveWireless Channel is time-varying and frequency-selectiveMultipath fading provides high peaks to exploitMultipath fading provides high peaks to exploitChannel capacity is achieved by such an opportunistic strategy Channel capacity is achieved by such an opportunistic strategy Channel varies faster and has more dynamic range in mobile Channel varies faster and has more dynamic range in mobile environmentsenvironmentsMore appropriate for data with More appropriate for data with soft latencysoft latency requirements requirements



Multi User Diversity

In a large system with users fading independently, there is likely to be a In a large system with users fading independently, there is likely to be a user with a good channel conditionuser with a good channel conditionMulti user diversity takes advantage of rather than compensate for the Multi user diversity takes advantage of rather than compensate for the channel fadingchannel fadingFast frequency selective fading now becomes beneficialFast frequency selective fading now becomes beneficialInstead of pumping more energy to compensate the multipath loss, Instead of pumping more energy to compensate the multipath loss, exploit the peaks in a channel-aware wayexploit the peaks in a channel-aware way



Why another degree of freedom?

By principal, aBy principal, a well designed communication system should take the available well designed communication system should take the available degrees of freedom of the channel as much as possibledegrees of freedom of the channel as much as possible

Multiuser diversity provides a system-wide benefitMultiuser diversity provides a system-wide benefit

Challenge is to share the benefit among the users in a Challenge is to share the benefit among the users in a fair and optimumfair and optimum way way

Frequency diversity gain is achieved by allocatingFrequency diversity gain is achieved by allocating OFDMA sub-carrier to the OFDMA sub-carrier to the user with relatively better channel, ideally the channel with the maximum gainuser with relatively better channel, ideally the channel with the maximum gain

Time diversity is traditionally obtained byTime diversity is traditionally obtained by interleaving and coding over symbols interleaving and coding over symbols across different coherent time periodsacross different coherent time periods

Time diversity is achieved by averaging the fading of the channel over time Time diversity is achieved by averaging the fading of the channel over time

Time Diversity technique is restricted to delay-tolerant applications, such as Time Diversity technique is restricted to delay-tolerant applications, such as video-on-demand or multimedia and data transfervideo-on-demand or multimedia and data transfer



How time-diversity gain can be achieved

Time Diversity technique fundamentally consists of retransmitting the corrupted Time Diversity technique fundamentally consists of retransmitting the corrupted information at times when the channel is expected to be more favourable, that is at information at times when the channel is expected to be more favourable, that is at time spacing exceeding the channel coherence time of the channeltime spacing exceeding the channel coherence time of the channel

In the context of OFDMA subcarrier allocation, time diversity gain is achieved In the context of OFDMA subcarrier allocation, time diversity gain is achieved by computing the resource allocation metric over time duration more than the by computing the resource allocation metric over time duration more than the coherence time of the channel, which should be typically few numbers of coherence time of the channel, which should be typically few numbers of frames frames



QoS aware OFDMA Sub-carrier allocation

The purpose of Resource Allocation is to intelligently allocate the The purpose of Resource Allocation is to intelligently allocate the limited resources (sub-carriers) among users to meet users’ service limited resources (sub-carriers) among users to meet users’ service requirements (QoS) and to enhance system capacityrequirements (QoS) and to enhance system capacity

• It’s a system optimization problemIt’s a system optimization problem• Available ResourcesAvailable Resources

– Transmit powerTransmit power– Frequency bandwidthFrequency bandwidth – Transmission timeTransmission time– Code resourceCode resource– Spatial antennasSpatial antennas

• Resource allocation impactsResource allocation impacts– Less Power consumptionLess Power consumption– More User throughputMore User throughput– Enhanced System CapacityEnhanced System Capacity– User QoS GuaranteeUser QoS Guarantee



Problem

Optimum instantaneous sub-carrier allocation is not possible in real Optimum instantaneous sub-carrier allocation is not possible in real time because of high computational costtime because of high computational cost

QoS parameters for different applications are differentQoS parameters for different applications are different Same resource allocation algorithm does not fetch optimum Same resource allocation algorithm does not fetch optimum

performance gain for all the QoS classesperformance gain for all the QoS classes Optimum capacity from hard QoS (UGS,RTPS) based applications can Optimum capacity from hard QoS (UGS,RTPS) based applications can

only take advantage of frequency diversityonly take advantage of frequency diversity Time as well as frequency diversity gains can be jointly exploited in Time as well as frequency diversity gains can be jointly exploited in

delay tolerant applications like file transfer, multimedia messaging, delay tolerant applications like file transfer, multimedia messaging, web browsing, in NRTPS, BE class of QoSweb browsing, in NRTPS, BE class of QoS

Find an optimum resource allocation scheme/algorithm for non Find an optimum resource allocation scheme/algorithm for non premium (NRTPS, BE) classespremium (NRTPS, BE) classes



Long Term Proportional Fair Resource Allocation



System Model

Single cell multi-user OFDMA system with FRF=1

Conditions:

Sub-carrier bandwidth < coherence bandwidth of the channel

Sub-carrier allocation period < coherence time

Resource allocation metric computation time > coherence time

Assumptions:

Perfect channel state informationSub-carrier

allocation

IFFT

fN

P/S

CSI

Sub-carrier to user

mappingFFT

S/P

Remove Cyclic prefix

Sub-carrier Allocation Module

User1

…

QoS1

QoSK

Transmitter

Wireless Channel

Add Cyclic prefix

User1

UserK

UserK



Proportional Fair Optimization

Objective is to maximize the sum rate over time with a feedback on Objective is to maximize the sum rate over time with a feedback on users’ already achieved data rate, i.e., users’ past performance users’ already achieved data rate, i.e., users’ past performance is also taken into account along with instantaneous channel is also taken into account along with instantaneous channel condition to allocate sub-carrier condition to allocate sub-carrier

PF scheduler or resource allocation heuristically tries to balance the PF scheduler or resource allocation heuristically tries to balance the fairness among the users in terms of outcome or throughput, fairness among the users in terms of outcome or throughput, while implicitly maximizing the system throughput in a greedy while implicitly maximizing the system throughput in a greedy manner. manner.

Let be the achievable rate for kth user at tth instantLet be the achievable rate for kth user at tth instant..

In PF optimization subcarrier n is allocated to k* user when the In PF optimization subcarrier n is allocated to k* user when the following condition is satisfied:following condition is satisfied:



Traditional PF is instantaneous decision maker

• Traditional Proportional Fair Optimization is based on instantaneous Traditional Proportional Fair Optimization is based on instantaneous computation of proportional fair metriccomputation of proportional fair metric

• The resultant optimization does not take advantage of the time The resultant optimization does not take advantage of the time diversity gaindiversity gain

• Traditional PF suitable for real time applications with hard delay Traditional PF suitable for real time applications with hard delay requirementrequirement



Long Term Proportional Fair • Objective is to

OFDMA resource allocation in 4G wireless networks

Technology

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