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Cross-Layer Design for Wireless Communication

Networks

Ness B. ShroffCenter for Wireless Systems and Applications

(CWSA) School of Electrical and Computer EngineeringPurdue University, West Lafayette, IN 47907

E-mail: shroff@ecn.purdue.eduURL: http://www.ece.purdue.edu/~shroff

Wireless vs. Wireline Networks Wireline systems

Reliable channel and very high bandwidth Core router: Gbps - Tbps Requirement: simplicity and scalability

Wireless systems Limited natural resource (radio

frequency) 3G: up to 2Mbps, WLANs: ~100Mbps Requirement: spectrum efficiency

Cross-Layer Design To satisfy the increasing demand for wireless

data capacity, a cross-layer perspective needs to be taken to improve wireless spectrum efficiency

Network

MAC

Physical

Transport

Cross-Layer Design To satisfy the increasing demand for wireless

data capacity, a cross-layer perspective needs to be taken to improve wireless spectrum efficiency

Network

MAC

Physical

Transport

Focus of this talk: Opportunistic Scheduling in cellular systems

Characteristics of Wireless Networks

Wireless environment is heterogeneous and Interference-prone

Radio tower

Laptop

Radio tower

Radio tower

Radio tower

Characteristics of Wireless Networks

Time-Varying Channel Conditions Reason: Mobility and the Propagation

environment Path loss (e.g., signal strength attenuates as D) Shadowing or slow-fading (e.g. log-normal shadowing

with spatial correlation) Fast-fading or multipath fading (e.g., Rayleigh or

Ricean) Both received signal and interference are time

varying SINR (Signal to Interference plus Noise Ratio)

is a measure of channel quality:

Opportunistic Scheduling

Under time-varying channel conditions, which user should be chosen to transmit?

Naive Approach: Schedule user with the best channel.

Our objective will be to schedule users in an opportunistic way(exploits channel variability) and at the same time satisfy QoSrequirements.

Performance Measure Different applications differ in how they can utilize the

channel The performance measure is based on a unifying metric,

using the notion of the utility value (or reward) to that user

Examples of Utility: Throughput; value of throughput; value of throughput – cost of power, etc.

Opportunistic Scheduling

Uik = utility value (function of SIR) of user i if it

is scheduled at time k Objective: Maximize the sum of all users utility

values by opportunistic scheduling while satisfying the QoS requirements of users

Scheduling decision depends on:

Channel conditions QoS requirements.

Radio tower

Laptop

U k2

U k1

U kN

N: number of usersr i Fraction of time assigned to user i

QoS Requirements

Under our framework, we can consider a variety of fairness/performance requirements

Temporal fairness requirement Utilitarian fairness requirement Minimum-performance requirement Combinations of the above

requirements

A Case Study: Temporal Fairness N: the number of users in the cell ri = fraction of time assigned to user i with

Given Uk=(U1k,,UN

k), decide who should take time-slot k?

Define a policy Q as a mapping from the utility vector space to the index set {1,…,N}

Given Uk, if Q(Uk) = i, then user i is assigned to the time slot k

Objective: Maximize average utility subject to the fairness constraints ri

Scheduling Problem Formulation The optimal scheduling problem with

temporal fairness

where : the set of all scheduling policies

An Optimal Scheduling Policy

A policy Q(U) = argmaxi Ui will maximize the system utility, but may not meet each user’s fairness requirement.

The vi’s are “off-sets” used to achieve the fairness requirementThe coupling needed between layers to balance

fairness and efficiency!

The optimal policy is given in a very simple form!

“No Loss” Property

The average utility of every user in our scheduling scheme will be at least that of any non-opportunistic scheduling scheme.

The opportunistic scheduling scheme does not sacrifice some users for overall optimal performance.

Parameter Estimation We can estimate vi

* based on measurements of the channel using stochastic approximation.

vik → vi

* w.p.1 under appropriate conditions (e.g., ak=1/k).

Scheduling ProcedureBasic Idea: Set initial value of vi

0. The initial value can be set to 0 or some estimate based on history information

At each time slot, the system performs the following: Estimates Ui

k

Uplink: the base station estimates each user’s channel condition and calculates the values of Ui

k

Downlink: user i measures its channel condition, calculates Ui

k, and informs the base station

Scheduling Procedure (Cont’d) The base station decides which user should take

the time slot based on the scheduling policy:

The base station updates the parameter vk by

For downlink, the base station transmits to the chosen user

For uplink, the base station broadcasts the ID of the selected user and the selected user transmits in the time slot

Scheduling Procedure (cont’d)

EstimateUtility

Values

ApplyScheduling

Polity

UpdateParameters

MeasureChannel

Conditions

iU

iV

System Performance

Our scheduling procedure is efficient, fair androbust against estimation errors

Summary on Opportunistic Scheduling Typical performance improvements with strict

fairness are around 50~100% Specific values not critical The users’ performance values are uniformly

better Opportunistic gains increase with

Level of user elasticity channel variability (over time) number of users negative correlations

Discussion (Cont’d) Further improvement by relaxing the fairness constraint

Similar type of myopic index policy

is optimal in many cases

Simple to implement Easily extended to include short term fairness Appears to be robust to estimation errors

Opportunistic scheduling can be combined with other resource allocation strategies (power control, rate control, etc.)

Discussion (Cont’d)

Traditional setting: performance of system depends on average channel conditions.

Cross-Layer (Opportunistic) setting: performance of system depends on peak channel conditions.

Significantly improve efficiency (especially for delay tolerant users)

Discussion (Cont’d)

No Free Lunch Signaling costs

Each user needs to maintain a signaling channel Signaling costs increase linearly with the number of users

Channel Estimation Errors Feedback Delay Time-Scale of fluctuation Scheduling gain vs. short-term fairness

Opportunistic Scheduling is important for future wireless systems (Qualcomm, Flarion, etc.)

Cross Layer Design

Opportunistic Scheduling: MAC & PHY

Many other Cross-Layer Design Issues MAC Interaction with Transport Protocols

TCP Congestion Control and MAC layer Security/energy need to be considered

across multiple layers Multi-hop wireless Networks

Joint Scheduling (link) and Congestion Control (end-to-end) results in significant gains

Energy Efficient Routing, synchronization…

Potential: cross-layer gains are multiplicative

Key to Success: Cross-layer solutions should be loosely coupled across the layers such that high performance gains are achieved without a complete loss of modularity.

Conclusion