A Simple and Effective Cross Layer Networking System for Mobile Ad Hoc Networks

Wing Ho Yuen, Heung-no Lee and Timothy Andersen

Outline

Introduction to cross layer designProposed channel modelRate adaptation scheme Routing metrics utilizing MAC infoSimulation setup and results

Why Cross-layer?

Nature of wireless ad hoc networks Limited capacity, constrained energy, mobility …

Application requirements Real time, mission critical …

Current layered design paradigm is inflexible and sub-optimal for wireless networksCross-layer design requires info exchanged across layers, thus allows protocols to adapt in a global manner, eventually achieves optimal network performance

Cross Layer Example

Channel Model

Three signal strength attenuation factors are considered, namely, pass loss, shadowing and multipath fadingFor channel-adaptive protocols, A good time-varying channel model is needed for simulationA correlated shadowing channel model is proposed

Correlated Shadowing Model

Correlated Shadowing Model

Shadowing attenuation Aj of a node j does not change until node j moves out of a disc of radius d from previously reference position

Suppose node j moves out of the disc, new attenuation is Suppose both node i and j move out of the disc

Where W is a zero mean Gaussian random variable

WnAnA ii21)()1(

WnAnA ijij21)()1(

)/exp( 0Di )/2exp( 0Dij

Rate Adaptation Scheme

Modification on IEEE 802.11 protocolRTS,CTS and ACK packets sent at nominal rateSNR is estimated at when node receives RTSTransmission rate is mapped from the estimated SNR, and appended to the CTS The sender transmits data at the adapted rate

Rate Adaptation Scheme

An M-QAM scheme is used in which the constellation size changed with SNRConstellation size is decided by where is a constant determined based on the power constraints, is SNR.Threshold rule is used, if , assign to

*)( KM *

K

1)( jj MMM

jM

NAV modification

Routing Metrics

Bandwidth awareness , represents the rate of link between node i and j Interferences awareness , Where is the interval from the when the RTS packet is sent to when the data packet is receivedCongestion awareness , where is the queuing delay in the buffer of transmit nodeInterference awareness is implemented

ijR1 ijR

ijD ijD

ijQ iQ

Implementation in DSR

DSR route maintenance unmodified since only low mobility scenarios are consideredReceived SNR information are appended in RREQ, since RTS and CTS are not used when broadcasting RREQ, no rate adaptation is used in RREQ packetsRREP packets are unicast packets to the source node using rate adaptation based on the SNR information along the routeSource node compute the MAC delay of every RREP packets and choose the route with min delay

Simulation Setup

Ns-2 with wireless extensions by the Monarch Project, CMU Channel Model: Correlated shadowing, implemented in C++MAC layer: 802.11b at 914MHz, 2MHz bandwidthNetwork layer: modified (dynamic source routing) DSR algorithmTransport layer: UDP agentApplication layer: CBR application

Simulation Environment

50 nodesTransmission range 250mScenario size 1500X300mChannel model:Path loss model: 2 ray ground reflection modelshadowing variance s=12 (severe shadowing)Correlated fading (slow fading at low mobility)Mobility model:Random waypoint model2 values of node mobility s=0m/s and 1m/scorresponding to stationary and pedestrian scenarios

Simulation Environment

Each scenario has 20 flows (source destination pairs)Packet rate varies from 10 to 60 packet/sEach traffic flow starts at staggered time between 0s and 100sPerformance metrics: throughput, delay, packet delivery ratioThree schemes are investigated:

Plain DSR RA: rate adaptation IARA: interference aware rate adaptation

Results: Stationary Scenario

Results: Pedestrian Scenario

Conclusions

Spectrally efficient rate adaptation scheme leads to drastic improvement in throughputSimple routing metric incorporated to the DSR protocol, leading to modest decrease in packet delay