EEEN 60184Internet and CommunicationsNetworksLaboratory Assignment:Overview, Tasks 1, 2, 3 and 41.0 IntroductionThe laboratory work is concerned with simulating various aspects of wireless sensornetworks. The basic simulations use the Zuniga and Krishnamachari link model, but higherlayers of the protocol stack are also considered.There are 4 parts to the laboratory work: Task 1: Modelling a network link in a pre-specified environment. Task 2: Modelling the connectivity of a network and investigating factors that affecttopology. Task 3: Calculating routes between nodes and the base station Task 4: Discussing the implications of the results of Tasks 1-3 for Transport Layercommunication.1.1 OutcomeYou will be expected to write a short report that presents and discusses your results. Theformat of the report, along with the marking scheme will be specified in a subsequentdocument. However, there will be a limit of 5 pages on the body of the report. This excludesthe front page, contents list, references and appendices.The deadline for uploading the report to Blackboard will be 9.00 am on Monday 1st April2019.Further details will be given shortly.1.2 SoftwareYou will be provided with a number of MATLAB programs to use to obtain results. These willrequire minor modifications to complete some of the tasks, but the amount of programmingneeded is small. However, if you are confident programmer and have reasons for makingmore extensive changes, then you are free to do so.1.3 Laboratory SessionsThese will take place on Wednesday afternoons (20th and 27th March) from 14.00-15.00 inthe Barnes Wallis cluster and attendance is optional. The purpose of the sessions is toenable you to ask questions about the assignment and the software that is provided. Youare expected to complete the assignment work during periods when there are no lectures ortutorials.32.0 Task 1This part the assignment is concerned with utilising the analytical model of Zuniga andKrishnamachari [1] (introduced in lecture 17) to predict the extent of the connected,transitional and disconnected zones associated with transmissions by wireless sensornodes.2.1 BackgroundAs discussed in lecture 17, the well-known model of a fixed (circular) radius radio range witha sharp cut-off between positions where a packet can and cannot be received, has beenfound to be unrealistic. Experimental data indicates the existence of 3 distinct receptionregions surrounding a transmitter. The first, where packet reception rates (PRR) are high (>90%) is known as the connected region. In the next zone the link is unreliable and packetreception rates vary widely (between 90% and 10%); this is known as the transitionalregion). Finally, there exists a region where packet reception is essentially negligible (lessthan 10%) and this is known as the disconnected region.The model of [1] is derived using two models and is a combination of empirical andanalytical approaches. The models are a channel model, based on the log normal law, whichdefines the received signal power as a function of distance from the transmitter, and a radiomodel that predicts PRR as a function of signal-to-noise-ratio (SNR) for a specificcombination of line coding and modulation schemes. This latter model is manipulated untilit can be written in terms of parameters that are known or can be measured/estimated for aparticular radio transceiver.The log normal law (channel model) is:r dB t dB dBdB dB dBP d P PL ddPL d PL d Xd(1)where Pr is the received signal power at distance d from the transmitter, Pt is thetransmitted power, PL is path loss, d0 is a reference distance at which path loss PL(d0) ismeasured. In this assignment d0 is 1m. X is a zero-mean Gaussian random variable whosevariance is 2 which represents fading. is the path loss exponent. See equation (1) in [1].The key elements of the radio model are:is the SNR at distance d from the transmitter, Pn is an estimate of noise, PRR is packetreception ratio (as a fraction), BER is the bit error rate at a SNR of ? (in dBs) and f is the sizeof a packet in bytes. See equation (2) in reference [1].Now PRR is usually written as a function of Eb/N0 (energy received per bit/noise powerdensity). These are difficult parameters to estimate, and so the following familiarrelationship is used:E R E B b b SNR(3)to write BER and PRR as functions of bandwidth B and data rate R, which are known or canbe estimated for a particular radio. The functions f and g depend on line coding andmodulation schemes. See Table V in [1].2.2 What to doA key element of the method is the plot shown in figure 1. This shows the curves from thetwo models superimposed upon one another and which together enable the extent of thethree zones discussed above to be defined. The curves labelled ?, and are derived from the log normal model and show the mean, and upper andlower bounds of received signal strength at a receiver placed at a distance d from thetransmitter. The lines marked ?L+Pn and ?U+Pn represent received signal strength powercorresponding to PRRs of 0.1 and 0.9 respectively. The region defined by the intersections ofthe curves from the two models defines the size of the transition region, as explained in [1].The plot in figure 1 was obtained using a specific set of parameters in both the channels andradio models namely:%channel model constantsPATH_LOSS_EXPONENT = 4.0;D0 = 1.0;PATH_LOSS_D0 = 55.0; %in dBmSHADOWING_VARIANCE = 4.0;TX_POWER = 0; %in dBm
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