System Level Modeling and Optimization of the LTE Downlink
System Level Modeling and Optimization of the LTE Downlink
System Level Modeling and Optimization of the LTE Downlink
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3. Physical Layer <strong>Modeling</strong> <strong>and</strong> <strong>LTE</strong> <strong>System</strong> <strong>Level</strong> Simulationcan be ei<strong>the</strong>r a 2D or a 3D pattern. In <strong>the</strong> last case, it combines a horizontal <strong>and</strong>vertical component with an optional mechanical/electrical tilt [79].ˆ L pathloss : A distance-dependent pathloss between <strong>the</strong> transmitter <strong>and</strong> <strong>the</strong> receiver.ˆ L shadow : Shadow fading, which models slow-changing deviations from <strong>the</strong> averagepathloss values that model irregularities such as geographical features. Modeledas a zero-mean space-correlated lognormal distribution.ˆ |h r,t | 2 : Assumed to be a χ 2 distribution with a number <strong>of</strong> degrees <strong>of</strong> freedom N<strong>of</strong> two, as <strong>the</strong> underlying distribution <strong>of</strong> h is assumed to be circular symmetriccomplex normal with an average power <strong>of</strong> one.As <strong>the</strong> macro-scale parameters are scalars applied to all <strong>of</strong> <strong>the</strong> entries <strong>of</strong> <strong>the</strong> MIMOchannel matrix, it can be trivially decomposed into a normalized 3 channel matrix Hmultiplied by <strong>the</strong> factors L pathloss , L shadow , <strong>and</strong> G antenna . Applying <strong>the</strong> link budget<strong>of</strong> Equation (3.10) to Equation (3.9) we can rewrite Equation (3.9), expressing <strong>the</strong>subcarrier post-equalization SINR for layer i asγ i =ζ i P ′ L,0ξ i P ′ L,0 + ψ iσ 2 n +N int ∑m=1θ i,m P ′ L,m, (3.11)where PL,m ′ = P L,m · G antenna,m · L pathloss,m · L shadown,m , <strong>and</strong> <strong>the</strong> index m denotes <strong>the</strong>transmitting eNodeB (m = 0 for <strong>the</strong> target transmitter <strong>and</strong> m = 1, . . . , N int for <strong>the</strong>interferers).Decomposing <strong>the</strong> combined fading experienced over <strong>the</strong> link into a slowly-changingposition-dependent macro-scale component <strong>and</strong> a faster-changing small-scale [80]enables to model <strong>the</strong> fading as two separate <strong>of</strong>fline-computable components: oneposition-dependent <strong>and</strong> one time-dependent.3.1.1.2. On <strong>the</strong> <strong>Modeling</strong> <strong>of</strong> OLSM <strong>and</strong> <strong>the</strong> Block Fading AssumptionOver <strong>the</strong> course <strong>of</strong> this chapter, it has been stressed that block fading is assumed,i.e., unchanging channel conditions for <strong>the</strong> duration <strong>of</strong> a TTI, <strong>and</strong> this assumptionis applied to <strong>the</strong> calculation <strong>of</strong> <strong>the</strong> post-equalization SINR in Section 3.1.1.1.However, it is clearly mentioned in Section 2.2.1.2 that <strong>the</strong> OLSM transmit mode isbased on cyclically applying a set <strong>of</strong> precoders, as well as a shift <strong>of</strong> <strong>the</strong> signal, to eachmodulated symbol during one TTI. Thus, even if a constant channel is considered,<strong>the</strong> effective channel, i.e., <strong>the</strong> combination <strong>of</strong> <strong>the</strong> channel <strong>and</strong> <strong>the</strong> precoder is notconstant during a TTI due to <strong>the</strong> applied CDD <strong>and</strong> cyclical precoding.3 Through <strong>the</strong> course <strong>of</strong> this <strong>the</strong>sis, a normalized channel matrix refers to one in which all <strong>of</strong> itsentries have a mean power <strong>of</strong> one.31