System Level Modeling and Optimization of the LTE Downlink

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D. Evaluation of Multi-User GainSimilar to the analysis in [63], this simulation extends the MIMO scenario describedin Table 5.1 (but without the addition of FFR). For these results, we compare thethroughput results with a log log fit. The reasoning for this fit is based on adaptingthe assumption that, for N TX transmit antennas at the eNodeB and N RX receiveantennas at each of the K UEs, cell capacity grown with N TX log log (KN RX ) [77,145, 146] to this cellular scenario in which each UE does not experience the sameSNR 1 .A metric a log log (K b) is adopted to quantify the maximum achievable MU gainin this scenario for different antenna configurations. Denoting as log log (K b 1×1 )the MU gain for the 1×1 case and accordingly normalizing, 2×2 and 4×4 CLSMconfigurations, shown in Figures D.2 and D.3 are compared to the SISO case. Weterm a as the multiplexing gain, while b is denoted as the multi-user gain flattening,as it depicts the reduction in the capacity of the scheduler to correctly extract multiusergain.Avg. cell throughput [Mbit/s]1401301201101009080706050400Throughput 2x25 10 15 20 25 30number of UEs/cellFairness of UE throughput10.90.80.70.60.50.40.30.20.100Fairness 2x25 10 15 20 25 30number of UEs/cellRound Robin Proportional fair Best CQI fitFigure D.2: 2×2 CLSM transmit mode multi-user gain results. Left: throughput results.Right: fairness results. Vertical lines mark the 95% confidence intervals.The values obtained from a log log MSE-minimizing fit are shown in Table D.1 forthe SISO and 2×2 CLSM and 4×4 CLSM cases.Table D.1.: log log fit results for the 1×1, 2×2, and 4×4 antenna configurations.1×1 2×2 CLSM 4×4 CLSMMultiplexing gain a - 1.55 2.67MU-gain flattening b 5.6 7.07 10.33While the potential throughput of 4×4 is double that of 2×2, such gains are not1 The original expression is derived for MU-gain derived from the channel distribution, rather thanthat of the channel and the cell pathloss/layout.98
D. Evaluation of Multi-User GainAvg. cell throughput [Mbit/s]240220200180160140120100800Throughput 4x45 10 15 20 25 30number of UEs/cellFairness of UE throughput10.90.80.70.60.50.40.30.20.100Fairness 4x45 10 15 20 25 30number of UEs/cellRound Robin Proportional fair Best CQI fitFigure D.3: 4×4 CLSM transmit mode multi-user gain results. Left: throughput results.Right: fairness results. Vertical lines mark the 95% confidence intervals.achievable unless unrealistically high SNRs are present, even in the case of uncorrelatedchannels, as previously shown on Figure 3.17.An analysis such as the one conducted here also quantifies the reduction in multi-usergain seen between the round robin and proportional fair schedulers when switchingfrom a 2×2 to a 4×4 antenna configuration due to the higher suboptimality (dueto the higher number of degrees of freedom), of the PMI and RI feedback in 4×4MIMO.The results of practically-employed schedulers, such as round robin and proportionalfair can in this manner be compared to the upper threshold of the best CQI scheduler,which is not used due to it starving the majority of UEs in a cell.Alternately, and similarly to the evaluation in Chapter 5, throughput and fairness(see Section 5.4) results can be evaluated together. As observed from Figures D.1 toD.3, proportional fair scheduling consistently converges to the same fairness valueof roughly 0.7, with a decrease in multi-user gain for higher antenna counts, whilethe varying fairness results of round robin hint at it operating at different points ofthe fairness-throughput trade-off shown in Section 5.6.99
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DissertationSystem Level Modeling a
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I hereby certify that the work repo
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KurzfassungDie vorliegende Arbeit p
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ContentsContents1 Motivation and Sc
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BibliographyThe combined throughput
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2. 3GPP Long Term Evolution2. 3GPP
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2. 3GPP Long Term Evolutionchannel
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