4.6 Detailed Investigation by Means of the Cumulative
outdoor, indicated with the dashed colored curves. In addition, it gives the throughput of the users connected to the MBS which are located inside the same building as the femtocell, drawn with a solid line. Again, as in Figure 4.21 the lines of the curves for the SeqDet, SimProb, and Global Opt match.
0 1 2 3 4 5 6 7 8 9 10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
MS@MBS throughput [Mbit/s]
Cumulativedistributionfunction
No ICIC: Indoor MUEs Seq Det:D=1, Indoor MUEs Sim Prob:D=1, Indoor MUEs Global Opt:D=1, Indoor MUEs No ICIC: Outdoor MUEs Seq Det:D=1, Outdoor MUEs Sim Prob:D=1, Outdoor MUEs Global Opt:D=1, Outdoor MUEs
Figure 4.22: ICIC sequential deterministic, simultaneous probabilistic, global optimizer, and noICICfor a lowHBSdensity, with 3MBSand 12HBS:CDF of the throughput of outdoor and indoor mobile stations connected to theMBS
The throughput of the outdoor MUEs draws 20% of the users which gain up to about 1Mbit/s higher data rates without interference coordination, but the rest of the users has only minimal data rates decreasing even to zero. The observation made for the outdoor users is even more sever for the MSs located indoors which can directly be shown with the throughput curve.
Now, even more severe: 12% of the users gain up tp about 750kbit/s higher data rates with no interference coordination but the remainder of the users receives only minimal rates below 1Mbit/s for 70% of the users and up to 5% of the users have zero rate. In sum, ICIC presents much higher cell edge and average throughput. Even in this minimum density deployment the indoor MUEs experience unacceptable interference levels.
The following considerations are made for a high density deployment with 1008 HBSs in the network. Again, the interference coordination techniques are compared to the situation without coordination. Figure 4.23 gives the UE throughput of all mobile stations in the network. For the overall throughput holds, as much more HBSs are introduced in the network which results also in a higher number of FUEs (1008) and the number of MUEs, in numbers 210, is much lower, that the crossing point moves. Now 78% of the users gain higher data rates without interference coordination but the rest has only minimal rates down to nothing at all. 12% of the users get even no throughput without interference coordination. When ICIC is applied only 2.5% remain with zero throughput within this very dense scenario. Thus, the weak performance for the cell edge users, which leads to a lot of users in outage, when no interference coordination is used, is unacceptable. Figure 4.24 depicts the throughput of the
users connected to the MBS. The users are split in two groups: First, the users connected to the MBS which are located indoors in the same building with the femtocell. And second, those users who are located outdoor. As before, the curves for the SeqDet and SimProb method, if not depicted differently, lie on top of one another.
0 5 10 15 20 25 30 35 40 45
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
MS throughput [Mbit/s]
Cumulativedistributionfunction
No ICIC Seq Det:D=1 Sim Prob:D=1
Figure 4.23: ICICsequential deterministic, simultaneous probabilistic, and no ICICfor a highHBSdensity, with 21MBSand 1008HBS:CDFof the
through-put of all mobile stations in the network
0 1 2 3 4 5 6 7 8 9 10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
MS@MBS throughput [Mbit/s]
Cumulativedistributionfunction
No ICIC: Indoor MUEs Seq Det:D=1, Indoor MUEs Sim Prob:D=1, Indoor MUEs No ICIC: Outdoor MUEs Seq Det:D=1, Outdoor MUEs Sim Prob:D=1, Outdoor MUEs
Figure 4.24: ICICsequential deterministic, simultaneous probabilistic, and no ICICfor a highHBSdensity, with 21MBSand 1008HBS:CDFof the
through-put of outdoor and indoor mobile stations connected to theMBS
When interference coordination is used, 75% of the outdoor users now experience a better situation. In here, the demand for interference coordination gets even more clear: All indoor users experience a better situation as without coordination. With ICIC no users have zero
data rate. Without coordination approximately 50% of the indoor MUEs are not able to receive any data. With this it gets even more clear, that interference handling measures have to be taken. Figure 4.25 shows the SINR within this dense deployment. In case of no coordination, the SINR of the cell edge users gets below -10dBm, which is very bad.
Differently, when ICIC is applied it is still below 0dB but can be increased by about 7dB.
The average SINR with the interference coordination technique is still 2.5dB better than when no countermeasures are taken.
−10 −5 0 5 10 15 20 25
0 0.2 0.4 0.6 0.8 1
SINR values in dB
Cumulativedistributionfunction
No ICIC Seq Det:D=1 Sim Prob:D=1
Figure 4.25: ICICsequential deterministic, simultaneous probabilistic, and no ICICfor a highHBSdensity, with 21MBSand 1008HBS: CDFof
signal-to-interference-plus-noise ratio
Figures 4.26–4.28 draw the CDF of the MS throughput for minimum HBS density with one HBS per MBS, 21 MBS in total which results in overall 21 HBS. Each figure draws a different number of subbandsDi=D=1, . . . ,4.
Figure 4.26 shows the overall MS throughput for all users including MUEs and FUEs. With 10 MUE on average per MBS and 21 MBS overall, there are in total about 210 users con-nected to the macrocells. This is much higher than the number of users concon-nected to the femtocells, as only 21 are present in total. In sum, there are much more macrocell users than femtocell users. This user distribution is also reflected in the overall mobile station through-put curves. The femtocells with the potential for high throughthrough-put rates mainly contribute to the best 10% of the users. The values below follow in this case the macrocell users.
The total achievable throughput increases with the number of available subbands. The kink in the curves around the 95-th percentile results from users with very good SINR which can transmit with the maximum modulation and coding scheme which limits the maximum achievable rate in this case.
0 5 10 15 20 25 30 35 40 45 0
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
MS throughput [Mbit/s]
Cumulativedistributionfunction
Sim Prob:D=1 Sim Prob:D=2 Sim Prob:D=3 Sim Prob:D=4
Figure 4.26: ICICsimultaneous probabilistic for a minimumHBSdensity, with 21 MBSand 21 HBSand increasing number of subbandsDfrom one to four:
CDFof the throughput of all mobile stations in the network
Figure 4.27 shows the MS throughput for the users connected to the femtocell. The total achievable throughput for the FUEs increases with the number of available subbands.The kink in the curves again results from users with very good SINR which can transmit with the maximum modulation and coding scheme which limits the maximum achievable rate in this case.
0 5 10 15 20 25 30 35 40 45
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Indoor MS@HBS throughput [Mbit/s]
Cumulativedistributionfunction
Sim Prob:D=1 Sim Prob:D=2 Sim Prob:D=3 Sim Prob:D=4
Figure 4.27: ICICsimultaneous probabilistic for a minimumHBSdensity, with 21 MBSand 21 HBSand increasing number of subbandsDfrom one to four:
CDFof the throughput of all mobile stations connected to a femtocell
Figure 4.28 depicts the MS throughput for indoor as well as for outdoor users connected to the macrocell. For such a low femtocell density, the total achievable throughput for the
MUEs is hardly effected. Further, it does not decrease significantly when the number of available subbands in the femtocell increases.
0 1 2 3 4 5 6 7 8 9 10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
MS@MBS throughput [Mbit/s]
Cumulativedistributionfunction
Sim Prob:D=1, Indoor MUEs Sim Prob:D=2, Indoor MUEs Sim Prob:D=3, Indoor MUEs Sim Prob:D=4, Indoor MUEs Sim Prob:D=1, Outdoor MUEs Sim Prob:D=2, Outdoor MUEs Sim Prob:D=3, Outdoor MUEs Sim Prob:D=4, Outdoor MUEs
Figure 4.28: ICICsimultaneous probabilistic for a minimumHBSdensity, with 21 MBSand 21 HBSand increasing number of subbandsDfrom one to four:
CDF of the throughput of outdoor and indoor mobile stations connected to the MBS
Previous investigations for increasing subband sizes considered only a minimum density of femtocells. The following Figures 4.29–4.31 show a much denser deployment. In here, D= 1, . . . ,4 for a deployment factor of Pd = 0.2 which drops in total 1008 HBS in the network are considered. As before, if not depicted differently, the lines of the curves for the sequential deterministic approach withD=1 and the simultaneous probabilistic method withD=1 match.
0 5 10 15 20 25 30 35 40 45
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Indoor MS@HBS throughput [Mbit/s]
Cumulativedistributionfunction
Seq Det:D=1 Sim Prob:D=1 Sim Prob:D=2 Sim Prob:D=3 Sim Prob:D=4
Figure 4.29: ICICsimultaneous probabilistic for a highHBSdensity, with 21 MBS and 1008 HBSand increasing number of subbands D from one to four:
CDFof the throughput of all mobile stations connected to a femtocell
The achievable throughput of the users connnected to the femtocell increases with increasing subband sizes up to a subband size ofD=3. With 4 subbands used in total, the maximum achievable rate is still increased but critical interference situations cannot be solved ade-quately. In here, no degree of freedom to find more beneficial resources is left. Now, even 45% of the users could achieve a better rate with a subband size of three. Thus, in order to provide an overall preferential situation, the network providers should select the number of allowed subbands in the femtocells properly according to the interference situation.
0 1 2 3 4 5 6 7 8 9 10
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Indoor MS@MBS throughput [Mbit/s]
Cumulativedistributionfunction Seq Det:D=1, Indoor MUEs
Sim Prob:D=1, Indoor MUEs Sim Prob:D=2, Indoor MUEs Sim Prob:D=3, Indoor MUEs Sim Prob:D=4, Indoor MUEs Seq Det:D=1, Outdoor MUEs Sim Prob:D=1, Outdoor MUEs Sim Prob:D=2, Outdoor MUEs Sim Prob:D=3, Outdoor MUEs Sim Prob:D=4, Outdoor MUEs
Figure 4.30: ICICsimultaneous probabilistic for a highHBSdensity, with 21 MBS and 1008 HBSand increasing number of subbands D from one to four:
CDF of the throughput of outdoor and indoor mobile stations connected to the MBS
The throughput of the outdoor MBSs is similar for different numbers of selected subbands.
Differently, when the number of subands increases, the throughput for the indoor MUEs decreases notably but still communication seems possible as all users receive a minimum throughput rate.
Figure 4.31 shows the CDF of the SINR for all scheduled user in the network.
−10 −5 0 5 10 15 20 25
0 0.2 0.4 0.6 0.8 1
SINR values in dB
Cumulativedistributionfunction
Seq Det:D=1 Sim Prob:D=1 Sim Prob:D=2 Sim Prob:D=3 Sim Prob:D=4
Figure 4.31: ICICsimultaneous probabilistic for a highHBSdensity, with 21 MBS and 1008 HBSand increasing number of subbands D from one to four:
CDFof signal-to-interference-plus-noise ratio
The SINR decreases when the number of selected subbands increases. Whereas, for sub-bandsizesD=1, . . . ,3 the SINR is within a similar range, increasing to a number of 4 sub-bands where no coordination of the resources between the femtocells is possible anymore but only protection of the MBSs due to the dedicated middle subband is possible. In sum, on average the reduction in SINR is increasing with the number of allowed subbandsD.