Chapter 3 Simulation Setup
3.6 Platform architecture
To sum up the above introduction, the platform was consisted of the infrastructure, interface, radio resource management, and library (Figure 3-10). In the infrastructure, we start to the “sim.c”, which include the whole flow. The “bs.c”, “rs.c”, “ms.c” were include the function initial and function enable. The generation message was saved in the interface, the method can provide convenient data exchange like the Figure 3-10.
After infrastructure and interface, the radio resource management was including the three parts: Handoff Scheduling Packet arrange. After the “Packet Arrange”, if the simulation time was over, we will get the simulation data.
Figure 3-10 Platform architecture
Finally, table 3-7is to summarize all the setting mentioned in this chapter for our simulation platform.
TABLE 3-7 PARAMETERS SETTING IN SIMULATION PLATFORM
Parameters Value/Comment
Cell layout Hexagonal grid, 19 cells (wrap around)
Sectors per cell 3
Frequency reuse factor 1x1, 1x3
Available bandwidth 10MHz in 1x1, 10/3 and 10*3 MHz in 1x3 reuse Antenna pattern (Θ3dB , Am) (70, 20 dB), according to [33]
Beamwidth 120°[33]
Antenna bore-sight gain 3 dB[33]
Cell radius 1 km[32]
Transmitter/Receiver Downlink (from BS to MSs and RSs , RS to MSs)
Duplex TDD mode
DL/UL subframe ratio 1:1
Frame length 5ms, according to [1]
Frame structure 1024-FFT OFDMA downlink carrier allocations with PUSC, according to [1]
OFDMA symbol length 102.9 μs, according to [34][35]
OFDMA symbols per slot 2 symbols
BS Tx power 46dBm (40 Watt), according to [32]
BS Antenna gain 17 dBi, according to [32]
BS back off 5 dB, according to [37]
RS Tx power 36dBm (4 Watt), according to [32]
RS Antenna gain 17 dBi, according to [32]
RS back off 5 dB, according to [37]
Thermal Noise Density -173.93 dB/Hz, according to [37]
MS Noise Figure 9dB, according to [35]
BS and RS to MS Pathloss model Type-E: PL(d)=38.4+35log10(d) dB for 50m < d < 5km[36]
Shadow fading model Log-normal distribution with STD=3.4,8dB and Gudmundson’s correlation model, according to [36]
Mobility model MS speed : 30 km/hr
Probability to change direction : 0.2 Max. angle for direction update : 45o
BS Power contol Max power
AMC QPSK+CC 1/2, 16-QAM+CC 1/2, 64-QAM+CC
1/2, according to [1]
Channel assignment Frequency first, according to [2]
Scheduling control Early Deadline First (EDF)
Handoff Hard handoff
Traffic model FTP, VoIP, HTTP [9]
CHAPTER 4
SIMULATION RESULT
In this chapter, the performance analyses with different frequency reuse factors and with and without relay station are presented. The simulation result can be classified into two sections based on different traffic types: Real-Time-Service, and Mixed traffic. In our simulation, we assume each user served by base station and relay station is perfectly traced. It means that the serving user is enhanced with maximum boresight gain of antenna pattern. In each section, the performances of real time services and mixed traffic are demonstrated include packet droop rate, the system throughput, and AMC usage are discussed.
4.1 Real Time Service
In this section, the performance analysis of real-time service is presented. When users are large, the frame will be more likely fully utilized, the permutation effect will be nullifier. The interference level will be saturated when all resource units are fully used.
We will only use the VoIP traffic type in following simulation.
4.1.1 AMC usage and throughput for different cell radius
First we check the influence of the distance on system performance. In [32], the cell radius was 1000m, and the simulation result was show that we had the higher BPSK ratio in figure 4-1. Hence, we try to simulate the cell radius 800m as compared with 1000m. In figure 4-2, we will find whether we'll get the better AMC percentage if we decrease the cell radius. The most of transmissions are under QPSK and 16QAM modulation, and with the increase of traffic loading, the utilization of QPSK burst profile is getting higher. About the receive signal, here have a formula:
Receive power = Transmit power * constant / (radius)α (4-1) α = 2 ~ 4, 2 mean in free space, 4 means in urban environment
Follow the formula, the system interference will increase by decrease the distance, but the user also can get the higher transmit power. The system SINR will be better.
Hence we can find the interference level is increase with traffic loading and increasing the cell radius. In figure 4-3 and figure 4-4 is show the system throughput and packet drop rate at the cell radius 800m and 1000m. It can clear display of the simulation result that is 800m will have the batter throughput and lower packet drop
rate. Although the 800m had the better performance, we will continue using 1000m in our whole simulation, because we consider the continuity between the parts of our research.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 2 3 4 5 6 10 20 30 40 50 60 70 80 90 100
Number of VoIP user per cell(1000m,reuse=1)
AMC%
EDF_bpsk EDF_qpsk EDF_qam16 EDF_qam64
Figure 4-1 AMC usage of VoIP type at cell radius 1000m
Figure 4-2 AMC usage of VoIP type at cell radius 800m
Figure 4-3 Throughput at cell radius 800m and 1000m
Figure 4-4 Packet drop rate at cell radius 800m and 1000m
4.1.2 AMC usage and throughput for different frequency reuse
At this section, we will check the influence of the frequency reuse factor. The cell’s frequency reuse factor in our simulation platform has two select, 1 and 3. The total bandwidth of frequency reuse factor 1 is 10MHz in our simulation. Frequency reuse factor 3 needs used triple bandwidth, which is 30MHz. Another condition is reuse factor 3 the system have trisect bandwidth that is 10MHz. The cell with frequency reuse factor 3 has longer distance between two cells used the same bandwidth than frequency reuse factor 1. Therefore, the interference in frequency reuse factor 3 is lower due to stronger interference path loss caused by longer distance. In the simulation result (Figure 4-1 versus Figure 4-5, Figure 4-2 versus Figure 4-6), we can see that the frequency reuse factor 3 can provide better transmission environment.
In Figure 4-7, Figure 4-8, we try to present the performance that is in the different distance and different frequency reuse factor. It is very clear that is the short radius and frequency reuse factor equal to 3 can let the throughput maximum and drop rate minimum. And the frequency reuse factor 1 has more interference then frequency reuse factor 3 no matter the distance.
In Figure 4-9, Figure 4-10, we try to find the influence in different system bandwidth.
As above, when the frequency reuse factor equal to 3, the system bandwidth we can provide 30MHz and 10MHz in three cells. About the relationship, here have a formula:
C=W * log2(1+S / N) (4-2)
C: Channel Capacity, bits/s; W: Bandwidth, Hz; S: signal power; N: noise power It is very clear that the system bandwidth will influence the system capacity. The simulation results were show that the frequency reuse factor equal to three and the cell bandwidth equal to 30MHz (three cells) will get the best performance. But we
Figure 4-5 AMC usage of VoIP type at frequency reuse factor = 3(1000m)
0%
Figure 4-6 AMC usage of VoIP type at frequency reuse factor = 3(800m)
0.0E+00
Figure 4-7 Throughputs at frequency reuse factor 1 and 3(800m & 1000m)
0%
10%
20%
30%
40%
50%
60%
1 2 3 4 5 6 10 20 30 40 50 60 70 80 90 100
Number of VoIP user per cell
Drop rate %
Drop rate_VoIP_800m_reuse=1(30) Drop rate_VoIP_800m_reuse=3(30) Drop rate_VoIP_1000m_reuse=1(30) Drop rate_VoIP_1000m_reuse=3(30)
Figure 4-8 Packet drop rate at frequency reuse factor 1 and 3(800m & 1000m)
Figure 4-9 Throughputs at frequency reuse factor 1 and 3(1000m)
Figure 4-10 Packet drop rate at frequency reuse factor 1 and 3(1000m)
4.1.3 AMC usage and throughput for different system
At this section, we try to find out the difference in the two systems: 802.16e and 802.16j. In this simulation we use some skill let the platform can switch between the two systems, the skill like the resource allocation, scheduling, etc. In the simulation environment, the two results (Figure 4-11, Figure 4-12) were very similar below 30 users, but over 30 the interference were become poor in the 802.16j transmit environment. The relation result we can see in Figure 4-13 and Figure 4-14. In Figure 4-12, the BPSK user percentage increase cause of the interference between the BS and RSs. This reason is that as user number increases, more users may be served by a BS and raise interference to the link between RS and BS. In the hexagon cell, the base station will serve partial MS user and relay station. The base station transmits information to the MS and RS in the same access zone, these will cause some interference. When the system have few users, they have low probability fall in the high interference area, when the users were increase, they will have high probability fall in the high interference area. Then in base station point of view, 802.16e the system have the constant AMC percentage, but in 802.16j have become poor AMC percentage when user is increased. But below 40 users, the advantage of using relay station will be found.
Figure 4-11 AMC usage of VoIP type at 802.16e
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 2 3 4 5 6 10 20 30 40 50 60 70 80 90 100
Number of VoIP user per cell(1000m,reuse=1)
AMC%
EDF_bpsk EDF_qpsk EDF_qam16 EDF_qam64
Figure 4-12 AMC usage of VoIP type at 802.16j
Figure 4-13 Throughputs at 802.16e and 802.16j
Figure 4-14 Packet drop rate at 802.16e and 802.16j
4.2 Mix traffic Service
In this section, the performance analysis of mix traffic service is presented. We will use the three traffic types (VoIP=50%, FTP=16%, HTTP=34%) in following simulation. And we will find out the relation in different system and different relay station number.
4.2.1 AMC usage and throughput for different system
At this section, we will check again the difference in the two systems: 802.16e and 802.16j. At this time we use the mix traffic type to evaluate the system performance.
In Figure 4-15, Figure 4-16, the two systems have the same AMC percentage ratio when user number are below 30, and when user number are over 30, it also got the same curve like the Figure 4-12. But the different in the two services is in the mix traffic service the FTP service will be preempted by VoIP services; therefore the FTP throughput will be decrease with increasing number of VoIP users. In Figure 4-17, Figure 4-18, we can get the two results. First, the simulation result show that the non-real-time service throughput will decrease as the number of real-time service increase. It is reasonable because transmission of real time service will take the resource of transmission opportunity from non real time service. Second, the 802.16j system throughput will always less then 802.16e. In our simulation platform, the total downlink resource is 12 OFDMA slots. The 16j base station was only controlled 7 OFDMA slots and another 5 OFDMA slots was controlled by the relay station.
According to the second result, if the resource in relay zone will not fully utilize, it will be a waste. Another limiting factor is coding rate, in our simulation platform we only use 1/2 coding rate, but in standard [1] it prepare three kinds of coding rate: 1/2, 2/3, 3/4. If we have high SINR in the link, it will waste the performance of relay station.
Figure 4-15 AMC usage of mix traffic at 802.16e
Figure 4-16 AMC usage of mix traffic at 802.16j
Figure 4-17 Throughputs of mix traffic at 802.16e
Figure 4-18 Throughputs of mix traffic at 802.16j
4.2.2 AMC usage and throughput for different relay station number
At this section, we will check the relation between the relay station number and the system performance. In Figure 4-19, Figure 4-20, Figure 4-21 were show the three different number of relay station (the relay station number is 3, 6, 9) for system throughput. In Figure 4-22 (Total throughput), Figure 4-23 (HTTP throughput), Figure 4-24 (FTP throughput), Figure 4-25 (VoIP throughput) were show the individual result at the number of 3, 6 and 9 relay stations. In Figure 4-26, the VoIP packet drop rate of mix traffic at the 3, 6 and 9 relay stations.
We will find when the relay station numbers were increase, the system throughput will decrease. Here have two reasons, first is the effective bandwidth was decrease, it reduce the effective resource unit per relay station. The formula is:
Effective bandwidth = System bandwidth (10MHz) / Relay station number (4-3) The second is the base station did not prepare the relation directional antenna to every relay station, so the transmission efficiency will not good, although the link between BS and RS is LOS.
Figure 4-19 Throughputs of mix traffic at 3 relay stations
Figure 4-20 Throughputs of mix traffic at 6 relay stations
Figure 4-21 Throughputs of mix traffic at 9 relay stations
Figure 4-22 System throughputs of mix traffic at 3, 6 and 9 relay stations
Figure 4-23 HTTP throughputs of mix traffic at 3, 6 and 9 relay stations
Figure 4-24 FTP throughputs of mix traffic at 3, 6 and 9 relay stations
Figure 4-25 VoIP throughputs of mix traffic at 3, 6 and 9 relay stations
Figure 4-26 VoIP Packet drop rate of mix traffic at 3, 6 and 9 relay stations
In the simulation result, the amount of relay station numbers will not be affects the link quality between BS to MS and BS to RS. Therefore, we only show Figure 4-27 (3 relay stations) represented the base station to the whole system, Figure 4-28 (9 relay stations) represented the link between the base station to the relay stations. It can be seen that burst profile BPSK is barely appear. That is because the interference is not serious in BS to RS.
Figure 4-27 Base station AMC usage of mix traffic at 3 relay stations
Figure 4-28 Base station to relay station AMC usage of mix traffic at 9 relay stations
CHAPTER 5
CONCLUSION AND FUTURE WORK
In this thesis, our contributions are (1) The Mobile Multihop Relay(MMR) system level platform establishment for supporting MAC layer with basic resource management in IEEE 802.16j draft standard and (2) The performance study of IEEE 802.16j system.
This platform is used for preliminary understanding of IEEE 802.16j system. In this simulator, we focus on studying the overall and complete downlink performance and investigating the advantages and disadvantages of different environment factor like the distance, frequency reuse factor and the number of relay station. The applied scheduling algorithm is the Early Deadline First (EDF). Secondly, real time service and mix traffic service performance is studied. After that, real time service performance with regarding to different environment factor is investigated. From these performance simulations, the conclusions are described as below: For real time service, the distance and frequency reuse factor will influence the throughput and packet drop rate. The shorter cell radius can provide better transmit environment. The frequency reuse factor will decide the interference level and the effective bandwidth.
The relay station number will also effect the effective transmit bandwidth and interference level. After simulating, we find the transparent relay station may not be the perfect. Transparent relay station means it can do the throughput enhancement.
We think the actuality meaning which helps the worst case user to improve the service quality like the BPSK user upgrade to the QPSK or other AMC, but everything is not ideal. The transparent relay station will have something done at the expense. The effective resource units were consumption on the resource segment. This will let the total system throughput degrade.
Hence, in future work, we need to let the more smart mechanism in transparent relay station. We need let the base station can partial control the relay zone, if the relay zone will not fully utilize. We did not setup enough corresponding coding rate, so in the future we need to set up whole coding rate to make up more diversified in our platform. We need to setup the relation directional antenna technical to provide every relay station have the better radio frequency (RF) condition, like the beamforming.
With beamforming, the co-channel interference is reduced and SINR is enhanced so that the transmission quality will be promoted. Besides, the relay station setup in the cell edge will improve the poor RF, but this situation needs to consider the interference in the neighbor cell. In the future, the research in the non- transparent
relay station will have more benefit. However, it is more complicated then transparent relay station. The trade-off shall be taken into consideration.
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