 Open Access
 Total Downloads : 151
 Authors : Naemah Mubarakah, Soeharwinto, Fakhruddin Rizal B
 Paper ID : IJERTV2IS110361
 Volume & Issue : Volume 02, Issue 11 (November 2013)
 Published (First Online): 13112013
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Optimizing OFDM Downlink Performance on LMDS System
Naemah Mubarakap, Soeharwinto 2, Fakhruddin Rizal B.3
13Electrical Engineering Department, University of Sumatera Utara, Medan
Abstract
Local multipoint distribution service (LMDS) is one of the transmission solutions for broadband applications. LMDS operates in millimeter band using and provides high bitrates services up to 40 Mbps. However, LMDS implementation in tropical countries as in Indonesia deals with rain intensity which introduces high transmission loss. In order to improve the performances of LMDS services in rainy environment, an adaptive power allocation (APA) technique is integrated. APA is a crosslayer technique which optimizes power allocation among users with fixed subcarrier division. The simulations show that the technique improves transmission capacity 9.8% in average, data rate 13.79% in average, utility 25.27% in average and fairness 25.3% in average for rain loss 30dB.
[5, 6] proved that the APA method improves the transmission efficiency and the allocation fairness on adaptive white Gaussian noise (AWGN) environment. Jun et al. analyzed performance improvement on power and subcarrier allocations [7].Previous research uses joint power and subcarrier allocation (JSPA) technique on millimeter channel with selected case in Surabaya city [8]. This paper enhances previous research by considering the effect of rain to the system, with selected area is Medan city.

Research Method

Rain Intensity Measurement
Rain intensity measurement is performed in three different locations: Padang Bulan, Polonia and Sampali using Hellman measurement unit. The location map and measurement unit are shown in Figure 1 dan 2.
1. Introduction
Broadband services such as high speed internet, digital video, audio broadcasting and video conference experience high demands. Local multipoint distribution service (LMDS) systems operate in frequency band 20 40 GHz [13] is one of the existing technologies used to provide those services. The radio propagation uses carrier frequency higher than 10 GHz is able to provide wide band modulating signal in one side, but sensitive to rain loss on the other side. This problem increases when LMDS system applied in tropical countries as the rain intense [4].
Padang Bulan
Polonia
Sampali
Existing works deal with performance enhancements on LMDS system mostly lay on separated layer improvements [3] which may not be optimal. Therefore, the approach combining two or more neighboring layers is developed to optimize the achievement in each layer. The method is referred to as a crosslayer technique. This paper integrates physical (PHY) layer and medium access control (MAC) layer in LMDS system with multiuser OFDM by using an adaptive power allocation (APA) technique. The APA technique requires the channel state information (CSI) and the incoming traffic information [57]. Song and Li
Figure 1. Rain intensity measurement location
Hellman measurement unit uses a rotary writing pad and a pen moved by floating device on a water tube. When rain enters the water tube, the water lifts the pen up and the level is recorded in a rotary pad. When the water tube is full, the siphon automatically discharges the water tube. At the same time pen moves down and the vertical line is recorded. More rain generates more vertical lines. The rain intensity is calculated from the level and the frequency of those vertical lines.
Figure 2. Rain intensity measurement unit

Rain Loss Calculation

Path loss is very important in radio communication systems, especially when the radio uses microwave and millimeter frequency bands. The higher the carrier frequency, the higher the path loss occurs. The specific path loss Y (dB/km) and the rain intensity R (mm/h) relation is a function of frequency and expressed as [9]:
distributed of rain intensity. The calculation steps are [10]:

Determine rain intensity 0,01% of the intensity distribution, R0,01% (mm/h).

Calculate the specific path loss Y.

Find the horizontal correlation factor r0,01 for R=0,01% using Equation 3:
(3)
where r is reduction factor, d is distance (km), d0= 35e0.015R0,01 for R0,01 100 mm/h, and d0=35e0.015R0,01
for R0,01>100 mm/h.

Calculate the average rain loss 0,01% per year using Equation 4:
A0,01 = Y(x) d.r (4)

Find the rain loss for other percentages, Ap (0,001% to 1%) by following rules:
– Area with earth latitude higher than 300
(1)
The rain loss in a propagation path with length of L (km) is expressed by [9]:
Ap A0.01
0.12 p(0.546 0.043 log10 p)
(5)
0
L – Area with earth latitude lower than 30
A aR(z)b dz
o
(2)
Ap 0.07 p
0.855 0.139 log10 p
A is the rain loss in dB, R(z) is rain intensity (mm/h), a and b are variables which depend on radio
A0.01
(6)
wave polarization and frequency.
To validate the rain loss calculation, ITUR Rec.P.53010 is referred by using cumulative
Specific path loss calculation depends on signal polarization and frequency [11], as shown in Table 1.
Table 1. Parameter k and for various frequencies and polarizations [11]
Frequency (GHz) 
kH 
kV 
H 
V 
1 
0.0000387 
0.0000352 
0.912 
0.880 
4 
0.000650 
0.000591 
1.121 
1.075 
6 
0.00175 
0.00155 
1.308 
1.265 
8 
0.00454 
0.00395 
1.327 
1.310 
10 
0.0101 
0.00887 
1.276 
1.264 
12 
0.0188 
0.0168 
1.217 
1.200 
15 
0.0367 
0.0335 
1.154 
1.128 
20 
0.0751 
0.0691 
1.099 
1.065 
25 
0.124 
0.113 
1.061 
1.030 
30 
0.187 
0.167 
1.021 
1.000 
35 
0.263 
0.233 
0.979 
0.963 
40 
0.350 
0.310 
0.939 
0.929 
45 
0.442 
0.393 
0.903 
0.897 
50 
0.536 
0.479 
0.873 
0.868 
Table 2. Parameters of the LMDS system (k=1,38.1023 and To=298 K)
GHz
Parameter 
Units 
Formula 
Value 
Transmit Power into Antenna 
dBW 
Ptx: transmit power per carrier 
0 
Transmit antenna gain 
dBi 
Gt:Gant 
15 
Frequency 
f: Transmit frequency 
30 

Path Length 
Km 
d: Hub to Subscriber Station Range 
2 
Field Margin 
dB 
Lfm : Antenna MisAlignment 
1 
FreeSpace Loss 
dB 
FSL = 92.4520*log(f)20*log(d) 
128,013 
Total Path Loss 
dB 
Ltot = FSL + LFM 
129,013 
Receiver Antenna Gain 
dBi 
Gr = Gant 
30 
Effective Bandwidth 
MHz 
BRF : Receiver Noise Bandwidth 
40 
Receiver Noise Figure 
dB 
NF : Effective Noise Figure 
5 
Thermal Noise 
dBW/MHz 
10*log(k*To) 
143,85 
System Loss 
dB 
Lsys=Gt+Ltot+Gr 
84,013 
Received Signal Level 
dBw 
RSL=Ptx+Lsys 
84,013 
Thermal Noise Power Spectral density 
dBW/MHz 
N0=10*log(k*To)+NF 
198,859 
Carrier to Noise ratio 
dB 
C/N = RSLNo10*log(BRF) 
98.8254 
2.3. The APA Algorithm
APA performance optimization implements water filling algorithm to achieve the expected bit error rate (BER). The algorithm is shown in Figure 3. In this
paper, waterfilling algorithm uses fixed subcarrier
In order to obtain optimum power allocation, iterative calculation is required. Suppose that each user has marginal utilityU ' r , the received power is the total transmitted power divided by number of user. If
i
i
i
i
the achieved throughput is a function of power
division so that optimum power allocation fulfills Equation 7 [5]:
p* f
allocation, then:
U ' r * 1
c ( f )
log
(1 ( f ) p( f )df
(8)
i
i
p* f i i
f
(7)
i 2 i
D
D
*
i
In order to integrate LMDS system with the
i is channel condition, where :
i
i
( f ) Hi
( f ) 2
outlined rain intensity calculation, the paper uses LMDS parameters from [8] which are outlined in Table
i
i

Value r* is optimum bitrate and is a normalized
Ni ( f )
with Hi(f) is channel gain, Ni(f) is noise, is BER representation:
power density constant.
N2 ( f )
H ( f ) 2
1,5

ln(5BER)
2
Water level of user 1
Water level of user 2
The utility parameter, U(r) demonstrates the capability of transmitting data which is formulated by Equation 9.
U (r) 0.16 0.8ln(r 0.3)
B
(9)
where r ci (n).f and f k .
0 N1 ( f ) f1 f2
1
1
H ( f ) 2
Frequency
In analysis, the LMDS system is assumed to have user with individual bandwidth B=80 MHz and
Figure 3. Waterfilling algorithm subcarriers K=8000.
The fairness is achieved if the user utility closes to the average value. The fairness is determined by Equation 10:
Table 4. Result of data rate simulation
M
M
1 U (r )
(10)
M


Results and Analysis
i i
i1
Rain loss simulation on each LMDS user is performed before analyzing the overall LMDS performance. The distant of users to base station is set in between 1 3 km. As a result, maximum transmission capacity is obtained as the limit of the maximum throughput can be achieved by LMDS system. The maximum transmission capacity is calculated for three different conditions: bright, rainy and rainy with an APA technique. Table 3 shows the outcome.
User Number
Distance (km)
Data rate (Mbps)
Clear Sky
Rain Attenuation
Without APA
APA
1
2.9623
154.93
37.22
59.66
2
2.5968
162.49
123.26
148.88
3
1.8701
181.39
89.50
94.45
4
1.1919
207.35
195.92
178.80
User Number
Distance (km)
Data rate (Mbps)
Clear Sky
Rain Attenuation
Without APA
APA
1
2.9623
154.93
37.22
59.66
2
2.5968
162.49
123.26
148.88
3
1.8701
181.39
89.50
94.45
4
1.1919
207.35
195.92
178.80
Table 5. Result of utility simulation
User Number
Distance (km)
Utility (bps/Hz)
Clear Sky
Rain Attenuation
Without APA
APA
1
2,9623
15.2468
14.1058
14.4833
2
2,5968
15.2849
15.0638
15.2149
3
1,8701
15.3729
14.8078
14.8509
4
1,1919
15.4799
15.4346
15.3614
User Number
Distance (km)
Utility (bps/Hz)
Clear Sky
Rain Attenuation
Without APA
APA
1
2,9623
15.2468
14.1058
14.4833
2
2,5968
15.2849
15.0638
15.2149
3
1,8701
15.3729
14.8078
14.8509
4
1,1919
15.4799
15.4346
15.3614
User Number
Distance (km)
Capacity (bps/Hz)
Clear Sky
Rain Attenuation
Without APA
APA
1
2.9623
7.7463
1.9086
2.9830
2
2.5968
8.1247
6.3208
7.4439
3
1.8701
9.0695
4.5899
4.7227
4
1.1919
10.3675
10.0471
8.9401
Distance (km)
Capacity (bps/Hz)
Clear Sky
Rain Attenuation
Without APA
APA
1
2.9623
7.7463
1.9086
2.9830
2
2.5968
8.1247
6.3208
7.4439
3
1.8701
9.0695
4.5899
4.7227
4
1.1919
10.3675
10.0471
8.9401
Table 3. Rain loss simulation
As shown in Table 3, the average bitrate for bright/ clear sky is 8.827 bps/Hz. The capacity decreases when the weather is rainy falling to 5.7116 bps/Hz. However, the capacity can be enhanced when APA technique applied, increasing up to 6.02243 bps/Hz. From this case, it is proven that the APA technique increases the capacity of system about 25.27 % when the path is rainy.
Further comparison can be seen in Table 4, where the average data rate when sky is clear is 176.54 Mbps. Rain causes data rate decreasing about 36.9%, down to
111.475 Mbps. Introducing APA technique within the LMDS system improves data rate to 120.4475 Mbps. It means the method achieves 13.79% improvement.
Utility simulation results 9.83 % improvement when APA is applied to LMDS system. This is depicted in Table 5, where the average utility in bright weather, rainy without and with APA 15.34613 bps/Hz, 14.853 bps/Hz and 14.97763 bps/Hz respectively.
In order to validate the results, 10.000 iterations are performed. The CDF iteration results that The APA technique improves capacity from about 0.00389
10.45 bps/Hz increase to about 1.002 10.49 bps/Hz. Utilities are improved from 9,141 15,47 bps/Hz to 13,61 15,49 bps/Hz. These improvements are depicted in Figure 5 and Figure 6.
Figure 5. The CDF of Capacity
Figure 6. The CDF of Utility
In term of fairness, the calculation produces 15.3461 for bright weather, 14.8530 for rainy without APA and 14.9776 for rainy with APA. Therefore, the fairness improvement caused by APA implementation is about 25.3%.

Conclusion
The adaptive power allocation (APA) technique is able to improve the LMDS performance, especially when the system implemented in the area with high rain intensity, such as in Indonesia. The simulations show that the improvements on LMDS capacity, data rate and utility on rain intensity 30 dB reaching 9.8 %,
13.79 %, and 25.27% respectively. While system fairness increases 25.3 %.
This paper has discussed the APA implementation on OFDM downlink for LMDS system which is used in rainy environment. However, the power distribution among user or the fairness is subject of propagation paths. Future work may explore APA implementation in both sides: base station and user to improve fairness.
References
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[3]. Falconer, D. and DeCruyenaere, J.P., Coverage Enhancement Methods for LMDS, IEEE Comm. Mag., pp. 8692. July, 2003. [4]. Salehudin, M., Hanantasena, B., Wijdeman, L., Ka Band LineofSight Radio Propagation Experiment in Surabaya Indonesia, 5th KaBand Util. Conf., pp. 161165, 1820 Oct., 1999. [5]. Song, G. and Ye Li, Crosslayer Optimization for OFDM Wireless Networks, part I, IEEE Wireless Comm. Vol.4 No.2 pp. 614624, March, 2005. [6]. Song , G., and Ye Li, Crosslayer Optimization for OFDM Wireless NetworksPart II : Algorithm Development, IEEE Transaction on Wireless Communications Vol.4 No.2, 2005.[7]. Jun, Y., Zhang and Ben Letaief, K, Adaptive Resource Allocation and Scheduling for Multiuser Packetbased OFDM Networks, IEEE Int. Conf. on Communications, V3.15,15651575, 2006.
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