Printer Friendly

Throughput performance for heterogeneous LTE network by using Fractional Frequency Reuse method.

INTRODUCTION

In current years, mobile broadband data traffic has witnessed enormous annual development rates [1-2] from Second Generation (2G), Third Generation (3G) and now Fourth Generation (4G) with more advanced features. The Long Term Evolution (LTE) is based on Orthogonal Frequency Division Multiple Access (OFDMA) in order towards reach the higher data rates as well as to enhance the spectral efficiency. The significant of nowadays problem is the inadequate of radio spectrum. So that one competent way of spectrum resource consumption is applying the Fractional Frequency Reuse (FFR). The frequency and time resources are allocated to users in orthogonal manner. However, the Co-Channel Interference (CCI) problem will occurs if the same sub-carriers are used by different users among adjacent cells particularly for cell edge users. Proper inter-cell interference coordination technique should be essential to boost the system capacity and system throughput [3-5].

Recently, LTE has developed a femtocell for indoor coverage extension. The femtocell becomes popular as a new emergence cellular revolution nowadays. Basically, femtocell are based on Access Point Base Station and it is called as Home Node B (HNB) or in other term as Home eNode B (HeNB) [6]. Fig. 1 shows the concept of femtocell networks where underlay in the macrocell network that used in this research work. This underlay concept so called heterogeneous networks that is consisting of macrocell and Low Power Nodes (LPNs). The LPNs has three features that make it easy and further flexible to deploy such as the LPNs are smaller in size, cost less and have a lower transmission power. The types of LPNs that has deployed in heterogeneous network are Picocell, Femtocell and Relay Station [7].

The rest of this paper is structured as follows. The next section presents an overview of the related works. After that, the system model of the radio resource partitioning for macrocell and femtocell networks by using FFR method will be introduced. The performance evaluations in the next section are carried out to analyzed the performance of the throughput for both macrocell and femtocell networks. Finally, conclusions are drawn in last section.

Related Work:

Interference management issues for the femtocell systems have been aggressively discussed in the LTE network nowadays. Numerous studies have attempted to explain and investigate the interference coordination in a network by adopted the FFR. The authors of [8] studied the different frequency reuse schemes in OFDMA network such as the LTE in order to prevail over the CCI problem. The total frequency band is separated into several sub-bands and each cell is allocated with the dissimilar sub-band as the way to lessen the interferences. However, the authors have presented expressions of SINR as well as cell data rate for integer frequency reuse (IFR), FFR and two level power control (TLPC) schemes where is offered an analytical approach based on the fluid model. The conclusion of this authors work is intra-cell interference is removed and the inter-cell interference is significantly reduced. The author of [9], proposed the fractional frequency reuse as well as pilot sensing scheme in order to lessen the CCI. The femtocells use the remaining frequency sub-bands following applying the frequency reuse of 3 or above to the macrocells. However, in the authors work, the overall capacity is improved when the macrocell throughput is reduced.

In [10], a method for optimal FFR scheme selection based on the mean user throughput or user satisfaction is proposed. This lesson is shown in a cellular network that does not bring the presence of femtocells. In [11], the author investigated inter-cell coordination for interference mitigation in multi-tier wireless network. The objective of this research is to investigate the difficulty of reasonable radio resource partitioning among the cell edge as well as cell center regions for the downlink of a SISO-OFDMA cellular system. The fractional frequency reuses (FFR) where tunes the values of a and p to achieve fairness is adopted. The finding shows that the mathematical relationship among network resources partitioning parameters can reduces the throughput margin among cell edge also cell center with 3 sectorizations.

A study on resource allocation with partitioning criterion for macro-femto overlay cellular networks with fractional frequency reuse is done by author [12]. In [12], a novel time-frequency resource allocation method by fractional frequency reuse for a macrocell and femtocell network is proposed. This research investigates macro and femto with have 19 macrocells but without any sectorizations applied same as in [9]. This research has shown that the standard capacity of macrocells and femtocells by changing the partition condition and the time resource ratio is determined. However, a weakness in this research work is that the amount of intra-cell interference from femtocells is not encompassed in the calculation. In [13], instant channel allocation technique is proposed under FFR method in order to improve the system throughput. In this research work, the Physical Resource Blocks (PRBs) is allocated to femtocells user through sectored FFR method to mitigate the interference between macrocell and femtocell. However, this research work only adopted three sectored FFR to analyze the performance of the implemented scheduling algorithms. In [14], FFR based resource allocation for device to device (D2D) is proposed. D2D communication consents two cellular devices to connect with each other without a base station, Another research work regarding on D2D communication in cellular networks with adopted the FFR method to mitigate interference is proposed in [15]. However, this research work also adopted three sectored of FFR same applied in [14].

The FFR is one of the answers to lessen the inter-cell interference in macrocell particularly for the cell edge users. Below this circumstance, the interference from the femtocell deployment ought to be lessened for the macro users. However, previous studies of [11] have not dealt with hexagonal network model but the author only adopted a circle network model to apply in their research work. Inspired by the achievement of C.Y.Oh [12], A.S.Afolabi [11] and the shortcoming of the author's work, the researcher goes further to investigate the throughput performance of the user's macrocell and femtocell. Unlike [11], the research's work is focuses on the radio resource partitioning for macrocell and femtocell networks that is adopted the hexagon network model with propose six sectorizations of FFR. This proposes work is the addition and enhancement from [16].

System Model:

The main objective of this study is to improves the throughput for both macro and femto users. In order to accomplish this objective, it needs to lessen the interference with FFR method. The method focuses on the analyzing and improving the macrocell throughput and maximizes the femtocell throughput. FFR is one of the interference mitigation technique in which divides the spectrum into some sub-band then allocates it to dissimilar regions of a cell. Fig. 2 illustrated how the radio resources are partitions for macrocell and femtocell networks in this research work. Fig. 2 shows the downlink of an OFDMA based macrocell system and the network resources in this work are partitioned based on FFR method with propose of six sectorizations where is enhancement and modification from [11]. The system bandwidth is divided into two parts which are the center region and the edge region. The yellow color is illustrated as the cell center region and other six colors is the cell edge region as shown in Fig. 3. The center region is assigned with sub-band B1 while the other six sub-bands B2, B3, B4, B5, B6, B7 are assigned to edge region with six sectored regions.

The researcher allocated the frequency sub-bands into macrocell as well as femtocell as shown in Fig. 4. Each one hexagonal cell of radius R is separated into center region (yellow color) and edge region (purple, pink, brown, orange, green and blue). One division of the available frequency band is devoted to the cell center users with reuse factor of 1, while the rest of the spectrum is correspondingly separated in six sub-bands and assigned to the cell edge users with reuse factor of 6.

The work firstly derives a mathematical formulation of network resource partitioning among cell which is emphasize the importance of the fraction of radius in center region a and the fraction of the system bandwidth p allotted for center region based on FFR method. The radio resource partitioning is analyzed based on two analyses which are for macrocell throughput and femtocell throughput. Some of the mathematical formulation involved in this research work as follows. Since the work is adopting the hexagonal network model, so that the area of the hexagon can be calculated from the following equation:

Area of hexagon = - [[square root of 3]/4] [R.sup.2] X 6 = 2.598076211 [R.sup.2] (1)

R = radius of hexagon cell,

[mu] = [N.sub.m]/2.598076211 [R.sup.2] (2)

[mu] = macro user density,

Nm = Number of macro user,

The system bandwidth can be stated as follow [11]:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (3)

W = the system bandwidth,

Wu = per user bandwidth,

Next, the system bandwidth can be expressed based on the Shannon's capacity equation as stated follow:

Wu = [C.sub.u]/[log.sub.z(1+CINR)] (4)

W = [2.418399153 NmCu/[R.sup.2]] [[integral].sup.R.sub.0] [1/[log.sub.z(1+CINR)]] rdr (5)

CINR = carrier to interference plus noise ratio,

Cu = per user capacity,

Rearranging the equation (5) and the capacity macro for user center region and edge region can be calculated from the following equation:

Cmacrocu = [beta]W[Rm.sup.2]/(2.418399153)(Nm)([[integral].sup.1000[alpha].sub.0] 1 + CINRc)rdr (6)

Cmacroeu = (1 - [beta])(W/6)[Rm.sup.2]/(2.418399153)(Nm)([[integral].sup.1000.sub.1000[alpha]] 1 + CINRe)rdr (7)

Cfemto = [[5 + [beta] - [6[alpha].sup.2][beta]]/6] NfW [log.sub.2] (1 + CINRf) (8)

Cmacrocu = capacity macro for center region user,

Cmacroeu = capacity macro for edge region user,

Cfemto = capacity femto,

[beta] = fraction of the system bandwidth for center region,

[alpha] = fraction of the center region radius,

Rm = macro radius,

Nf = number of femto user,

CINRc = carrier to interference plus noise ratio for center region,

CINRe = carrier to interference plus noise ratio for edge region,

CINRf = carrier to interference plus noise ratio for femtocell,

Further, from the equations (6), (7) and (8), the throughput for macro and femto can be calculated as follow:

Tmacro = (Nm) (k) (Bmk)(Cmacrocu + Cmacroeu) (9)

Tfemto = (Nf) (k) (Bfk) (Cfemto) (10)

Tmacro = macro throughput,

Tfemto = femto throughput,

k = the number of occupied sub-carrier,

Bmk = the sub-carrier assignment for macrocell,

Bfk = the sub-carrier assignment for femtocell,

Performance Evaluation:

A. Software Description:

The simulation results are carried out by using MATLAB software. Assume that the work has the limitation which no multi access channel and no fading for simplicity. Table I referring the several simulation parameters that have been used in the simulation part in order to achieved the results shown in the section below.

The overall network is composed of two-tier of macrocells and femtocells and the femtocells are randomly deployed over the macrocells. The researcher varies the number of macro and femto user to 180 users. All the base stations are operated by the OFDMA technology. An Omni-directional antenna and the six sector antennas are installed at a macro base station. The transmit power for center and edge region are 15W and 22W respectively. While the transmit power for all femto base station is 20mW.

B. Analysis Results:

The Comparison of Macrocell Throughput between FFR 6 and FFR 3

The objective of this part is to study the comparison of throughput between FFR of 6 sectors and 3 sectors due to several values of p. The total throughput for macrocell can be adjusted by controlling p and a. In this simulation analysis, as much three values of p varies in order to see the effect of p due to a for average total macrocell throughput. The result of total macrocell throughput for 6 sectors and 3 sectors shows in Fig.5 and Fig.6 respectively. Table II and Table III show the summary of simulation results for average total macrocell throughput 6 sectors and 3 sectors respectively.

Fig.5 and Fig.6 shows the macrocell throughput according to a and p. Table II and Table III shows the summary of simulation results for total macrocell throughput. The results demonstrated that the FFR of 6 is higher than the FFR 3 throughput at a = 0.1. The finding shows that the proposed method which is FF R of 6 is better in interference reducing so that can increases the throughput of cell. Referring to these findings, it shows that the higher the values of p assigned, the higher the values of total throughput of users in the network will be. While as increasing the value of a in a cell, the value of throughput will be decreases then. It can be concluded that the macrocell throughput is improved in higher assigning the p value. This is because with proper partitioning bandwidth in cell so then it will make the user balance received resources will reduce the interference occurrence and hence increasing the throughput values. From this simulation result that has been done, it noticed that the best p to choose to ensure the improvement of throughput is 0.9 as c ompared others. These findings are also supported from the previous author's study where is our macro throughput is achieved improvement compared to that author's work [20].

The Comparison of Femtocell Throughput between FFR 6 and FFR 3

Fig. 7 shows the comparison of the femtocell throughput between FFR 6 and FFR 3 as the number of a varies. The results demonstrated that the throughput for FFR of 6 which is the proposed method is higher than the FFR of 3. In propose method, the femto users can obtain the sub-carriers which are unused by macro users at every position. So the interference among the macro users also femtocells is significantly avoided and hence increases the throughput performance. However, the performance of femtocell throughput is decreasing as increasing the values of a. It cause of the probability of using the same sub-carriers by macro user and the femto users who are extremely near to each other as a increases. So the interference among the macro and femto user is higher and hence reduces the throughput performance.

The Throughput of Macro+Femto Users (Edge)

In Fig. 8, it refers to the throughput of total macro and femto users positioned at the edge region individual. In the OFDMA cellular network, the performance of the edge region stays reduced due to the inter-cell interference. In the proposed method, assigning the additional sub-carriers to femtocells which are positioned in the edge region, the throughput performance of the edge region is better. The finding shows that the throughput for the proposed method is higher than the FFR of 3 sectors. The throughput performance is study as the number of femtocell user increases. In this analysis, the number of femto users is varying up to 180 users.

The Throughput of Macro+Femto Users (Center)

In Fig. 9, it describes the throughput of total macro and femto users located at the center region only. The finding shows that the throughput for the proposed method is better and higher than the FFR of 3 sectors. The throughput performance is study as the number of femtocell user increases. In this analysis, the number of femto users is varying up to 180 users. From these findings, it shows that the throughput for FFR of 6 up to 180 users is 475Gbps while for FFR of 3 up to 180 users is 440Gbps.

Conclusion:

The research in this paper paying attention in the reducing the interference in LTE networks that mixed of femtocells as well. We propose an interference coordination method by using FFR. Our technique is based on the idea of fractional frequency reuse of 6 sectors in order to reduces interference in network and achieve higher throughput performance. The proposed method enhances the throughput performance especially for the cell edge users. It is also beneficial for the OFDMA network such as the LTE network where the FFR is applied.

This research work will be proceeds by looking on the development an algorithm that can offload macrocells traffic to femtocells and the inter-cell interferences can be reduces in a network in the future work.

ARTICLE INFO

Article history:

Received 12 March 2015

Accepted 28 April 2015

Available online 24 May 2015

ACKNOWLEDGMENT

This paper is part of research work that supported by the Faculty of Electrical Engineering, UiTM Shah Alam.

REFERENCES

[1] Ovum., 2010. Global Mobile Market Outlook. Premium Report, 2009-14.

[2] Cisco., 2011. Cisco Virtual Networking Index. Global Mobile Data Traffic Forecast Update. White Paper, 2010-2015.

[3] Boudreau., G., J, Panicker, N. Guo, R. Chang, N. Wang and S. Vrzic, 2009. Interference Coordination and Cancellation for 4G Networks. IEEE Communication Magazine, 47(4): 74-81.

[4] Novlan., T., J. Andrews, I. Sohn, R. Ganti and A. Ghosh, 2010. Comparison of Fractional Frequency Reuse Approaches in the OFDMA Cellular Downlink. In Global Telecommunications Conference (GLOBECOM 2010) IEEE, pp: 1-5.

[5] Xu., Z., G.Y. Li, C. Yang and X. Zhu, 2012. Throughput and Optimal Threshold for FFR Schemes in OFDMA Cellular Networks. Wireless Communications IEEE Transactions 11(8): 2776-2785.

[6] Neruda., M., J. Vrana and R. Bestak, 2009. Femtocells in 3G Mobile Networks. pp: 3-6.

[7] Ronoh., K., 2012. Load Balancing in Heterogeneous LTE-A Networks. Department of Science and Technology Linkoping University.

[8] Godlewski., P., M. Maqbool, M. Coupechoux and J.M. Kelif, 2008. Analytical Evaluation of Various Frequency Reuse Schemes in Cellular OFDMA Network. ValueTools.

[9] Kim, T. and T. Lee, 2008. Throughput Enhancement of Macro and Femto Networks by Frequency Reuse and Pilot Sensing. IEEE International Performance Computing and Communications Conference (IPCCC).

[10] Billios., D., C. Bouras, V. Kokkinos, A. Papazois and G. Tseliou, 2012. Optimization of Fractional Frequency Reuse in Long Term Evolution Network. WCNC.

[11] Afolabi., A.S., 2012. Inter-Cell Coordination for Interference Mitigation in Multi-Tier Wireless Networks. Kobe University Repository : Thesis, 993.

[12] Oh., C.Y., M.Y. Chung, H. Choo and T.J. Lee, 2011. Resource Allocation with Partitioning Criterion for Macro-Femto Overlay Cellular Networks with Fractional Frequency Reuse. Wireless Pers Communication.

[13] Rezvy., S., S. Rahman, A. Lasebae and J. Loo, 2014. Instant Channel Allocation Technique to Improve System Throughput in Joint LTE Cellular Network. 28th International Conference on Advanced Information Networking and Application Workshops, doi 10.1109.

[14] Shah., S.T., J. Gu, M.Y. Chung and S.F. Hasan, 2014. FFR based Resource Allocation Scheme for Device- to-Device Communication. IEEE 3rd Global Conference on Consumer Electronics (GCCE), 978-1-4799- 05145-1.

[15] Zhu, H. and J. Wang, 2014. Device-to-Device Communication in Cellular Networks with Fractional Frequency Reuse. IEEE ICC Wireless Communications Symposium, 978-1-4799-2003-7

[16] Rosdi, M., A.L. Yusof, M.T. Ali, N. Ya'acob, M. Ismail., M.A. Zainali, M.S. NasroAli and B.A. Bakar, 2014. Capacity Improvement For Heterogeneous LTE Network by Using Fractional Frequency Reuse Method. Control and System Graduate Research Colloquium (ICSGRC), IEEE 5th, pp: 37,42, 11-12 Aug. 2014 doi: 10.1109/ICSGRC.2014.6908692.

[17] Saquib., N., E. Hossain and D.I. Kim, 2013. Fractional Frequency Reuse For Interference Management in LTE-Advanced HetNets. IEEE Wireless Communications, 1536-1284/13.

[18] Bouras, C., G. Kavourgias, V. Kokkinos and A. Papazois, 2012. Interference Management in LTE Femtocell Systems Using Adaptive Frequency Reuse Scheme.IEEE, 978-1-4577-0580-9/12

[19] Lee., P., T. Lee, J. Jeong and J. Shin, 2010. Interference Management in LTE Femtocell System Using Fractional Frequency Reuse. ICACT, ISBN 978-89-5519-146-2.

[20] Oh., C.Y., M.Y. Chung, H. Choo and T.J. Lee, 2010. A Novel Frequency Planning for Femtocells in OFDMA-Based Cellular Networks Using Fractional Frequency Reuse. ICCSA.

Mastura Rosdi, Azita Laily Yusof, Mohd Tarmizi Ali, Norsuzila Ya'acob, Muhammad Aiman Zainali, Mohd Saufi NasroAli, Basyirah Abu Bakar

Department of Communication, Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor Malaysia

Corresponding Author: Mastura Rosdi, Department of Communication, Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor Malaysia

Table I: The Simulation Parameters
[10][11][17][18][19]

Parameter                                 Setting

Bandwidth (W)                             10MHz
Macro Radius (Rm)                         1000m
Femto Radius (Rf)                         500m
Distance between macro user and
  neighboring macro base station (D)      1732m
Number of macrocell user (Nm)             180
Number of femtocell user (Nf)             180
Outdoor path loss exponent ([alpha])      4
Indoor path loss exponent ([alpha])       6
Macro Center User Transmit Power (Pmc)    15W
Macro Edge User Transmit Power (Pme)      22W
Femto Transmit Power (Pf)                 20mW
Noise Power (No)                          -174dBm
Number of occupied sub-carrier (k)        100
Sub-carrier assignment (Bmk, Bfk)         1

Table II: Macrocell Throughput (6 Sectors)

         Throughput (Gbps)

[beta]   [alpha] = 0.1   [alpha] = 0.5   [alpha] = 1

0.1      70              5               1
0.5      145             10              2
0.9      225             15              3

Table II: Macrocell Throughput (3 Sectors)

         Throughput (Gbps)

[beta]   [alpha] = 0.1   [alpha] = 0.5   [alpha] = 1

0.1           25               5              1
0.5           120             10              2
0.9           220             15              3
COPYRIGHT 2015 American-Eurasian Network for Scientific Information
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2015 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:Long Term Evolution
Author:Rosdi, Mastura; Yusof, Azita Laily; Ali, Mohd Tarmizi; Yaacob, Norsuzila; Zainali, Muhammad Aiman; N
Publication:Advances in Environmental Biology
Article Type:Report
Date:Jun 15, 2015
Words:3492
Previous Article:Overview of acid optimization in impregnation method for sugarcane bagasse activated carbon production.
Next Article:Studies on the preparation of activated carbon sugarcane bagasse on removal of chemical oxygen demand, alkalinity and oil and grease of car wash...
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters