Capacity Improvement of Cellular System Using Fractional Frequency Reuse (FFR)

Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

Capacity Improvement of Cellular System Using Fractional Frequency Reuse (FFR) 1

Gyan Prakash Pal, 2Sadhana Pal

1

M.E. Scholar, ECE Department, NITTTR, Chandigarh, India Assistant Professor, ECE Department, VGI, Greater Noida, India

2

Abstract:- Today wireless communication is mostly used rather than wired communication, due to remote location reach ability, less fault occurrence, less time to commissioning and low cost etc. But wireless network has less frequency spectrum to cover the whole world. To improve the capacity of cellular system in a limited spectrum without major technological changes, frequency is reused in cells. But it offers interferences mostly for cell edge users. To solve the problem of spectral congestion and user capacity, fractional frequency reuse is used. This paper gives idea about different frequency reuse factors, fractional frequency reuse and super cell with sectoring to improve the capacity of cellular system.

Keywords: Frequency reuse factor, Frequency reuse ratio, Interference, Co-channel interference, Adjacent channel interference, Fractional frequency reuse, Signal-to-interference ratio

I.INTRODUCTION Enable a fix number of channels to serve an arbitrarily large number of users by reusing the channel throughout the coverage region. Effective reuse of resources can highly enhance the system capacity. Frequency reuse factor (FRF) N defines frequency reuse pattern

=

+

+

Where i and j are non-negative integers.

(1)

Figure 1: Cell arrangements with reuse factor

With a smaller frequency reuse factor (FRF), N more available bandwidth can be obtained by each cell. With the usage of FRF-1, the most user terminals (UTs) are afflicted with heavy Inter-cell interference (ICI). Especially near the cell edge. The conventional method to figure out this problem is by increasing the FRF which mitigate the ICI efficiently but decrease on available bandwidth in a cell.

The most representative approaches improving cell-edge performance while retaining spectrum efficiency by Fractional Frequency Reuse (FFR).

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Figure 2: Interference for cell edge users II. LITERATURE SURVEY The initial search procedure in WCDMA is used to identify the scrambling code used by the base station that has the lowest path loss coefficient of the received signal among all the other base stations. The timing relationship between base stations is asynchronous in W-CDMA system. So the three-step cell search algorithm is introduced in 3GPP protocols in order to fast identify the special base station.

The second step, Secondary Synchronous Channel(S-SCH) acquisition, is much critical. We have focused on the second step of the initial search procedure: frame synchronization and code-group identification. We propose partial correlation method, which extremely reduces the hardware complexity. This method minimizes the acquiring time of the scrambling code group further used for identify the scrambling code of the selected base station. [7] Wireless Sensor Network (WSN) has specific constraints and stringent requirements in contrast to traditional wired and wireless computer networks. Due to the wide potential applications of wireless sensor networks, this topic has attracted great attention. The strict energy constraints of sensor nodes result in great challenges for energy efficiency. Because of limitation in energy and selection of best route, for the purpose of increasing network remaining energy a node with most energy level will be used for transmission of data. The most part of energy in nodes is wasted on radio transmission, thus decreasing number of transferred packets in the network will result in increase in node and network lifetimes.

This paper proposes an energy-efficient organization method. The organization of wireless sensor networks is formulated for target tracking. The destination route is achieved by collaborative sensing with multi-sensor fusion.

The sensor nodes implement sensing tasks are awakened in a distributed manner. Thus, by using this we can be 172

Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

minimized energy consumption in wireless sensor network.

[8][10] The network developed after integrating the various wireless technologies is called heterogeneous network.

This growth of available broadband access technology has brought enormous challenges for operators wanting to ensure seamless mobility to its customer in heterogeneous environment. In this paper, we proposed a possible UMTSWIMAX internetworking architecture and the VHO protocol based on MIH (IEEE 802.21 standard) for UMTS and WIMAX heterogeneous network for seamless intersystem handover, services continuity with low handover latency, system throughput and packet loss. The handover procedure is based on the media independent handover function (MIHF) which is guided by MIIS server. [9] This paper presents the features of the Worldwide Interoperability for Microwave Access (WiMAX) technology and future applications of WiMAX. A discussion is given by comparing WIMAX with DSL (Digital subscriber line) & Cable and Wireless Fidelity (Wi-Fi). Several references have been included at the end of this paper for those willing to know in detail about certain specific topics. [11] [12] 5G technologies will change the way most high-bandwidth users access their phones. With 5G pushed over a VOIPenabled device, people will experience a level of call volume and data transmission never experienced before.5G technology is offering the services in Product Engg., Documentation, supporting electronic transactions (ePayments, e-transactions) etc. As the customer becomes more and more aware of the mobile phone technology, he or she will look for a decent package all together, including all the advanced features a cellular phone can have. Hence the search for new technology is always the main motive of the leading cell phone giants to out innovate their competitors. The ultimate goal of 5G is to design a real wireless world that is free from obstacles of the earlier generations. This requires an integration of networks. [16] III. INTERFERENCE Interference is the major limiting factor in the performance of cellular radio systems. Interference on voice channels causes crosstalk and on control channels, interference leads to missed and blocked calls due to errors in the digital signaling.

Two major cellular interferences are: 1. Co-channel interference 2. Adjacent channel interference 1. Co-channel Interference Frequency reuse pattern give the coverage area with several cell that use the same set of frequencies. These cells are called co-channel cells, and the interference between signals from these cells is called co-channel interference. To reduce co-channel interference, cochannel cells must be physically separated by a minimum distance to provide sufficient isolation due to propagation.

When the size of the each cell is approximately the same and the base stations transmit the same power, the cochannel interference ratio is independent of the transmitted power and becomes a function of the radius of the cell (R) and the distance between centers of the nearest co-channel cells (D). By increasing the ratio of D/R, the spatial 173

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

separation between co-channel cells relative to the coverage distance of a cell is increased. Thus interference is reduced from improved isolation of RF energy from the co-channel cell. The parameter Q, called the co-channel reuse ratio, is related to the cluster size. For a hexagonal geometry

Q

D  3N R

(2)

A small value of Q provides larger capacity since the cluster size N is small, whereas a large value of Q improves the transmission quality, due to a smaller level of co-channel interference. A trade-off must be made between these two objectives in actual cellular design.

Table 1: Co-channel reuse ratio and SIR for some value of N Cluster Size Co-channel Reuse (N) ratio (Q) I = 1, j = 1 3 3 I = 1, j = 2 7 4.58 I = 2, j = 2 12 6 Let io be the number of co-channel interfering cells. The signal-to-interference ratio (SIR) for a mobile receiver can be expressed as

=

(3)

∑

Considering only the first layer of interfering cells, if all the interfering base stations are equidistant from the desired base station and if this distance is equal to the distance D between cell centers, then equation (3) simplifies to

=

( / )

=

√

(4)

S: the desired signal power from the desired base station Ii: interference power caused by the ith interfering cochannel cell base station Signal-to-interference ratio for the worst case can be

Or

= =

(

)

(

)

(

)

(

)

(5)

(6)

2. Adjacent Channel Interference Interference resulting from signals which are adjacent in frequency to the desired signal is called adjacent channel interference. Adjacent channel interfere results from imperfect receiver filters allow nearby frequencies to leak into the pass band. Adjacent channel interference can be minimized through careful filtering and channel assignment. Keep the frequency separation between each channel in a given cell as large as possible. A channel separation greater than six is needed to bring the adjacent channel interference to an acceptable level.

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Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

 

receiving filter response signalon adjacentchannel

signalon adjacentchannel

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

Low inter-cell interference Cell edge users have fairly good connection quality

desired signal

FILTER interference

desired signal

interference

Figure 5: Frequency Reuse Factor 3 Figure 3: Adjacent channel interference

iii.

IV. POWER CONTROL FOR REDUCING INTERFERENCE In practical cellular radio and personal communication systems, the power levels transmitted by every subscriber unit are under constant control by serving base stations.

Ensure each mobile transmits the smallest power necessary to maintain a good quality link on the reverse channel Power control helps on:  long battery life 

decrease SIR



solve the near-far problem

V. IMPROVING CAPACITY IN CELLULAR SYSTEMS Methods for improving capacity in cellular systems are:  Cell Splitting: subdividing a congested cell into smaller cells. Reduce transmission power.  Sectoring: directional antennas to control the interference and frequency reuse.  Fractional frequency Reuse (FFR)

Different frequency reuse factor in one sector  Sector edge band using frequency reuse 3, allocated to the cell edge users  Sector center band using frequency reuse 1, allocated to the users in the center of the sector

Figure 6: Frequency Reuse Factor 1 and 3

iv.

VI. FRACTIONAL FREQUENCY REUSE (FFR) There are different methods to use fractional frequency reuse: i.

Frequency reuse factor 1  Same frequency is reused by each sector  High spectral efficiency  Large inter-cell interference  Cell edge users can rarely retain connection

Soft Fractional Frequency Reuse  To compensate the spectral efficiency loss due to fractional frequency reuse  The reserved band at each sector is allocated for center users with restricted power

Figure 7: Soft Fractional Frequency Reuse

v.

Dynamic Fractional Frequency Reuse  Dynamic fractional frequency reuse  The ratio of sector center and sector edge bands is adaptive to traffic load, user distribution, etc.

Figure 4: Frequency Reuse Factor 1

ii.

Frequency reuse factor 3  Same frequency is reuse every 3 sectors  Low spectral efficiency

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Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

REFERENCES

Figure 8: Dynamic Fractional Frequency Reuse

VII. SIMULATION RESULTS

Fig. 9: Comparison of dynamic and soft FFR schemes

Fig. 10: Performance improvement of cell edge users

VIII. CONCLUSION Fractional frequency reuse (FFR) scheme should be supported to improve average and cell-edge user throughput. The ratio of different frequency reuse factor and the corresponding power level are optimized or adjusted adaptively according to the traffic load and user distribution, etc., to trade of between spectral efficiency and average/cell-edge user throughput enhancement.

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[1] Theodore S Rappaport, “Wireless Communications- Principles and Practice” Prentice-Hall of India Private Limited, Second edition, 2008 [2] Vijay K. Garg, “Wireless Communications and Networking”’ Morgan Kaufmann Publishers, 2006 [3] S. W. Halpern, “Reuse partitioning in cellular systems,” 33rd IEEE Vehicular Technology Conference, 1983, vol. 33, pp. 322 – 327, May 2010.

[4] Zohreh Mohades, Vahid Tabataba Vakili, S. Mohammad Razavizadeh, Dariush Abbasi-Moghadam, “Dynamic Fractional Frequency Reuse (DFFR) with AMC and Random Access in WiMAX System”, Wireless Pers Commun, Springer Science+Business Media, LLC. 2012 [5] Andreas Dotzler, Wolfgang Utschick, Guido Dietl, “Fractional Reuse Partitioning for MIMO Networks”, IEEE Globecom 2010 proceedings.

[6] S. Shamai and B. M. Zaidel, “Enhancing the cellular downlink capacity via co-processing at the transmitting end,” IEEE VTS 53rd Vehicular Technology Conference, VTC 2001 Spring, vol. 3, pp. 1745– 1749, 2001.

[7] Mridula S. Korde, Abhay S. Gandhi, “An Improved Method for Secondary Code Synchronization in WCDMA” IJSRET Volume 1 Issue 3, pp-1-6, June 2012 [8] Anuj Kumar, Dr. Ashish Chaturvedi, “Organization of Energy Efficiency in Wireless Sensor Network”, IJSRET Volume 1 Issue 3, pp22-25, June 2012 [9] Gurpartap Singh, Garima Saini, “Development of Vertical Handover (VHO) Protocol Based on MIH (IEEE 802.21 standard) In UMTSWIMAX Heterogeneous Network”, IJSRET Volume 1 Issue 2, pp-27-34, May 2012 [10] Anuj Kumar, Neeraj Shukla, Dr. Ashish Chaturvedi, “Formulation of Energy Consumption in Wireless Sensor Network”, IJSRET Volume 1 Issue 2, pp-35-39, May 2012 [11] Gyan Prakash, Sadhana Pal, “WIMAX TECHNOLOGY AND ITS APPLICATIONS”, IJERA, Vol. 1, Issue 2, pp.327-336, July-Aug 2011 [12] Abdul Rehman, Tauheed Khan, Sunil Kumar Chaudhry, “Study of WiMAX Physical Layer under Adaptive modulation Technique using Simulink”, IJSRET Volume 1 Issue 5, pp- 5-11 August 2012 [13] Ruchin Mangla, Maninder Singh, “MIMO-Orthogonal Frequency Division Multiplexing System over Rayleigh Fading Channel with Simulink”, IJSRET Volume 1 Issue 5, pp- 53-58, August 2012 [14] Nalini Tyagi, Rahul Gupta, Ruchi Singh, “Parent Cluster Head with XML usage in Wireless Network”, IJSRET Volume 1 Issue 5, pp- 41-44, August 2012 [15] Sakshi Srivastava, Kushal Johari, “A Survey on Reputation and Trust Management in Wireless Sensor Network”, IJSRET Volume 1 Issue 5, pp- 139-149, August 2012 [16] Sapana Singh, Pratap Singh, “Key Concepts and Network Architecture for 5G Mobile Technology”, IJSRET Volume 1 Issue 5, pp165-170, August 2012

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