# Resource allocation for relay-assisted OFDMA systems using inter-cell interference coordination

- Hongtao Zhang
^{1}Email author, - Xiaoxiang Wang
^{1}, - Yang Liu
^{2}, - LZ Zheng
^{1}and - Thomas Michael Bohnert
^{3}

**2012**:156

https://doi.org/10.1186/1687-1499-2012-156

© Zhang et al; licensee Springer. 2012

**Received: **15 June 2011

**Accepted: **1 May 2012

**Published: **1 May 2012

## Abstract

This article proposes a new enhanced fractional frequency reuse (FFR) scheme to improve the system performance in multi-cell orthogonal frequency division multiple access system, which tackles the problems of frequency distribution and inter-cell interference (ICI) by jointly FFR and ICI coordination. The proposed scheme dynamically assigns subcarriers to center and edge groups depending on load conditions and the channel state information by two algorithms. The center allocation algorithm assigns subcarriers to center users from different directions. The edge allocation algorithm allows the highly loaded sectors to borrow the remaining subcarriers from center band or other sectors considering the fairness requirements of all the users. Simulation results illustrate that the proposed scheme can outperform the traditional schemes by achieving higher throughputs and better spectral efficiency especially in highly loaded cells.

## Keywords

## 1. Introduction

In the Long-Term Evolution (LTE) advanced systems, they are confronted with the limited resource for high spectral efficiency (SE) and large coverage [1]. By introducing relay station (RS) into a cellular network, we can extend the cell coverage, save the transmitting power and improve the link quality.

The major reason for performance degradation in orthogonal frequency division multiple access (OFDMA) system is the inter-cell interference (ICI). In particular, users at the cell-edge may have relatively low signal-to-interference-plus-noise ratio (SINR) because such locations suffer severely from ICI.

Several frequency distribution schemes have been suggested to improve the system data rate of an OFDMA system. Among those are soft frequency reuse (SFR) [2] and a more efficient modified SFR (MSFR) frequency allocation scheme [3]. In particular, MSFR is a better tradeoff between the frequency reuse factor and the ICI. MSFR can highly improve the throughput and the SE. However, it cannot be adapted to non-homogeneous networks.

For mitigating ICI, several methods [4–7] have been proposed to avoid interference between cells. A static ICI coordination scheme is studied in [4], which simplifies the frequency distribution and achieves good channel gain. However, it can only achieve a low SE. Based on [4], semi-static ICI coordination schemes are proposed in [5, 6] to improve the SE. The subcarriers distribution is decided by both the radio network controller and the base stations (BSs). This algorithm can coordinate interference and assign subcarriers to the BSs. However, it cannot fulfill all the users' requirements and has a reuse multiuser diversity gain. The combination of ICI coordination with cancellation or beamforming in [7] is a complementary to each other and to some extent improving the performance.

Dynamic frequency allocation (DFA) has widely been studied for multi-cell cellular networks [8–10]. Power allocation (PA) to different subcarriers can improve system data rate, so many studies have been done by joint DFA and PA in OFDMA networks. Partial isolation scheme for LTE system has been analyzed in [8]. It uses different transmission powers in different frequency bands in order to reduce interference at cell-edge. The subcarriers distribution in [9] considers the tradeoff between the ICI mitigation and SE. However, previous study [10] has indicated that the performance improvements are limited.

Fractional frequency reuse (FFR) statically divides subcarriers into two overlapping regions, which are called center band and edge band [11]. The subcarriers distribution is statically depending on the distance from the serving BS or the SINR thresholds. The edge subcarriers are further divided into three sectors and reused in the edge regions. However, FFR scheme divides users just on the basis of the distance or SINR thresholds, which reduces the link gain. The subcarriers distribution does not consider the channel state information, so it cannot fit for the rapid changes of networks.

The MSFR and static FFR schemes statically divide subcarriers into cells and do not consider the load conditions. In order to overcome the shortcomings of these two allocation schemes and improve multi-cell system performance, we propose enhanced FFR scheme (EFFR) by jointly dynamically subcarriers distribution and interference coordination between cells. To increase the link gain, there are no obvious boundaries between center and edge regions. The proposed center allocation algorithm assigns subcarriers according to the load and the channel state information to improve the system data rate. The BS schedules subcarriers to center users from different directions in different cells. The edge allocation algorithm divides subcarriers into three sectors and allows users to borrow remaining subcarriers from center group and other sectors, which can meet the fairness requirements of users.

## 2. System model

*R*and each RS is about 2/3 of cell radius away from the BS. A user equipment can communicate either directly with a BS by a one-hop link or by a two-hop link via fixed RS. The direct link between MS and BS is referred to as the access link while the link between RS and BS is referred to as the relay link. The one-hop user is mainly interfered by the neighboring BSs and the interfering sources of a two-hop user are all the RSs which use the same band with its serving RS.

### 2.1. EFFR cell architecture

*A*) and edge band (

*B, C*, and

*D*). All the cells in the grid reuse

*α*portion of subbands and the edge users use

*β*

_{ i }portion of subbands, where

*α*+ (

*β*

_{1}+

*β*

_{2}+

*β*

_{3}) = 1. Figure 2b shows the proposed cell frequency planning architecture. In this architecture, cell-edge is further partitioned into three sectors. The center frequency band (

*A*) is shared by all the center regions to serve the one-hop users. The edge band (

*D*) is used for relay links in cell 1. The edge band (

*C*) is reused by cell 2, 4, 6 and the edge band (

*B*) is reused by cell 3, 5, and 7.

The resource partitioning to center and edge group is proportional to the numbers of users based on center allocation algorithm. The edge allocation algorithm assigns subcarriers to the sectors considering both the channel state information and the load conditions. By borrowing subcarriers from center group or other sectors, the edge users can obtain a better gain than the static FFR scheme. Furthermore, the dynamically distribution can effectively avoid the ICI by scheduling subcarriers with interference coordination between sectors and also improve the edge-cell performance. In this article, we study 19-cell grids with 3 sectors per cell.

### 2.2. System model

In this OFDMA cellular network, the total number of cells is *K*, so we have *K* - 1 adjacent cells, numbered 2 to *K*, the main cell being number 1. Let *M*_{
k
} be the number of users in a cell *k*, where *k* = 1 ... *K*. Let ${M}_{k}^{c}$ denote the number of center users in a cell *k*, so the total number of users is $\mathsf{\text{M=}}{\sum}_{k=1}^{K}{M}_{k}$. In the proposed architecture, the edge group is divided into *L* sectors and ${M}_{k}^{l}$ is the number of users in the *l* th sector of a cell *k*, so ${M}_{k}={\sum}_{l=1}^{L}{M}_{k}^{l}+{M}_{k}^{c}$. The frequency band of *N* subcarriers is divided into *W* subchannels and the set of bands is denoted by *B* = {*B*_{center}, *B*_{edge}}. Let *y*_{
k
} denote the set of subcarriers borrowed from center band and ${\mathsf{\text{y}}}_{k}^{c}={B}_{k}^{c}$ be the number of remaining subcarriers borrowed from center band in a cell *k*. ${\xi}_{k}={\xi}_{k}^{l}$ denotes the number of remaining subcarriers borrowed from the *l* th sector of a cell *k*.

## 3. Frequency allocation schemes

FFR scheme offers a simple alternative to the frequency reuse problem in multicell OFDMA networks [11]. Based on the FFR, the proposed scheme aims to improve the system data rate to satisfy lower data rate requirements of all users. We also combine the ICI coordination with subcarriers distribution to increase the edge cell throughput. To achieve the optimal subcarriers distribution, we propose both center and edge allocation algorithms. Detailed description of the two algorithms is given as follows.

### 3.1. Center allocation algorithm

*A*) is then larger in cell 2 than in cell 1.

From Figure 3b, we can see the direction that BSs schedule subcarriers in different cells. The BS in cell 2 schedules available subcarriers from the center of bandwidth in both the left and the right directions. The BS in cell 1 schedules available subcarriers from the left of bandwidth while the BS in cell 3 schedules subcarriers from the right of bandwidth. By using this proposed algorithm to schedule subcarriers, the remaining subcarriers in different cells are different parts of *A* and will have a low probability of overlap. The cell-edge users can also borrow the remaining subcarriers to meet their requirements with less interference.

### 3.2. Edge allocation algorithm

The edge allocation algorithm divides the edge band into three parts for different cells and each cell is partitioned into three sectors.

*n*1 can meet the users' minimum data rate requirement and sector

*D*1 is highly loaded. The subcarriers allocation scheme can be described as follows:

- (a)
We can first schedule the remaining subcarriers of center band in cell 1. If there is no remaining subcarriers or it still cannot meet the users rate requirements, go to step (b)

- (b)
If the distribution of the subcarriers to sector

*B*1 or*C*1 is remaining, the algorithm schedules the remaining subcarriers of these sectors. - (c)
If sector

*B*1 or*C*1 is highly loaded, go to step (d). - (d)
If all the users in sector

*D*1 now still cannot meet users' data rate requirements and the sector*B*2 (or*B*3 or*C*2 or*C*3) has remaining subcarriers, the algorithm will schedule the remaining subcarriers from these sectors with a reduced power*P*2 for transmission. - (e)
If all the users in sector

*D*1 now can meet users' data rate requirements, stop. Other highly loaded sectors can also use the same methods to borrow the remaining subcarriers. The edge allocation algorithm can be effective in improving the throughput of low SINR users at the cell edge.

## 4. Performance analysis

The proposed frequency planning scheme aims to realize a high throughput and low outrage performance. In this section, we analysis the interference of MSFR, static FFR, and the proposed scheme and calculate the average SINR and throughput. The calculation results must be performed taking into account the path loss and shadowing.

### 4.1. Center allocation algorithm

#### 4.1.1. Subcarriers partition

where *ϕ*_{1} denotes the max number of center users in all cells and *ϕ*_{2} denotes the max number of edge users in cell 2, 4, 6. *ϕ*_{3} represents the max number of edge users in cell 3, 5, 7.

### 4.1.2. SINR

*i*from its own BS can be formulated as

where *b* ∈ *B*_{center} represents the center band and ${P}_{k}^{\mathsf{\text{BS}}}$ denotes the transmit power of BS *k*. ${G}_{k,i}^{b}$ is the channel gain between user *i* and its own serving BS *k* on band *b*. The channel gain takes into account the path loss, shadowing, and fast fading.

*i*in cell 1 is interfered by the surrounding 18 BSs. Then, the interference power of user

*i*received from a neighbor BS can be written as

where *k* ∈ *K* is the cell number. ${G}_{i,j}^{b}$ denotes the channel gain between user *i* and its interference BS *j* on band *b*.

*i*from its own BS1 on band

*b*can be expressed as

where *N*_{0} is the power spectrum density of AWGN, and Δ*f* is the neighboring subcarrier spacing. We assume that all users have the same noise level.

### 4.2. Edge allocation algorithm

#### 4.2.1. MSFR

*R*1 in the surrounding 18 cells. The received SINR of user

*i*in cell 1 can be expressed as

where ${P}_{1,\nu}^{{R}_{1}}$ is the transmitted power from *R* 1 in cell 1. *v* ∈ *B*_{edge} represents the edge band.

#### 4.2.2. EFFR

*i*of sector

*D*1 in cell 1 is interfered by

*R*1 in six cells: 8, 10, 12, 14, 16, and 18. The interference power of user

*i*received from a neighbor R1 can be written as

*D*1 in cell 1 cannot meet their load requirement. The algorithm will search other sectors which have remaining subcarriers. If sector

*B*1 in cell 3, 5, 7 has remaining subcarriers, then we will borrow these subcarriers. Now, the increased interference power of a user

*i*can be written as:

where $\omega \in {\xi}_{\mathsf{\text{k}}}^{B1}$ denotes the number of remaining subcarriers borrowed from sector *B* 1 of cell *k*, where *k* = 3,5,7.

*C*2 in cell 2, 4, 6 has remaining band, we will borrow these remaining subcarriers to meet the load requirement. A user

*i*may also be interfered by

*R*5 in cell 2, 4, 6. The increased interference power of a user

*i*can be written as

where $w\in {\xi}_{k}^{C1}$ represents the number of remaining subcarriers borrowed from sector *C* 1 of cell *k* (*k* = 2, 4, 6).

*i*in cell 1 can be expressed as

where *λ*_{1} is an index variable with *λ*_{1} = 1 implying that the remaining subcarriers are borrowed from sector *B* 1 and *λ*_{1} = 0 otherwise. *λ*_{2} is an index variable with *λ*_{2} = 1 implying that the remaining subcarriers are borrowed from sector *C* 1 and *λ*_{2} = 0 otherwise.

where ${M}_{k}^{l}$ is the number of the *l* th sector users in cell *k*.

#### 4.2.3. Cell throughput

*i*on subcarrier

*j*in cell

*k*can be given as

*B** is the total bandwidth of the assigned subcarriers for the

*i*th user.

*λ*is a constant which is related to the target bit error rate (BER) and can be specified as [12]

where *χ*_{
i, j
} is an assignment index variable with *χ*_{
i, j
} = 1 implying that subcarrier *j* is assigned to user *i* and *χ*_{
i, j
} = 0 otherwise.

#### 4.2.4. SE and outage probability

*R*

_{threshold}. It is formulated as

where *N* = 64, *K* is the number of cells. *M*_{
k
} denotes the number of cell-edge users.

## 5. Simulation results

Main simulation parameters

Parameter | Value |
---|---|

Carrier frequency | 2 GHz |

Channel bandwidth | 5 MHz |

Cell radius ( | 500 m |

Shadowing deviation | 8 dB |

Relay location | 2 |

Subcarrier number | 64 |

BS transmit power | 43 dBm |

Grid layout | 3-sectored hexagonal 19 cells |

| -174 dBm/Hz |

Number of users in cell-edge | 30 |

Relay number each cell | 6 |

Target BER | 10 |

## 6. Conclusions

In this article, we show an efficient frequency allocation scheme to plan the frequency allocation and reduce the ICI in OFDMA cellular system. The proposed scheme contains the optimal center and edge allocation algorithms. The center allocation algorithm partitions subcarriers into two main groups considering load conditions and the channel state information. The center subcarriers are scheduled from different directions in different cells. The users in the center group are interfered by all the neighboring 18 cells in the grid. The edge allocation algorithm assigns edge bands into three sectors and the subcarriers are reused in edge region of some cells. The highly loaded sector can borrow the remaining subcarriers from other sectors or cell-center regions, which provides high gain for the edge users. The dynamic distribution of subcarriers according to load and channel state information helps the proposed scheme to perform better than other conventional schemes. Simulation results compare the performance of these schemes and demonstrate that our proposed scheme reduces about 18% outage probability than traditional FFR scheme.

## Declarations

### Acknowledgements

This study was supported by the Fundamental Research Funds for the Central Universities (2011RC0112, 2011RC2J12), and the NSFC (60972076, 61072052).

## Authors’ Affiliations

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## Copyright

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.