Interference management with adaptive fractional frequency reuse for LTE-A femtocells networks

The Journal of China Universities of Posts and Telecommunications April 2013, 20(2): 86–91 www.sciencedirect.com/science/journal/10058885

http://jcupt.xsw.bupt.cn

Interference management with adaptive fractional frequency reuse for LTE-A femtocells networks ZHANG Wei-dong (), WANG Ying, XU Ming-yue, ZHANG Ping Wireless Technology Innovation Institute, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract This paper presents a novel interference management strategy, to adaptively choose the best fractional frequency reuse (FFR) scheme for macro and femto networks. The strategy aims to maximize the system throughput taking into account a number of system constraints. Here, the system constrains consist of the outage constraints of two-tier users and macrocell spectral efficiency requirement. The detailed procedures of our proposed strategy are: 1) A reference signal received power (RSRP) based selection algorithm is presented to adaptively select the optional FFR schemes satisfying the outage constraints. 2) Considering the macrocell spectral efficiency, the optimal FFR scheme is selected from the optional FFR schemes at MeNB side, to achieve the maximum system throughput in two-tier femtocell networks. We study the efficacy of the proposed strategy using an long term evolution advanced (LTE-A) system level simulator. Simulation results show that our proposed interference management strategy can select the best FFR scheme to maximize the system throughput, and the FFR schemes derived by using RSRP-based selection algorithm can be the effective solutions to deploy femtocells in macrocells. Keywords

femtocell, FFR, outage probability, spectral efficiency, RSRP

1 Introduction LTE-A technology is designed to further improve the data rates over air interface, and expected to enable download peak rates over 1 Gbit/s at 100 MHz bandwidth in the future [1]. The femtocell technology is a highly promising communications paradigm for LTE-A indoor environments. Deploying home evolved NodeB (HeNB) can improve indoor coverage for cellular networks [2–3]. Since femtocells reuse the macrocell spectrum, co-channel interference between femtocell and macrocell should be taken into consideration [4]. Therefore, the placement of femtocells has a critical effect on the performance of a pre-existing macrocell, and the problem of interference and its management in two-tier femtocell networks has been identified as one of the key areas for investigation [5]. To eliminate the two-tier interference, the downlink Received date: 31-07-2012 Corresponding author: ZHANG Wei-dong, E-mail: [email protected] DOI: 10.1016/S1005-8885(13)60033-3

inter-cell interference coordination (ICIC) strategies can be categorized into two types: power control and frequency reuse scheme [6–7]. However, it is difficult to use power control scheme in practical system, due to many constraints such as resource element (RE) power control dynamic range [8], and UE-specific parameters [9]. Therefore, using frequency reuse scheme is more flexible to eliminate the two-tier interference. In this paper, we introduce FFR scheme for interference management, wherein the bandwidth of the cells is partitioned into regions with different frequency reuse factor. Per-tier outage probability identified as the capacity-limiting factor, is a key figure of merit in interference-limited systems. With using different FFR schemes, many recent researches analyzed the relationship between system throughput and the outage probability. Ref. [10] investigated the throughput performance of the two-tier femtocell networks using full frequency reuse scheme, where outage constraints are taken into consideration. Ref. [11] studied the problem of spectrum allocation and proposed an orthogonal frequency portion

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(OFP) scheme to eliminate the cross-tier interference. However, the above-mentioned references [10–11] haven’t considered the performance degradation of macrocell user equipments (MUEs) when femtocells are deployed. Using FFR schemes in two-tier femtocell networks, the available resources for MUEs are partitioned, and thus the macrocell spectral efficiency needs to be analyzed. This paper defines the two-tier outage constraints and macrocell spectral efficiency requirement as system constraints. Under such constraints, to the best of our knowledge, there are few researches that investigate an effective mechanism to select an optimal FFR scheme. Considering this, we first provide a RSRP based FFR scheme selection algorithm at HeNB side to adaptively select the optional FFR schemes satisfying outage constraints. And using the proposed RSRP-based algorithm, we can then derive two new FFR schemes. Based on the optional FFR schemes, we obtain the optimal FFR scheme for two-tier femtocell networks to maximize the system throughput with macrocell spectral efficiency requirement constraints. The rest of the paper is organized as follows. Sect. 2 presents the system model of two-tier femtocell networks and formulates the optimization problem with system constraints. Sect. 3 proposes the two-tier interference management strategy. Sect. 4 introduces the simulation setups. Sect. 5 shows simulation results and Sect. 6 concludes this paper.

2 System model and problem formulation 2.1

System model

We consider the topology of the two-tier femtocell networks as suburban scenarios in LTE-A system [12–13]. A two-layer OFDMA based cellular network with 7 macrocell eNBs (MeNBs) is illustrated in Fig. 1. Ω is used to represent the set of MeNBs, and the hexagonal region of a macrocell is denoted by | H | . Moreover, the distance between adjacent | H | is denoted by RM . The macrocell network is overlaid with a femtocell network consisting of multiple femtocells denoted by Λ . Each femtocell is designed as RF × RF grid, where RF RM . The user attached to macrocell is called MUE denoted by uM , while the femtocell user is referred as HUE and denoted by uF . The MUEs are uniformly distributed over the entire region in the macrocells. This ensures that there

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is a certain probability that MUEs lie within femtocells. Users attach to the MeNB or HeNB depending on RSRP with the following key assumption:

Fig. 1 The two-tier femtocell networks for safe/victim UE classification

AS 1 Femtocells provide closed-access mode to a fixed set of subscribed indoor users within radio range who are licensed to use femtocells for privacy and security reasons [2]. 2.2 Interference scenarios for two-tier femtocell networks Resource block (RB) is defined as transmit time-frequency channel in LTE-A system, where each RB corresponds to a time-frequency unit. The set of available RBs for two-tier femtocell networks can be denoted by B ={bn ,n = 1, 2,..., N } , where N = 50 with bandwidth 10 MHz. Universal frequency reuse is considered, so that both the macrocell and femtocell utilize the entire system bandwidth. The set of available RBs B is distributed by MeNBs and HeNBs respectively. Therefore, allocating B to MUEs and HUEs leads to a certain co-channel interference among different cells. The received signal power observed by user u at is given by Ynu = Px g nu + I nu + N0 (1) where gnu denotes the channel gain of bn allocated to user u by its serving eNB. The transmit power is set to Px = PM and Px = PF when u is served by a MeNB and a HeNB, respectively. The aggregate interference I nu is composed of the macrocell and femtocell interference and given by I nu = ∑ PM g nu + ∑ PF g nj ,u (2) i∈Ωint

i∈Λint

The sets of interfering MeNBs and HeNBs are denoted

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by Ωint and Λint respectively. gnj ,u accounts for the

constraints.

channel gain between u and interfering MeNB i, while gnj ,u denotes the channel gain between u and interfering

2.3

HeNB j. Considering that two-tier femtocell networks consist of two layers (the macrocell and femtocell layers), interference on the downlink can be typically classified as follows: Cross-layer Interference Interference is caused by an eNB in one layer to the users, which belong to another layer (e.g., interference caused by a femtocell to MUEs). Co-layer Interference Interference is caused by an eNB to the users that belong to the same layer (for e.g., interference caused by a femtocell to the HUEs of other femtocells). Therefore, the co-layer and cross-layer interference for MUE uM can be respectively written as Ω co

∑P

⎫ ⎪ (3) j , uM ⎬ Ω I cr = ∑ PF g n ⎪ j∈Λint ⎭ Similarly, the co-layer and cross-layer interference for HUE uF can be respectively written as I

=

M

g

i ,uM n

i∈Ωint

Λ co

∑ Pg

⎫ ⎪ (4) i , uF ⎬ Ω I cr = ∑ PM gn ⎪ i∈Ωint ⎭ According to Refs. [14–15], the co-layer interference for the femtocells is regarded as the additive white Gaussian noise in this paper. For one MUE, all HeNBs in the system are interfers, and in addition, all MeNBs other than the serving MeNB are also interfers. Therefore, the signal to interference plus noise ratio (SINR) of MUE uM which I =

F

i ,u F n

j∈Λint

occupies the nth RB amounts to P g i ,uM γ nuM = Ω M Ωn I co + I cr + N 0

(5)

where N 0 denotes the thermal noise. Similarly, all MeNBs in the system are interferers for HUE uF . The SINR of uF which occupies the nth RB amounts to P g i ,uF γ nuF = ΛF n I cr + N0 In the following probability and the analyzed based on optimization problem

(6) section, per-tier average outage macrocell spectral efficiency are Eq. (5) and Eq. (6). And the will be formulated with the system

2.3.1

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Problem formulation Analysis of performance on two-tier users

Letting qnu denote the outage probability of u which occupies nth RB. The outage probability of u can be written as: qu = En [qnu ] = E n [Pr(γ nu < γ th )] (7) where γ th represents the uniform SINR threshold of users. A reception is assumed to be successful in case the received SINR exceeds γ th , with an outage resulting if this condition is not satisfied. As derived from Eq. (5) and Eq. (6), γ nu = γ nuM for uM , while γ nu = γ nuF for uF . Therefore, for all uM and uF served by Ωi and Λj respectively, the average outage probabilities of macrocell Ωi and femtocell Λj are obtained from Eq. (7) as qΩi = EuM [quM ] and qΛ j = EuF [quF ] . And the average outage probabilities of the macrocells and femtocells can be derived as qΩ = EΩi [qΩi ] and qΛ = EΛi [qΛi ] . Utilizing Shannon’s formula, the actual transmission throughput of macrocell and femtocell can be written as: (8) RΩ = ∑ ∑ (1 − qnuM )lb(1 + γ nuM ) uM ∈U M n∈ N uM

RΛ =

∑ ∑ (1 − q

uF n

)lb(1 + γ nuF )

(9)

uF ∈U F n∈ NuF

where U M and U F denote the set of the whole MUEs and HUEs accordingly. Therefore, the two-tier system throughput can be expressed as R = RΩ + RΛ , where NuM and NuF denote the number of available RBs for uM and uF respectively. 2.3.2

Optimization problem formulation

The system constraints defined in this paper can be expressed as ε C , ε F and RMreq , where ε C and ε F denote the macrocell and femtocell outage constraints, RMreq denotes the macrocell spectral efficiency requirement. Mathematically, the optimization expressed as: max{RΩ (qΩi ) + RΛ (qΛ j )} ⎫ s.t. qΩi <= ε C , ∀Ωi ∈ Ω ⎪ qΛ j <= ε F , ∀Λ j ∈ Λ ⎬ ⎪ RΩ / N > RMreq ⎭

problem

can

be

(10)

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In this paper, the objective of Eq. (10) is defined to satisfy the two-tier outage constraints such that the achievable system throughput is maximized while the MUEs are sufficiently protected. Therefore, the macrocell spectral efficiency requirement would be taken into consideration under the condition of satisfying the two-tier outage probability requirements. In the following, we propose the two-tier interference management strategy to satisfy Eq. (10).

3 3.1

Two-tier interference management RSRP-based selection algorithm

On the basis of RSRP from other eNBs, HeNBs can allocate/block RBs to eliminate the cross-layer interference. Since the coverage area of macrocells would be much larger than femtocells and the interference seen by MUEs only be dominated by co-layer interference, the outage probability performance on MUEs would be better than HUEs. And the macrocell and femtocell outage constraints are set to be equal ε C = ε F . Therefore, we only consider the outage constraint of femtocells as the system constraints in the heuristic algorithm. The detailed procedure of the proposed FFR scheme selection algorithm for HeNBs is in three steps. Note that in order to reduce signaling overhead involved, a set of RBs together is taken into consideration for allocation/blocking. Macro/femtocells can cooperate with the neighboring macro/femtocells through X2 interface [8]. Initialization The frequency reuse factor of macrocells is initialized. Each HeNB receives RSs from MeNBs, and arranges the MeNBs in descending order with respect to RSRP. Each HeNB identifies its least-interfering MeNB, from which the HeNB receives RSRP is the least among all interfering MeNBs. For different HeNBs, the least-interfering MeNBs may be different. And the initialized available RBs for HeNBs are the whole RBs with respect to their least-interfering MeNBs. Iteration Let σ Ω denotes the frequency reuse factor in macrocells. Since each HeNB arranges the MeNBs in descending order with respect to RSRP, the available RBs for the jth HeNB are increased with respect to the lower interference MeNB. Here, each HeNB will testify whether its outage probability is less than ε F in the iteration step γ . Only if qΛ j is less than ε F , which means ε F is satisfied for

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qΛ j , the new set of RBs is considered to be utilized by the jth HeNB. And the new available set of RBs RBΛ( rj ) is added to the set of optional FFR schemes for the jth HeNB: NΛj . Finalization: Since the frequency reuse factor σ Ωi is set to 3 or 7, the available RBs for macrocells are derived. For each HeNB, the set of the optional FFR schemes N Λ j can be obtained from the two steps above. 3.2

Selection of optimal FFR scheme

Using the RSRP-based FFR scheme selection algorithm, the optional FFR schemes for HeNBs are summarized in Table 1, in which two new FFR schemes are proposed. Here, the conventional FFR scheme represents the no interference management scenarios. And in OFP scheme, HeNBs block the RBs utilized by the highest interference MeNB. For r = 1, 2,..., 7, in case that RBΛ( rj ) is an element of N Λ j , σ Λ j represents the optional frequency reuse proportion schemes of Λj . Table 1 Differences between proposed, conventional and OFP schemes FFR scheme

σ Ωi (Ωi ∈ Ω )

σ Λ j (Λ j ∈ Λ)

Conventional OFP Proposed 1 Proposed 2

1 3 3 7

1 2/3 1/3 1/7, 2/7,…,6/7

Since the HeNBs are cooperated with the MeNBs through X2 interface, the signaling of optional FFR schemes for HeNBs are transmitted to MeNBs [8]. The selection of optimal FFR scheme for macrocells and femtocells is presented in Fig. 2.

Fig. 2 Iterative selection of optimal FFR schemes for macrocells and femtocells

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Here, we firstly reduce the available RBs for the femtocells whose resources are relatively more. And the available RBs for femtocells is selected in the above-mentioned iteration procedure step by step, to ensure the maximum system throughput for two-tier femtocell networks. Finally, the optimal FFR scheme for macrocells and femtocells can be derived.

4 System simulation setup

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deployment in the macrocell should be limited. Moreover, if ε C = ε F < 0.3 , no femtocell could be deployed in macrocell with no interference management. The outage probability performance of both femtocell and macrocell is improved by using OFP scheme. However, in case the values of ε C and ε F are lower, OFP scheme is not suitable for such case. If ε C = ε F < 0.1 , it is observed that all of the proposed FFR schemes can satisfy the outage constraints.

A two-layer OFDMA based cellular network with 7 hexagonal MeNBs (i.e., 7 macrocells) is evaluated as illustrated in Fig. 1, where RM = 1 732 m and RF = 12 m [12]. The MeNBs are arranged in grid fashion with appropriate cell-wrap to ensure elimination of edge effects. Meanwhile, all the other simulation parameters, including transmit power and antenna pattern etc., are set based on Refs. [12–13]. Full buffer traffic model are utilized wherein all users in the system are active. For more accurately description, the channel model can be classified into three types: path loss model, shadow fading model and fast fading model , which is set according to Refs. [13, 16] in our simulation. MUEs are scheduled by the channel aware proportionally fair (PF) algorithm. Since Ref. [13] defines only one HUE is served by each HeNB, the scheduler at femtocell is channel blind round-robin (RR). Both the macrocell and femtocell allocate transmission power uniformly over all their active RBs.

5 Results and experiments The following ‘Fullruse’ curves represent no interference management scenarios. We first analyze the outage performance of two-tier femtocell networks by utilizing different optional FFR schemes presented in Table 1. Assume that all HeNBs utilize the same FFR schemes, we set σ Λ j = 1/ 3 and σ Λ j = 5 / 7 for proposed scheme 1 and 2 respectively. As shown in Fig. 3, the outage probability performance of the macrocells and femtocells is presented. Compared with femtocell, macrocell is more sensitive to the two-tier interference. And deploying femtocells and macrocells with no interference management leads to the worst outage probability performance on MUEs and HUEs. Under the constraints of the two-tier outage probability requirement ε C and ε F , it is clear that the femtocell

Fig. 3

Outage probability of the macrocell

In Fig. 4, we evaluate the macrocell spectral efficiency for different FFR schemes in Table 1. Here, we assume that all HeNBs utilize the same FFR schemes. We set σ Λ j = 4 / 7 and σ Λ j = 5 / 7 for proposed scheme 2-1 and 2-2 respectively. Compared with no interference management scenarios, the macrocell spectral efficiency performance of the optional FFR schemes is worse. With the number of femtocells increasing, using the conventional and OFP schemes lead to a certain degradation on performance due to the two-tier interference. In contrast, the performance using the proposed schemes is nearly unchanged.

Fig. 4

The macrocell average spectral efficiency

In Fig. 5, the macrocell spectral efficiency is set by

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RMreq = 0.8 . This figure show the total throughput performance of our proposed interference management, where the ε C = ε F = 0.2 is set for management scheme 1 and ε C = ε F = 0.2 is set for management scheme 2, respectively. It is observed that the performance is improved significantly by using our proposed interference management. Compared with management scheme 2, the system constraints are more strictly for management scheme 1, leading to a certain performance degradation on the system throughput in two-tier femtocell networks.

Fig. 5

System throughput of the two-tier femtocell networks

To reduce the signal overheads and complexity, all HeNBs can be implemented to utilize the same FFR schemes. Fig. 5 also shows the downlink total throughput for different FFR schemes derived from Table 1, where all HeNBs utilize the same FFR schemes. Compared with no interference management scenarios, the throughput performance of the proposed scheme 2-1 is better. In case the outage constraints are strict, the proposed FFR scheme 2-1 is more effectively to be implemented. And if ε c = ε f < 0.3 , it is beneficial to utilize the proposed FFR scheme 2-2.

6 Conclusions In this paper we have presented an interference management strategy for two-tier femtocell networks under practical system constraints. The comparison results have shown the accuracy of the proposed interference management strategy. No new protocol needs to be designed and thus our strategy is easy to be implemented.

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Acknowledgements This work was supported by the National Natural Science Foundation of China (61121001), Program for New Century Excellent Talents in University (NCET-10-0242).

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(Editor: ZHANG Ying)