Considerations of Small Cell Strategy in Mobile Communication Systems

Hiroyuki Otsuka, Yuki Ichimura, Yukihiro Sakamoto, and Katsunori Kikuchi Department of Information and Communications Engineering,

Kogakuin University, Tokyo, Japan

otsuka@cc.kogakuin.ac.jp

Abstract This paper presents a design method for a small cell system formed by splitting a macro cell from the perspective of user throughput performance. System level computer simulation results such as average user throughput and the cell edge user throughput performance are provided for several types of small cell. Furthermore, the possibility of the increase of system capacity using small cells is also investigated in the simulation under conditions of increased user equipment (UE) density. This strategy is important for realizing a small cell strategy for heterogeneous networks (HetNets) and relaying in future mobile communication systems such as LTE-advanced and beyond.

Keywords- Mobile communication, Small cell, HetNet, Relaying, User throughput, System capacity

I. INTRODUCTION Increased usage of mobile Internet applications such as

browsing and streaming has led to a rapid increase in the amount of data traffic on mobile communication systems. It is expected that by 2015 the volume of wireless data will exceed that of wired data. The data rates desired by end-users have also increased, and there is a need to determine how this large data capacity will be handled while meeting both user expectations and mobile operators requirements for cost-effectiveness. These should be considered when determining the future deployment of mobile networks.

Long Term Evolution (LTE) has been implemented worldwide as a 3rd-generation (3G) enhanced and/or 4th-generation (4G) technology. Furthermore, studies on LTE release 10 and beyond, which is referred to as LTE-Advanced, have been performed, and it is a candidate for International Mobile Telecommunication (IMT)-Advanced standard [1]-[4].

It is of prime importance to improve the average user throughput, the cell-edge user throughput performance and to further increase the system capacity, although the LTE link performance is already close to its theoretical limit. From a radio frequency assignment perspective, the radio frequency assigned to LTE-Advanced is expected to be much higher compared to existing mobile systems; for example, the 3.4GHz band is assigned in Japan. With higher radio frequencies, there is a great potential to increase the user throughput; however, the propagation loss may be increased with distance between the base station and user equipment (UE). For example, if the

cell size remains unchanged, the cell-edge performance must be degraded. Therefore, macro-only mobile networks will no longer be able to accommodate a higher system capacity while meeting the desired transmission quality.

Small cell concepts have attracted attention from various fields other than mobile operators [5]. Small cells are expected to facilitate a new type of mobile service that exploits the capabilities of mobile technology by interacting with existing networks such as macro-only networks. This will also provide enhanced applications for homes, enterprises, and metropolitan public areas. Several kinds of technical solutions have been discussed by the 3rd Generation Partnership Project (3GPP) to improve the average throughput, cell-edge throughput, and/or the overall system capacity on the basis of small cell technology.

The small cell approach involves deploying a denser infrastructure, which includes support by a low-power evolved Node B (eNB). One is a heterogeneous network, which is referred to as HetNet, or multi-layered network, which is used to deploy additional low-power eNB within the radius of a macro cell, in comparison with the conventional homogeneous networks [6]-[8]. Relaying is also a technical approach to realize a denser infrastructure, since it can reduce the distance between the UE and the base station such as eNB [4], [9]-[12]. This means that relaying can improve the link budget and can increase the possibility of realizing high data rates, which results in an improved cell edge performance.

Another approach is to increase the number of cells, which is called cell splitting. Examples of small cell types include femtocells, picocells, and microcells, all of which can easily provide improved cell coverage and capacity. However, there is uncertainty about the determination of the cell size on the basis of user throughput performance using system level computer simulations. So, this paper presents a system design method for cell splitting, especially from a user throughput performance perspective.

The small cell strategy and its architecture are described in Section II. In Section III, the condition of the system level computer simulations and their results are pointed out. The average user throughput and the cell edge user throughput performance are described as parameters of the cell radius, antenna height, the number of users, and so on. The possibility

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Proceedings of the 43rd European Microwave Conference

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of increasing the system capacity using small cells is also investigated in the simulation while increasing the UE density within the small cell. Finally, conclusions are summarized in Section IV.

II. SMALL CELL STRATEGIES

Figure 1 illustrates the concept of a small cell, where a macro cell is divided into several small cells. Here, small cells are controlled by low-power eNBs that operate in the licensed spectrum and are managed by mobile operators. Two scenarios are considered in the small cell strategy. First, each small cell is controlled by the macro cell. The representative example is a remote radio equipment (RRE) system, in which the RRE in each small cell is connected by a macro-eNB [7]. The macro-eNB fully controls these RREs. This approach is expected to improve the user throughput and exploit the capabilities of mobile technologies such as coordinated multipoint transmission and/or reception (CoMP) and network multiple-input multiple-output (MIMO); however, this type of small cell will not improve the system capacity.

Second, the specification of each small cell is independent of each other. Each low-power eNB in the small cell is connected directly to a core mobile network. Accordingly, this type of small cell is expected to improve both the user throughput and the system capacity compared with a traditional macro-only networks. In this case, it is very important for mobile operators to deploy the mobile network in a cost-effective manner. Likewise, mobile operators would benefit by using small cell technology to both improve the user throughput and increase system capacity.

Fig. 1. Concept of small cell.

Fig. 2. HetNet and/or relaying using small cell technology.

As mentioned in the Introduction, HetNet and relaying are also based on small cell strategy as shown in Fig. 2. A typical example is a pico-cell placed within the coverage area of a macro cell. Femto, wireless LAN access points, and pico-eNBs are candidates for the low-power wireless nodes. The purpose of HetNet is to allow UEs to access pico-cells that overlap geographical coverage areas even though the UEs are within the donor macro cell. This strategy is expected to increase the system capacity mainly in LTE-Advanced.

In HetNet as shown in Fig. 2, the UE has a capability possible to connect with the macro cell (Macro eNB), or small cell (pico eNB). For example, mobile operator can offload macro network traffic to small cells network when the traffic in the macro cell is enormously increased. Relaying is expected to improve the cell edge performance by locating the relay node (RN) as shown in Fig. 2. The RN will be introduced by wirelessly connecting to the network via an eNB (donor cell).Here, the link between the donor eNB and the RN can also be defined as the network backhaul. Accordingly UEs located at the cell edge are connected to eNB via the adjacent RN. However, typical relaying cannot increase the system capacity.

III. SIMULATION RESULTS

A. Simulation conditions In this paper, system level simulations are performed on the

basis of typical LTE/LTE-Advanced system parameters, which are provided as 3GPP standards. Two types of user throughput are evaluated, namely the average user throughput and the cell edge user throughput. The main simulation parameters are summarized in Table 1. The radio frequency is 2 GHz band, and the system bandwidth is fixed to 10 MHz.

Table 1. Main simulation parameters.

Table2 shows the simulation parameters for the different

types of small cells. These are classified into 7 types from A to G according to the cell radius, the transmitting power (TX power), and the transmitting antenna height. The cell radius of Type A is the typical value for a macro cell defined by ITU-R. The cell radius of Type B is the typical value for a micro cell.

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Type C is 80% of the cell size of Type B. Likewise, Types D, E, F, and G are 60%, 40%, 20%, and 10% of the cell size of Type B, respectively. We also assumed that the TX power and the antenna height of the low-power eNB in the small cell are marginally smaller relative to the cell radius.

In terms of the number of UEs, we discuss two scenarios. First, the number of UEs changes in accordance with the cell radius, which is considered as Case 1. In this paper, we assumed that the number of UEs is reduced relative to the cell radius. For example, the number of UEs in Type C is reduced by 80% compared with that of Type B, since the cell radius of Type C is reduced at the same rate. On the other hand, in Case 2, the number of UEs is fixed to 35 for all types. Hence, the traffic in the smaller cell has a larger density. The cell layout is common to all types, and there are 19 cell sites and 3 sectors per site, which is typical in the 3GPP system parameters.

Table 2. Simulation parameters for the different types of small cells.

B. Throughput performance for Case 1 On the basis of the simulation parameters shown in Tables

1 and 2, the throughput performance is confirmed by performing computer simulations. Figure 3 shows the average user throughput for all types (A to G) under the condition of Case 1. As shown in Fig. 3, the small cell strategy significantly improves the average user throughput when compared to the macro cell of Type A. The reason is that small cells can assign larger resource blocks to UEs within the cell. Type G slightly degrades the user throughput performance when compared to Type F, although the cell radius becomes smaller. It would appear that the degradation is caused by the interference between cells.

Figure 4 shows the cell edge user throughput performance for Types A to G under the condition of Case 1. Here, the cell edge user throughput is defined as the throughput of the UE corresponds to a low 5% of all UEs (so-called CDF 5% worst). The performance aspect is almost the same as the results of the average user throughput as seen in Fig. 3. The cell edge user throughput of Type F is almost 5 times as much as that of Type A.

From these simulation results, it is confirmed that small cells improve both the average user throughput and the cell edge user throughput for Case 1. However the interferences between cells must be within a given range, which depends on the TX power.

Fig. 3. Average user throughput performance for Case 1.

Fig. 4. Cell edge user throughput performance for Case 1.

C. Throughput performance for Case 2 Figure 5 shows the average user throughput performance

for Case 2, where the number of UEs is fixed at 35 for all Types. Unlike the results for Case 1, Types B, C, D, and E, the average user throughput is not better compared with that of the macro cell of Type A. In other words, these can maintain an average user throughput performance in the macro cell. The reason for this is that there are limited resource blocks available for assignment within the cell. Types F and G have

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worse throughput performance compared with that of Type A, because of the increased density of UEs in which the interference between cells degrades the throughput performance.

Figure 6 illustrates the comparison of the cell layout for Types A and E to show the effect of the increased system capacity. The cell coverage for Type A is shown by dashed line. Type A is divided into 36 small cells on the basis of Type E, since the cell radius of Type E is approximately 1/6 of that of Type A. Moreover, as shown in Fig. 5, the average user throughput of Type E is almost the same as that of Type A. In other words, the average user throughput has no degradation even though the cell size is smaller when the number of UEs are the same as that of the macro cell. Accordingly, it is confirmed that Type E can increase the system capacity by 36 times compared to Type A.

Fig. 5. Average user throughput performance for Case 2.

IV. CONCLUSION This paper presented a small cell system design method by

splitting the macro cell from the user throughput performance perspective. System level computer simulation results such as the average user throughput and the cell edge user throughput performance are provided for several types of small cells using the typical 3GPP standard system parameters. Furthermore, the system capacity is investigated comparing the average user throughput of several small cells to that of a single macro cell when the number of UEs is fixed within the cell for all types.

We confirmed that small cells improve both the average user throughput and the cell edge user throughput when reducing the number of UEs within the cell. Type F (cell radius = 23 m) improves the average user throughput by a factor of approximately 5 compared to Type A (cell radius = 289 m). From the system capacity points of view, it is clarified that Type E (cell radius = 46 m) can increase the system capacity by 36 times compared to Type A, while increasing the density

of UEs within the small cell. We also investigated the effect of the transmission power and the antenna height in addition to the number of UEs.

This work was supported in part by the Wireless Networking Research Group, Research Laboratories, NTT DOCOMO INC.

Fig. 6. Comparison of cell layout for Types A and E.

REFERENCES

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