Macrocell Offloading Benefits in Joint Macro- and Femtocell Deployments

Holger Claussen 1, Doru Calin 2 1 Bell Laboratories, Alcatel-Lucent, Swindon, United Kingdom.

2 Bell Laboratories, Alcatel-Lucent, Murray Hill, NJ, USA.

Abstract − Femtocells are low-cost, low-power cellular base stations that are designed to provide high quality cellular service in residential or enterprise environments and operate in licensed spectrum to connect conventional, unmodified mobile terminals to a mobile operator’s network. The deployment of femtocells will reduce the number of indoor users that need to be served by the macrocellular network. Moreover, since indoor users usually have poorer radio channel conditions to the macrocell compared to outdoor users, for each indoor user that is served by a femtocell, the equivalent system resources of the macrocellular network might be able to serve more than one outdoor user, resulting in a potential macrocell offloading gain. The macrocell offloading benefits achievable in joint macro-femtocell deployments are investigated using system level simulations. It is shown that the potential increase in the number of supported users per macrocell in joint macro- and femtocell deployments depends on the macrocellular network configuration and can range from no gain for a system which is only interference limited to more than 30% in cases where noise is the limiting factor for indoor users at the macrocell edge.

Keywords − Capacity, femtocells, macrocells, offloading.

I. INTRODUCTION The drive towards more broadband from home, coupled

with increasing demands for users’ mobility support, has stimulated the research community to think about alternatives to existing WiFi solutions. The idea to have low-cost, low-power, small, in-house deployable, privately owned base stations, has led to the concept of “femtocells”. Femtocells are designed to provide high quality cellular service in residential and enterprise environments while operating in licensed spectrum. Through their integration with the more traditional access networks, femtocells present new opportunities for the wireless operators to capture precious wireline minutes and hence to tap into new sources of revenues [1, 2].

The concept of femtocells - and of small cells in general - raises new challenges for deployment and operation that include radio compatibility aspects, network-wide integration through femto based architectures, Quality of Service (QoS) of supported applications, and end-to-end networking paradigms.

While femtocells could potentially operate in separate frequency bands than the macrocellular network, the scarcity of the radio spectrum calls for co-channel deployment solutions of both femtocells and macrocells on the same frequency band. The later scenario is obviously more challenging due to the resulting mutual interference between femtocells and

macrocells. The co-existence of femtocells and macro cellular networks has been studied in [3, 5] for various deployment scenarios. The findings of this research indicate that with appropriate configuration of femtocell power levels, femtocells can co-exist with macrocells on the same frequency bands and provide service to small, limited zones, while causing just marginal interference to the macrocellular network.

The concept of femtocell auto-configuration and self-optimization, as a way to dynamically and autonomously adapt the femtocells coverage has been explored in [6]. It was shown that mobility event based coverage optimization can significantly reduce the number of handovers and idle mode mobility events in residential femtocell deployments, resulting in a significantly reduced core network signalling load.

In this paper the scope of the previous studies [2 - 6] is expanded by investigating the benefits of jointly deploying and operating a macro-cellular network with femtocells. Precisely, the goal of this paper is to evaluate an exhaustive set of operational scenarios in order to quantify the macro-offloading benefits in realistic network deployments. The achievable macro-offloading benefits constitute a key aspect that a network operator offering traditional wireless based macrocell services would like to understand, and is a key component to any business case related to the introduction of femtocells. To the best of our knowledge, these benefits have not been addressed, quantified and published before.

This paper is organized as follows: Section II provides an overview of the offloading problem addressed in this work. The investigated scenarios and the assumptions are described in Section III. Results showing the impact of offloading of indoor users on the macrocell throughput are presented for different macrocell power configurations in Section IV. The offloading benefits are quantified, and the general applicability to a broad set of macrocell sizes is also discussed. Finally, conclusions are drawn in Section V.

II. PROBLEM OVERVIEW It is well known that the radio signals are subject to various

forms of attenuations as they propagate through the radio environment. Particularly in buildings, the propagation losses are more significant and may result in poorer QoS in indoor environments compared to outdoors for an end user. This is because the in-building penetration losses can have a high impact on the overall link budget. In fact, depending on the type

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of environment, the radio planners may need to account for degradations as high as 20dB due to such losses.

Obviously, the connections which are subject to stronger attenuations are the most expensive in terms of macrocell radio resources. This can be very well the case for users calling from their residential areas due to signal propagation through walls. Having such users served through femtocells would result in macrocell resource savings; hence an improved usage of the macrocell network radio resources is expected. The savings in resources represent the macrocell offloading benefits we are investigating through this work. This is visually illustrated in Figures 1 and 2. Figure 1 represents a traditional macrocellular deployment scenario, with macrocell base stations offering service to both indoor and outdoor users. Figure 2 represents a joint macro-femtocell deployment, which allows femtocells to serve indoor users while macrocell resources are used more wisely to serve a larger set of outdoor users compared to the deployment scenario of Figure 1, hence leading to network-wide capacity enhancements.

The study conducted in this paper is tackling two fundamental questions that need to be answered in order to understand qualitatively and quantitatively the macrocell offloading benefits:

(a) Under which conditions can the macrocell capacity be increased through offloading of indoor users to femtocells?

(b) By how much can the macrocell capacity be increased by reducing the fraction of served indoor users through femtocells deployments?

III. SCENARIO AND ASSUMPTIONS In this section the considered scenario and the simulation

assumptions are discussed.

A. Scenario A scenario with 7 macrocells with 3 sectors each is

considered as illustrated in Figure 3. A total number of 5000 houses are placed at random locations with a uniform distribution in the area around the central macrocell shown as dashed square in Figure 3. Two different house types are placed with equal probability: a detached house, and a terraced house. The corresponding floor plans are shown in Figure 4.

It is assumed that the addition of femtocells does not impact the macrocell interference negatively. This is the case when femtocells are deployed on a separate frequency band. Alternatively this can also be achieved for co-channel operation where the femtocells and macrocell operate on the same frequency band as described in [2], [3]. In these studies it was shown that when the femtocells are configured appropriately, co-channel operation is possible with only minimal interference impact on the macrocellular network.

B. Simulation assumptions System level simulations were performed to derive the

resulting signal to interference and noise ratios (SINRs) for both outdoor and indoor users in the coverage area of the central macrocell represented in Figure 3. Key simulation parameters

Figure 1. Traditional macrocellular deployment.

Figure 2. Joint macro- femtocell deployment.

Figure 3. Simulated scenario.

Figure 4. Simulated house types.

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including the models for path-loss, shadow fading, and the antenna gain for the macrocell sectors are shown in Table I.

The assumed transmission losses for the explicit house model as a function of the incident angle for external and internal walls, sheetrock partitions, windows and doors are taken from the WISE simulator [7] and shown in Figure 5.

Different macrocell transmit power configurations are considered, ranging from powers that result in a signal to noise ratio (SNR) of 0dB to 30dB at the macrocell edge. Two configurations are investigated in more detail: (a) mainly interference limited, and (b) noise limited for indoor users.

For the mainly interference limited configuration, the cell range is calculated such that the received SNR outdoors at the macrocell edge is 25dB. As a result, the received signal level indoors is typically above the noise level by a significant amount, and interference is the limiting factor for the achievable throughputs.

Table I: Simulation Parameters

Path loss is modelled as 38.5+20log10(d) + Lwalls dB for short distances with a smooth transition to 28+35log10(d) + Lwalls dB in other cases, where d is the distance from the base station in metres. The loss Lwalls is calculated based on the materials and the incidence angle of the walls/doors/windows in the signal path. Shadow fading is modelled as random process with log-normal distribution (8 dB standard deviation for the macrocell signal where other houses and obstacles are implicitly modelled) The receiver noise power is modelled as 10 log10 (kT NF W) where the effective noise bandwidth W = 3.84 × 106 Hz, and kT = 1.3804 × 10−23 × 290 W/Hz. The noise figure at the UE is NF[dB] = 7 dB. The macrocell antenna gain is calculated as

dB in level gain maximum 16dB dB in level gain sidelobe 20dB

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Figure 5. Assumed transmission attenuation as a function of the cosine of the incidence angle for different materials.

For the configuration where the indoor users are noise limited, the cell range is calculated such that the received macrocell SNR outdoors at the cell edge is 10 dB. While the achievable throughputs outdoors remain interference limited, the additional wall penetration for indoor users results in a supplemental attenuation such that noise can become the limiting factor for indoor users, particularly when located close to the cell edge.

For all considered macrocell configurations, the achievable outdoor and indoor throughputs can be estimated based on the resulting SINRs using either performance results of existing receivers, or a model based on the theoretically achievable capacity. Subsequently, the offloading gain can be derived from the difference between outdoor and indoor throughputs.

Here, a theoretical approach is used to calculate the achievable throughputs. Assuming that thermal noise can be modelled as additive white Gaussian noise and interference as a zero-mean circularly symmetric complex Gaussian process whose variance equals the sum of the powers received from all interferers, the theoretically obtainable throughput can be calculated for an operation point α[dB] dB from the Shannon capacity limit [8] as

⎟⎟⎠

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SINRWC , (1)

where W is the channel bandwidth. For the investigations in this paper an operation point of α[dB] = 3 dB from the capacity limit is chosen which roughly matches the performance of well designed systems today, and W = 3.84×106 Hz.

IV. RESULTS One example of the resulting SINR distribution around the

central macrocell in the investigated scenario with 5000 randomly distributed houses (50% Type 1, 50% Type 2) is shown in Figure 6, for clarity, without the additional effects of shadow fading. Note however that the shadow effects are taken into account for all results described below. It is shown that the SINRs are highest close to the macrocell in direction of the maximum gain of the antenna in each sector, and then falls off towards the cell edges. The walls of the simulated houses (Figure 4) have an impact on the indoor SINR since they attenuate the macrocell signals. The average shadowing effects for the outdoor locations are taken into account in the path-loss model. The deployment of femtocells reduces the number of indoor users that have to be served by the macrocells, which has an impact on the achievable macrocell capacity. The following results show these effects for different macrocell configurations in the considered area.

Figure 7 illustrates the CDFs of the achievable total macrocell throughput for both indoor and outdoor locations for a mainly interference limited system where the macrocell power is set to achieve an average signal to noise ratio of 25 dB at the cell edge. It is shown that in the interference limited case, the throughput for indoor users is roughly equivalent to the throughput for outdoor users. The results show a slightly higher mean throughput for the indoor users which results from the shading effects of walls which can result in improved SINRs

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Figure 6. Resulting SINR map in dB with 5000 randomly distributed

houses, for clarity, shown without shadow fading.

Figure 7. CDFs of achievable macrocell throughputs in an

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Figure 8. CDFs of achievable macrocell throughputs in a mainly

noise limited scenario (10 dB macrocell SNR at cell edge)

due to the asymmetric wall attenuations. As a result, reducing the fraction of indoor users by deploying femtocells would not increase the capacity or number of users supported by the macrocell in such interference limited scenarios.

Figure 8 shows the CDFs of the achievable total macrocell throughput for both indoor and outdoor locations for a more noise limited system where the macrocell power is set to achieve an average signal to noise ratio of 10 dB at the cell edge. Here, it is shown that the achievable outdoor throughputs are significantly higher than the achievable indoor throughputs, since the signal for indoor users is attenuated so much by the walls that the noise power becomes the major contribution in the SINR. As a result, reducing the fraction of indoor users by deploying femtocells would increase the capacity or the number of users supported by the macrocellular network in such mainly noise limited scenarios.

In addition to the two cases shown in Figures 7 and 8, the achievable mean throughputs for a range of macrocell power configurations that result in SNRs between 0dB and 30dB at the macrocell edge were investigated. The resulting mean throughputs are shown in Figure 9. Increasing the macrocell power results in an increasing outdoor throughput up to the point where the edge SNR reaches approximately 10dB. For higher edge SNRs the mean throughput does not increase significantly anymore since interference becomes the limiting factor for outdoor users. For indoor users, increasing the macrocell power to a point where the edge SNR reaches approximately 25dB results in increases in the mean indoor throughput as well. Consequently, higher macrocell powers do not bring much benefit in such deployment scenarios since interference becomes the limiting factor for indoor users. In cases where interference is limiting both outdoor and indoor throughputs (e.g. for edge SNR of 30dB), it is shown that the indoor throughputs can even exceed the outdoor throughputs due to the asymmetric shielding effects of the walls for different base stations, which can result in increased indoor SINRs.

Based on the mean throughputs, the achievable macrocell offloading gain - defined as the equivalent number of outdoor users that can be supported by the macrocell network for each offloaded indoor user to femtocells - can be determined, as illustrated in Figure 10. It is shown that the offloading gain is highest when the macrocell is noise limited indoors, and reduces gradually with increasing macrocell power transmission levels (when indoor users become interference limited). The offloading gain disappears completely, or even becomes smaller than 1 for purely interference limited scenarios, where the macrocell power is so high that the edge SNR exceeds 25dB in the considered scenario.

In real deployments such an interference limited scenario could be encountered for green field deployments where a macrocellular network is planned from scratch with the aim to provide excellent indoor coverage.

One example of a more noise limited scenario in real deployments would be the case where existing cell sites (e.g. those in use for GSM) are re-used for an access technology operating at a higher frequency band (e.g. UMTS). Due to the higher resulting path-loss to indoor locations, the noise may

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Figure 9. Mean macrocell throughput for different macrocell power configurations (0 to 30 dB macrocell SNR at cell edge)

Figure 10. Achievable macrocell offload capacity gain for different macrocell power configurations.

become the limiting factor in some indoor locations compared to interference.

So far, this study was based on the assumption of one specific cell radius, so the question arises if the results also apply to cellular systems with other dimensions. Since all results are based on the resulting SINR distributions it can be argued that if the SINR distributions are independent of the cell range, the results would remain valid. Figure 11 shows the CDFs of SINRs for different cell ranges between 100 metres and 10 kilometres. The results show that the SINR distribution is independent of the cell radius, so it can be concluded that the result in this paper can be generalized to other macrocell ranges.

V. CONCLUSIONS In this paper the macrocell offloading benefits resulting

from femtocell deployments were investigated. It was demonstrated that the macrocell offloading capacity gain - defined as the equivalent number of outdoor users that can be supported by the macrocell network for each offloaded indoor user to femtocells - depends on the macrocell transmit power configuration. In mainly noise limited systems, where the average edge SNR of the macrocell is 10 dB, the average capacity gain is 30% and rises to over 100% for edge SNRs of 0dB. This range would for example correspond to new deployments (e.g. UMTS) where existing cell sites that were selected for a technology operating at a lower frequency band (e.g. GSM) are reused. In mainly interference limited scenarios, where the average edge SNR exceeds 25dB, the capacity gain disappears completely, or even becomes negative. This would correspond to green field deployments where the number of cells and the cell sites are optimized for indoor coverage. It was shown that the results can be generalized to other macrocell ranges since the macrocell range does not affect the SINR distribution for configurations that lead to the same edge SNR target.

REFERENCES [1] Chris Edwards, “The future is femto,” IET Engineering & Technology,

vol.3. no.15, 70-73, 2008. [2] H. Claussen, L. T. W. Ho, L. G. Samuel, “An overview of the femtocell

concept,” Bell Labs Technical Journal, vol.13. no.1, pp 221-246, 2008. [3] H. Claussen, “Performance of macro- and co-channel femtocells in a

hierarchical cell structure,” in Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2007.

[4] H. Claussen, L.T.W. Ho, L.G. Samuel, “Financial Analysis of a Pico-cellular Home Network Deployment,” in Proc. IEEE International Conference on Communications (ICC 2007), 24–28 June 2007.

[5] L. T. W. Ho, H. Claussen, “Effects of user-deployed, co-channel femtocells on the call drop probability in a residential scenario,” in Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2007.

[6] H. Claussen, L. T. W. Ho, L. G. Samuel, “Self-optimization of coverage for femtocell deployments,” in Proc. Wireless Telecommunications Symposium (WTS), 2008.

[7] S. J. Fortune, D. Gay, B. Kernighan, O. Landron, R. Valenzuela, and M. Wright, “WISE Design of Indoor Wireless Systems”, IEEE Computational Sci. and Engineering, vol.2, no. 1, pp. 58–68, 1995.

[8] C. E. Shannon, “A mathematical theory of communication,” Bell System Technical Journal, vol. 27, pp. 379–423, 623–656, July, October, 1948.

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