2011 Wireless Advanced
Performance of Different Cell Selection Modes in 3GPP-LTE Macro-/Femtocell Scenarios Meryem Simsek, Hanguang Wu∗ , Bo Zhao, Tarik Akbudak and Andreas Czylwik University of Duisburg-Essen Bismarckstrasse 81, 47057 Duisburg, Germany Email:{simsek, bo.zhao, akbudak, czylwik}@nts.uni-due.de mimoOn GmbH ∗ Bismarckstrasse 120, 47057 Duisburg, Germany∗ Email:
[email protected]∗
Abstract—Femtocells have become an attractive approach for operators to offer extended services on their licensed UMTS/LTE spectrum. They are typically deployed indoors to improve coverage and provide high data rates. Cellular operators benefit from reduced infrastructure and operational expenses for capacity upgrades and coverage improvements. As a drawback, femtocells may cause interference to other femtocells or to the macrocellular wireless network. The interference in the system strongly depends on the type of cell selection method, which decides if a given mobile station is allowed to get access to a certain macro or femto base station (BS). In this paper various cell selection methods for femto and macro user equipments (UE) together with their benefits and drawbacks are introduced and discussed. We report on the first results obtained by using different cell selection methods in LTE macro-/femtocell deployment scenarios.
I. I NTRODUCTION Wireless data traffic has been increasing exponentially in recent years. To meet future demands for mobile broadband services, wireless operators must further improve service delivery, for example through higher data rates, shorter delays and greater capacity. These are the very targets of 3GPP radio access networks, specifically through LTE (long term evolution), which includes many of the features considered for 4G systems. Since macrocell coverage becomes expensive to serve indoor customers with large service demands, new solutions for the indoor coverage are required. Heterogeneous networks (HetNets) seem to be the answer. The objective of heterogeneous networks is to improve the overall capacity as well as to provide a cost-effective coverage extension. HetNets can consist of different cell scales which range from macro to micro, pico and femtocells. Unlike the traditional networks, in HetNets multiple types of nodes with different transmit power and RF coverage cooperate to provide seamless coverage of universal wireless access. While a homogeneous network provides coverage of urban, suburban or rural areas, small cells like femtocells with small RF coverage fit better for indoor areas. Since femtocells are low-power BSs operating in a licensed spectrum providing high-quality cellular service in residential or enterprise environments, they promise to be
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the cost-effective and budding answer for wireless operators. Femtocells have extensive auto-configuration and selfoptimization capabilities to enable simple deployment and are designed to automatically integrate themselves in an existing macrocellular network. Furthermore, connections of individual users to femtocells decrease the traffic load on the macrocellular network, thus improving the quality of the network for the remaining users, and reducing the costs for the network operator. Hence, the use of femtocells will benefit both users and operators. Nevertheless, it should be noted that femtocell technology is still in development and features of the necessary technology, that are the keys to success of femtocells, have been studied elaborately and reported in literature, i.e., the guaranteed coverage area of the cell, the auto-configuration capabilities, self-optimization competences and interference management [1] [2] [3]. While this designates that many of the major issues have been studied, there are still various areas that are left open. One such area is the wideband signal-tonoise plus interference ratio (SINR) and link loss (including pathloss, antenna gain and shadowing factor) distributions, which are important parameters when designing the characteristics of a new mobile communication system. To the best of the authors’ knowledge analysis including these parameters have not been published, yet. This paper provides an overview of possible femtocell access scenarios along with an analysis of link gain and wideband SINR characteristics as output from an LTE system level simulator. We start with the description of the used LTE femtocell system level simulator by further introducing various access scenarios. We show simulation results including the link gain, wideband SINR and average UE throughput for each of the access scenarios. We analyze the performance of different cell selection methods. The discussion of simulation results for each of these scenarios will conclude the paper. II. LTE FEMTOCELL SIMULATION ENVIRONMENT A system level simulator generally consists of different components. These can be summarized to: the deployment scenario/geometry of a wireless network including base and mobile stations, the mobility and traffic model of mobile
Fig. 1.
Macrocell environment including femtocell deployment scenarios.
stations, the link level abstraction, the radio channel, the resource allocation and the evaluation of various parameters. First aspects in the characterization of a wireless system are the environments, for which it is designed, and the usage conditions. These aspects are summarized in the deployment scenario including the cellular environment, antenna configuration, channel models, user distribution as well as mobility and traffic models. The deployment scenario has implications on the typical radio conditions and influences the expected performance. In the first step performances can be evaluated for the downlink wideband SINR and link loss distributions for comparing with known scenarios from literature, i.e., 3GPP case 1 2D [5]. The simulation area we used comprises a hexagonal cell distribution, such that each cell can be considered as a sector. In this way the macro BS serves three sectors, with each sector reusing all frequency resources. Fig. 1 depicts the macrocell environment including the femtocell deployment scenarios that have been agreed in 3GPP [5]. More details of the LTE femtocell system level simulator can be found in [6]. First, a suburban-type modeling is considered in which a various number of femtocells, represented by 12 m × 12 m rectangular houses, are randomly dropped within the macro coverage area while keeping the density of femtocells per macrocell variable. Each of the femtocells is assumed to be active, i.e., there is at least one active call in the cell. In each house the femto BS and femto UEs are randomly dropped within a specified distance of the centre point of the house. With a certain probability a femto UE might also be outdoors. Simulating this scenario represents the first approach to analyze the interference on macrocells caused by femtocells. Dense femtocell deployment modeling is simulated by using the so called dual-stripe model. In this scenario femtocell modeling is done by two stripes of 10 m × 10 m apartments separated by a street, each stripe has 2 × N apartments. In each macro cell sector, one or several femtocell blocks are randomly dropped. It is assumed that each femtocell block is not overlapping with another. A realistic case is obtained by defining a deployment ratio to determine whether an apartment
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is a femtocell or not. This scenario can be used especially to study the interference of neighbouring femtocells. An alternative simple femto cluster model is also included in the system level simulation environment. Here a single floor building with 25 apartments is considered. The apartments, which have a size of 10 m × 10 m, are placed next to each other on a 5 × 5 grid. With a certain probability it is assumed that there is a femtocell in each apartment. In all supported femtocell deployment scenarios macro UEs are assumed to be indoors similar to the 3GPP RAN1 assumptions [7]. Macro UEs are dropped uniformly and randomly throughout the sector, i.e., it is possible that some macro UEs will be dropped into the femtocell area. Various cell selection methods are examined as illustrated in Fig. 2. The lower right box in Fig. 2 shows an overview of all possible connections represented by encircled numbers. The connection of a macro UE to macro BS is described by an encirled 1, whereas an encircled 2 reflects the connectivity of a femto UE to a macro BS. The numbers 3 and 4 describe the connection of macro and femto UEs to femto BSs, respectively. Initially we define a predefined number of macro and femto UEs per macro and femto BS, respectively, and drop them before activating any access scenario within our deployment scenario. These preliminarily as macro and femto UEs defined UEs are those which are used in the notation of Fig. 2. Depending on the simulated cell selection method a UE may change his state from macro to femto or vice versa. It has to be noted, that we do not consider any signalling in the backhaul. As a baseline we use the deployment scenario in which each mobile station, no matter if it is initially dropped as a femto UE or not, is connected to the macro BS with the strongest link (case A). The femto BSs are assumed to be inactive. This scenario illustrates a macrocellular environment with indoor mobile stations. It provides a basis to express the benefits of femtocells when introducing them into a wireless network. Activating femtocells in a macro cellular environment leads to various cell selection options. The first and simplest one is the closed-access method (case B). In closed-access systems the femto BS only grants access to a particular set of authorized UEs. These mobile stations are in our case those which were initially defined as femto UEs. In other words, femto UEs remain femto UEs and get access to the femto BS that they are subscribed to and macro UEs (or nonsubscribers) remain macro UEs and select the macro BS providing the strongest link. With closed access, macro UEs can receive severe interference from nearby femtocells. Even if the received power from the femto BS is larger than that of the nearest macrocell, nonsubscribers are not allowed to connect to femtocells. In [8] [9] it was shown that in closedaccess femtocell networks macrocell UEs lying in the coverage area of a femtocell greatly suffer from high interference in the downlink and that such macrocell UEs cause destructive interference to femtocell BSs in the uplink. To reduce this interference in closed access, previous studies have considered power control, frequency assignment and a spectrum sensing
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Different cell selection methods.
approach. An alternative is to simply hand over macro UEs that cause (in the uplink) or experience (in the downlink) strong interference to the femtocell. This is known as open access (case D). In this access mode macro UEs get connected into the femtocell, which means that mobiles stations that lie within the coverage area of a femtocell are allowed to get access to the corresponding femto BS. Intuitively, this should increase the overall network capacity at the possible expense of a given femtocell owner, who must now share his femtocell resources with an unpredictable number of cellular users. Another cell selection method has also been studied: Mobile stations that were initially defined as femto UEs are not forced to get connected to femto BSs, i.e., subscribers are free in becoming nonsubscribers and getting access to macro BSs if their received power is larger. This access mode is illustrated as case C in Fig. 2. This may occur especially if a femtocell is very close to a macro BS. Since the transmit power of a macro BS is larger than that of a femto BS the received power from a macro BS at femto UE might be larger, although this user is indoor and the received power suffers from penetration losses. In this case a mobile station, which was preliminarily defined as femto UE, is allowed to become a macro UE. After introducing these access modes an upper bound is also considered. The last cell selection method we analyzed is case E in Fig. 2. In this case no matter how a UE was initially defined, each UE is free to select the BS it wants to get access to. It is expected that this case shows the best result concerning the wideband SINR and link gain distribution. It can also be expected that the average throughput of UEs with bad channel conditions/low SINR values will be improved in case E. For all the described access modes the same cell selection criterion is used. The selection criterion that a UE uses is
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the so-called long-term received power, which is the transmit power of a BS minus all the losses including path loss, antenna gain, shadowing and penetration loss. As far as the selected access mode gives the UE the permission to get access to a certain BS type, the UE always chooses the BS with the largest long-term received power. In the following section the simulation results obtained from the introduced cell selection methods are discussed in order to show the impact and benefits of introducing femtocells within a macrocellular environment using various access modes. III. S IMULATION RESULTS AND DISCUSSION For this study the suburban model is considered. For the study of the link gain and wideband SINR a scenario with 19 macrocells with three sectors and 10 femtocells per macro sector is simulated. Within each macro sector 10 macro UEs are randomly dropped. Each femtocell has a single femto UE. The maximum transmit power of a macro BS is set to 46 dBm. The maximum trasmit power of a femto BS is 20 dBm. A fixed power control algorithm is used, i.e. the maximum transmit power of each BS is distributed equally over the whole bandwidth. The downlink wideband SINR is the frequency-and timeaveraged power received from the serving BS in relation to the average interference power from all other BSs plus noise. For a UE m connected to BS i the wideband SINR ΓWB is defined as: ! prx,i(m) [dB], (1) ΓWB,m = 10 · log P ∀j6=i prx,j + σ
where prx,j is the received power from BS j and σ is the noise power. The link gain is defined as the ’average’ signal attenuation between a UE and its serving BS. It includes path loss,
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shadowing and antenna gains while the effects from fast fading are excluded. The link gain may hence be defined as the difference between the long term received power and the long term transmit power: Glink = Prx − Ptx
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In order to derive the statistical properties of the wideband SINR and link gain of macro and femto UEs, system level simulations were performed. For the suburban scenario fifty random drops were simulated for each of the described cell selection methods. It was guaranteed that for each method exactly the same random scenarios were analyzed. To consider a realistic case, we evaluate the results from the inner macrocell consisting of three sectors, while regarding the 18 surrounding macrocells just as interferers. This is a common way to take care of inter-cell interference. The cumulative distribution function (CDF) of the wideband SINR and the link gain are depicted in Fig. 3 and Fig. 4, respectively. In both figures the red curves show the simulation results obtained from the reference scenario (case A), in which we do not activate any femtocell. These curves provide a basis for the comparison of the results that we obtain from the introduced cell selection methods. The reference curve shows that with a probability of 50% (median) a UE receives a wideband SINR of more than +2.7 dB. Fig. 3 depicts that by using cell selection methods the median of the wideband SINR can be increased up to 11.6 dB. This can be interpreted as the benefit of femtocells, because activating femtocells leads to higher received powers particularly for indoor mobile stations. As a drawback of the investigated cell selection methods it can be observed that low wideband SINRs occur with a larger probability than for the reference system. This is due to the interference that is caused between macro and femto BSs. Here interference mitigation techniques, for example power control or resource allocation
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Simulation results for the link gain.
TABLE I M EAN VALUES OF WIDEBAND SINR AND LINK GAIN FOR EACH CELL SELECTION METHOD
Cell selection method Reference scenario; case A Closed access; case B Case C Open access; case D Upper bound; case E
wideband SINR [dB] 4.5 5.4 6.9 7.0 13.4
link gain [dB] -105.8 -82.2 -83.6 -78.3 -61.9
become more important [10]. This drawback will also be pointed out for the average UE throughput later on. However from TABLE I it can be seen that the expectation/mean values are larger than the one of the reference model. As expected the upper bound provides the highest mean value, because this cell selection method selects the best access for each type of mobile station. The benefits of introducing femtocells in a macrocellular network can also be seen in Fig. 4. All cell selection methods lie on the right side of the reference curve, i.e., all methods promise a higher link gain. From TABLE I it can be seen that the upper bound has on average a link gain that is around 44 dB larger than the reference method (case A). As expected the open access case (case D) provides a lower average link gain than the upper bound (case E). This is due to the fact that femto UEs are not allowed to connect to macro BSs, although they would have a better connection/larger long term received power. The case that femto UEs are able to get access to a macro BS, but macro UEs cannot connect to femto BSs shows a lower link gain than the closed access case (see TABLE I). It results from the fact that femto UEs have usually a larger distance to the macro BS than to their corresponding femto BS. A femto UE might have a lower link gain to a macro BS anyhow it will get access to that macro BS. This is because macro BSs have higher transmit power which might provide a
TABLE II S IMULATION PARAMETERS FOR AVERAGE NORMALIZED UE THROUGHPUT.
Path loss model Traffic model Scheduling algorithm Link-to-System mapping
Cell−edge UEs
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Value Hexagonal grid, 3 cells per site 50 (each snapshot: 1 ms) 20 7 10 10 macro UEs; 1-4 femto UEs 500 m 2000 MHz 3 MHz 46 dBm 20 dBm 8 dB Between macrocells: 0.5 fixed Between macro sites: 1.0 fixed see [10] Full buffer Proportional Fair Exponential Effective SINR Mapping
larger long term received power. So a worse link gain is taken into account in the statistics. In addition to the downlink wideband SINR and the link gain, we analyze the average normalized UE throughput, which is defined as the number of information bits that the user successfully received, divided by the simulation time Tsim and the bandwidth B. If a UE m has received pm packet calls, with qn,m packets for the n-th packet call, and bl,n,m bits for the l-th packet, then the average normalized throughput for user m is: Ppm Pqn,m bl,n,m Rm = n=1 l=1 [bps/Hz]. (3) Tsim · B It has to be noticed that for full buffer simulations there is one packet call with time Tsim . In TABLE II we summarize the simulation parameters, which we use in order to obtain the curves in Fig.5. In Fig. 5 the CDF of the average normalized throughput of all UEs in the system is depicted for each cell selection method. Obviously the curves of all cell selection methods are quite close to each other besides the curve of the reference scenario (case A). The difference of the curve of case A to the curves of all other access methods shows the impact of femtocells in a cellular system. Introducing femtocells will significantly improve the average normalized throughput of UEs in a system. Although all curves from case B-E are close to each other, it can be outlined that for higher rates (high average throughput) the poorest performance is obtained for the reference case. If no femtocells are deployed in the system high rates cannot be achieved. This is due to the reason that indoor UEs have bad channel conditions to macros BSs. Although the curves for the cell selection methods are close to each other, some differences can be outlined. Case D shows in higher rates the weakest performance. This is because the number of femto UEs will increase rapidly for this case. The upper bound (case E) shows a better performance than case D for higher rates, because in
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CDF of average normalized UE throughput.
case E femto UEs may get access from macro BSs. Comparing the cases B and C it can be seen that case C outperforms case B for higher rates. This is because in case C femto UEs with bad channel conditions get access to macro BS, i.e. a smaller number of remaining femto UEs get very high rates due to the small distance to their femto BSs and the reduced number of UEs in their femtocell. Case C also outperforms the upper bound (case E) for higher rates, because in case E macro UEs can get access to femtocells. This increases the number of UEs within a femtocell and consequently decreases the number of high rate femto UEs. For cell-edge UEs, which is zoomed in Fig. 5, the cell selection methods show different performances compared with high rate UEs. Case B shows for cell-edge UEs the worst performance, because macro UEs are interfered by femtocells as well as femto UEs will suffer from interference caused by macro BSs. Allowing macro UEs to get access from femtocells (case D) enhances the performance, whereas for case C even more enhancement can be achieved. For cell-edge UEs the upper bound (case E) outperforms all cell selection methods including the reference case, case A. In conclusion, for higher rates case C outperforms all methods and for cell-edge UEs case E shows the best performance. This means that for high rates/high SINR values the limiting factor is the number of UEs to be served, whereas for low SINR values the interference is the limiting factor for the performance of the UEs. Proportional fair scheduling combined with different cell selection methods shows in this case different performance in high and low SINR values. There exists a trade-off between the presented cell selection methods. IV. C ONCLUSION Using femtocells in an LTE macrocellular system is an appealing application to enhance the indoor service quality. Due to the randomness of femtocell deployments, it is crucial to understand the impacts of femtocells on the existing macro-
cellular networks. This paper offers some insights into a set of cell selection methods in a wireless network with coexisting femtocells using an LTE system level simulator. It provides a study about the impacts of deploying a large number of femtocells into a macrocellular system. As a reference system a macrocellular LTE system without femtocells is analyzed. The reference system is compared with a hybrid cellular system containing femto BSs. Different cell selection methods are applied. It was shown that all access methods, that use femtocells, provide a better wideband SINR and link gain and an improved average normalized UE throughput than the reference system. In summary, for the wideband SINR and the link gain it can be pointed out that open access has always an overall better performance than the one of closed access. The best performance is however provided by the upper bound access mode, in which each UE can feel free in selecting a BS no matter if it is a macro or a femto UE. For the average normalized UE throughput the upper bound (case E) supports mainly UEs with low SINR values, whereas for high SINR values the access mode, which gives the femto UEs the permission to get access from a macro BS, shows the best performance. R EFERENCES [1] D.-L. Prez, A. Valcarce, G. De La Roche and J. Zhang, ”OFDMA femtocells: a roadmap on interference avoidance,” IEEE Communications Magazine, Sept. 2009. [2] R.-T. Juang, P. Ting, H.-P. Lin, D.-B. Lin, ”Interference Management of femtocell in macro-cellular networks,” Wireless Telecommunications Symposium (WTS), 2010, pp. 1-4. [3] M. Yavuz, F. Meshkati, S. Nanda, A. Pokhariyal, N. Johnson, B. Raghothaman, A. Richardson, ”Interference management and performance analysis of UMTS/HSPA+ femtocells,” IEEE Communications Magazine, Sep. 2009, pp. 102-109. [4] 3GPP TS 36.201, ”3rd Generation Partnership Project; Technical Specification Group Radio Access Network; LTE Physical Layer - General Description (Release 8)”, V8.3.0 (2009-03). [5] 3GPP TR 36.814, ”3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Further advancements for E-UTRA physical layer aspects (Release 9)”, V9.0.0 (2010-03). [6] M. Simsek et al, ”An LTE-femtocell dynamic system level simulator,” in Proc. IEEE Smart Antennas (WSA), 2010 International ITG Workshop, Bremen, Germany, Feb. 2010, pp. 66-71. [7] 3GPP R1-070674, ”3rd Generation Partnership Project; Technical Specification Group Radio Access Network; LTE physical layer framework for performance verification”, (2007-02). [8] Z. Bharucha, A. Saul, G. Auer, H. Haas, ”Dynamic Resource Partitioning for Downlink Femto-to-Macro-Cell Interference Avoidance,” EURASIP Journal on Wireless Communications and Networking, vol. 2010, Article ID 143413. [9] Z. Fan, Y. Sun, ”Access and Handover Management for Femtocell Systems,” Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st, 2010, pp. 15. [10] Femto Forum, (2008, Dec.) Interference Management in UMTS Femtocells [Online]. Available: http://www.femtoforum.org/femto/Files/File/ FF UMTS-Interference Management.pdf.
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