- Research Article
- Open Access
QoS-Guaranteed Power Control Mechanism Based on the Frame Utilization for Femtocells
© Pavel Mach and Zdenek Becvar. 2011
- Received: 3 September 2010
- Accepted: 18 February 2011
- Published: 13 March 2011
The paper focuses on a power control mechanism and proposes a novel approach for dynamic adaptation of femtocells' transmitting power. The basic idea is to adapt the transmitting power of femtocells according to current traffic load and signal quality between user equipments and the femtocell in order to fully utilize radio resources allocated to the femtocell. The advantage of the proposed scheme is in provisioning of high quality of service level to the femtocell users, while interference to users attached to macrobase station is minimized. The paper proposes the power adaptation algorithm and evaluates its performance in terms of mobility events, achieved throughput, and FAPs transmitting power. Performed simulations show that the proposed scheme can significantly reduce the number of mobility events caused by passerby users and thus to minimize signaling overhead generated in the network. In addition, our proposal enhances overall throughput for most of the investigated scenarios in comparison to other power control schemes.
- Traffic Load
- User Equipment
- OFDM Symbol
- Mobility Event
- Power Control Scheme
In the recent years, the demands for high data rates have been driven by introduction of new wideband services for mobile users. The contemporary studies demonstrate that more than 50% of voice calls and more than 70% of data traffic originates from indoors . The main problem of current wireless networks working in the higher-frequency bands (above 1 GHz) such as 3G or 4G networks is a poor indoor coverage. Hence, to support high-quality multimedia services in that kind of scenarios is a challenge. The promising way for guaranteeing high data transmission for indoor users is represented by femtocell access points (FAPs). The FAPs are portable low cost base station deployed, for example, in the household or office. The connection of the FAPs with a cellular network is ensured over a broadband connection such as DSL, cable modem, fiber optic, or wireless link.
The FAPs can operate in three different access control modes: closed access, open access, and hybrid access [2, 3]. A closed access mode corresponds to the case when only small group of users are allowed to connect to the FAPs. The users, who are permitted to access the FAPs, are determined according to a closed subscriber group (CSG) list. This option is suitable for FAPs owners who do not wish to share their backhaul link for which they have to pay. On the other hand, an open access mode is allowing all passersby users to access the FAPs. The FAPs operating in open access can help to alleviate traffic load of macrobase stations (MBS) by serving some of its users. The last access mode, that is, hybrid access mode, is a sort of compromise between the closed and open access. A certain part of the FAPs bandwidth is always dedicated for users belonging to the CSG, while the rest of the bandwidth can be utilized by all passing users.
Various options of frequency allocation are considered for the FAPs and MBS . First, separate frequency for the MBS and FAPs can be utilized. Consequently, no interference between MBS and FAPs occurs. On the other hand, this option is not always possible, as free radio spectrum may not be available for the FAPs. More than that, this approach significantly reduces the spectrum efficiency. The second option of the frequency allocation is to use the same frequency for both MBS and FAPs. The benefit of this approach is high spectral efficiency, since all FAPs fully reuse frequency spectrum of the MBS. The evident drawback is the increase of cochannel interference between the MBS and FAPs. The last option of the frequency allocation partially shares specific amount of the bandwidth between the MBS and FAPs. The rest of the bandwidth is solely dedicated to the MBS. Thus, users attached to the MBS close to the FAPs can use different frequency spectrum than the interfering FAPs.
Many technical studies have been already performed to analyze the advantages of femtocells implemented in the network (see, e.g., [5, 6]). Technical challenges, which must be solved to fully utilize femtocells potential, are described in . One of the most important problems regarding femtocells is how to avoid the harmful interference either to the MBS or to the neighbor FAPs if the same spectrum is utilized by the MBS and FAPs. The effective way of interference avoidance is an appropriate power control mechanism allowing adaptation of FAPs transmitting power.
To that end, the aim of this paper is to propose a novel power control mechanism. The idea is to decrease transmitting power of the FAPs to fully utilize its frame while requirements of all users attached to the FAPs are ensured; that is, QoS (quality of service) requirements of the users are met. The advantage of this approach is that at light and medium traffic load, the power of FAPs can be significantly reduced. Consequently, the probability of signal leakage out of the residential house is decreased as well. This fact ensures either mitigation of harmful interference to the adjacent FAPs or to MBS's users (in case of closed access) or a reduction of undesired mobility events (in case of open access).
The principle of the proposed scheme and performed simulations are described for LTE-A system according to release 10 . However, the general principle may be used in other contemporary technologies such as WiMAX or former LTE versions. In LTE-A technology, the data can be transmitted either in TDD or FDD manner. Without loss of generality, the rest of the paper assumes only FDD frame, since TDD frame has only different structure. In addition, the paper assumes only FAPs with open access. Nonetheless, the whole idea can be applied to FAPs with closed access as well.
The rest of the paper is organized as follows. Section 2 discusses the related works concerning the power control in femtocell environment. The next section provides description of the proposed power control technique. It is logically divided into five subsections. The assessment of parameters influencing frame utilization is delivered in the first subsection. The second subsection analyses the dependence of frame utilization on FAPs transmitting power. A relationship between the probability of generated mobility event and FAPs transmitting power is contemplated in the third subsection. The fourth subsection is dedicated to the description of the proposed power control algorithm. The requirements of the proposed mechanism on existing networks are contemplated in the last subsection. The system model and simulation results are presented in the two following sections. The last section gives our conclusions.
The power control mechanism may be implemented either in an uplink or in a downlink direction. In the former case, a transmission power of user equipment (UE) is adapted. In the latter case, an adaptation of FAPs transmission power is accomplished. The power control in uplink is addressed, for example, in [9–11]. Regarding the power control in downlink, which is the focus of the paper, several mechanisms have been already proposed. Generally, two different approaches are followed regarding the downlink power control in femtocell's environment. According to the first approach, the main aim is to completely cover a specific area of certain radius (e.g., to ensure the whole house coverage). The advantage is that users are always able to connect to the FAPs when inside the building. Nevertheless, the signal leakage out of the building boundaries may be significant. The primary goal of the second approach is to set the transmitting power of FAPs to minimize interference to passerby users or neighboring FAPs. The disadvantage of this approach is that the coverage of whole building is not always assured, especially if the FAPs are positioned close to the building boundary.
In [12, 13], authors suggest autoconfiguration schemes (representatives of the first approach) and self-optimization schemes (representatives of the second approach), respectively. While the autoconfiguration schemes provide an initial power setting of the FAPs, the self-optimization schemes try to optimize the FAPs transmitting power during a normal operation. Authors distinguish three autoconfiguration schemes: (i) fixed power, (ii) distance based, and (iii) measurement based. When fixed power configuration scheme is utilized, the transmitting power is set to fixed value (authors consider −10 dBm). Disadvantage of this method is that the FAPs coverage strongly depends on the distance from the MBS. This drawback is eliminated by the distance or measurement-based approaches. In these cases, the FAPs power is configured so that the received signal from the strongest macrocell and the FAPs are the same at a defined target cell radius. Usually, the target cell radius corresponds to the maximum distance from the FAPs where a UE attaches to the FAPs rather than to the MBS. The performance of autoconfiguration schemes is analyzed in terms of the number of mobility events (i.e., number of the handovers or their initiations) for the different FAPs positions within a building. Although the distance and measurement-based methods outperform simple fixed power autoconfiguration scheme, the number of registered mobility events is still high and unsatisfactory (especially for the scenario if the FAPs are positioned close to the house boundary). Further improvement is achieved by the introduction of the self-optimization schemes.
Three self-optimization schemes are proposed in [12, 13]. Generally, all self-optimization schemes aim to minimize the number of mobility events based on their measurement. Consequently, the FAPs must be able to collect statistical information regarding the mobility events. The first scheme forces the adaptation of FAPs power only according to the mobility events generated by passing users. The advantage is that the number of outdoor mobility events is significantly minimized. Nevertheless, the number of indoor mobility events may be high. This disadvantage is eliminated by the second proposed self-optimization scheme when the FAPs tries to minimize all mobility events. The last scheme exhaustively searches over all possible power settings and the power of FAPs, during which the smallest number of mobility events occurred, is regarded as the optimum. However, as this approach is not really practical, it serves only as a benchmark. The numerical results demonstrate that self-optimization schemes noticeably outperform all autoconfiguration methods. As already stated, the main disadvantage of all self-optimization schemes proposed in [12, 13] is that UEs inside the house are not always able to attach to the FAPs as the full house coverage is not ensured.
In , the authors additionally contemplate another autoconfiguration scheme taking activity/inactivity of users into consideration. If no users of the FAPs are currently active (no voice or data are transmitted), the transmitting power of FAPs are decreased by 10 dB. At the same time, the FAPs user's idle mode cell reselection threshold is decreased by 10 dB to guarantee that the UEs remain connected to the FAPs. However, even with this improvement, the autoconfiguration scheme is outperformed by the above-mentioned self-optimization schemes.
Two more power schemes, which represent the second approach, are introduced in [15, 16]. In , the authors propose an adaptive coverage adjustment (ACA) algorithm. The aim of the paper is similar to the self-optimization schemes proposed in [12, 13], that is, to minimize mobility events and to reduce signal leakage. If the UE currently attached to the MBS is in close vicinity of a FAPs, the FAPs itself iteratively decreases its transmit power as long as the passing UE is in FAPs range. After specific time period when the UE moves away from the FAPs coverage, the FAPs increases power to the initial value. Nevertheless, this scheme is not able to fully mitigate the redundant handovers, since the decrease of power is done after reception of handover request at the side of FAPs. In , self-optimization scheme allowing the FAPs to adaptively adjust transmitting power is presented. The proposed scheme is composed of two steps. In the first step, the self-configuration of the FAPs transmitting power is accomplished. In the second step, the adaptation of current transmitting power according to radio environments obtained by measurements is performed. The aim of the authors is like as described in [12, 13], that is, to minimize interference caused by the FAPs to passersby users while to achieve sufficient indoor coverage. However, the authors do not use the number of generated mobility events but consider leakage of the FAPs signal for its power adaptation.
Other two studies proposed to control FAPs transmission power in dependence on current traffic load of the FAPs. In , the authors contemplate the possibility to adapt transmitting power of FAPs based on traffic density. The proposed scheme suggests observing the length of queue at the FAPs. If the queue is filled at a certain level given by proposed parameters, the FAPs transmits either at full level (at high traffic density) or at half of its full power (at low traffic density). From the results, it can be observed that transmission power can be decreased. Nevertheless, the paper does not show how the proposed scheme performs in comparison to existing power control schemes in terms of interference reduction or throughput. The second study described in  proposes a similar idea as defined in . The aim is to adapt the transmitting power of femtocells according to current traffic load and signal quality between mobile stations and femtocell in order to fully utilize data frame. The study provides only simple analytical evaluations in order to demonstrate the effect of proposed principle on FAPs transmitting power.
The work in this paper is based on the idea introduced in . In comparison to , the paper proposes a whole new algorithm enabling FAPs to adapt their transmitting power and contemplates its applicability to existing LTE networks. In addition, extensive simulations emulating real scenarios with FAPs are undergone. The aim of the proposed scheme is to find the optimal tradeoff between both of the above-mentioned approaches by elimination of their weaknesses. On one hand, our objective is to minimize the number of undesired mobility events in a similar way as the proposals based on the second-approach aims. However, at the same time, the goal is to keep the same QoS level to the FAPs users as in case of the first approach.
Actual frame utilization must be known at the side of FAPs to estimate current appropriate transmitting power of FAPs ( ). According to , the LTE-A frame is composed of 20 slots with 0.5 ms duration in a time domain. Every two slots create one subframe, and ten subframes form one LTE-A frame. Furthermore, one slot includes seven OFDM symbols (or six OFDM symbols if extended cyclic prefix is considered). Depending on channel bandwidth, the frame structure could be decomposed in a frequency domain into certain number of subcarriers, and every twelve subcarriers form one resource block. The resource block consists of the so-called resource elements representing one subcarrier in the frequency domain and one OFDM symbol in the time domain.
For the purpose of our proposed power control scheme, it is necessary to analyze aspects influencing current frame utilization and relationship between FAPs transmitting power and its frame utilization. These issues are addressed in the next two subsections.
3.1. Assessment of Parameters Influencing Frame Utilization
where and represent the number of resource elements appointed to control information and data, respectively. Thus, as long as , the frame is not fully used and some resources are still free. The number of resource elements carrying overhead depends on system configuration and usually varies between 15% and 30% of (see ).
where is the number of users attached to the FAPs and is the amount of data send to user during frame . In general, the number of resource elements used for data transmission is proportional to the amount of generated data in the downlink direction.
Transmission efficiency depending on CINR .
Transmission efficiency Γ
where is the transmitting power of FAPs, corresponds to the signal attenuation between a transmitter and a receiver, and stands for the noise plus interference.
3.2. Impact of FAPs Transmitting Power on Frame Utilization
3.3. Impact of FAPs Transmitting Power on Mobility Events
where and are pilot's signal levels received from a target station (station to which the UE is supposed to be connected after handover), and a serving station (station to which the UE is attached before handover), respectively, and represents hysteresis margin for avoiding redundant handovers. Furthermore, in order to prevent any other unnecessary handovers, its initiation is postponed by handover delay timer .
If we consider handover from the MBS to FAPs, that is, is the transmitting power of the MBS and corresponds to transmitting power of FAPs, it is apparent that a probability of handover decreases with lowering of FAPs transmitting power. Since the goal of the proposed power control is to fully utilize the frame by decreasing of FAPs transmitting power, the overall number of performed handovers may be potentially minimized as proved by simulation results in Section 5.
3.4. Power Adaptation Algorithm
Transmitting power of the FAPs
Power adaptation step
Minimal transmitting power of the FAPs
Maximal transmitting power of the FAPs
Minimal CINR when the UE is still able to connect to the FAPs
CINR when the data between the FAPs and the UE are sent with the highest MCS
Current frame utilization
Target frame utilization
The set of UEs' average CINR of the FAPs ,
The set of UEs' transmission efficiencies of the FAPs m,
Power adaptation interval
Fade margin to cope with fading effects
The Case I occurs when all UEs connected to the FAPs are in inactive state ( ). In order to minimize potential interference to passerby users, the transmitting power of the FAPs are automatically set to its minimal value . To prevent the handover of UEs in idle state to other station with higher transmitting power (either to MBS or to adjacent FAPs), the handover threshold is decreased accordingly.
The FAPs power is incremented only by when . In this situation, the generated data can be still transmitted and adjusting of the FAPs power by is sufficient. Before increase of the FAPs transmitting power is accomplished, two conditions must be satisfied. The first condition is the same in the previous case; that is, there exists . The second condition is that the FAPs transmitting power incremented by a power adaptation step does not exceed maximal allowed value .
So far, we have assumed the power adaptation is done in such manner that all UEs attached to the FAPs would experience satisfying signal quality regardless of their activity/inactivity. Nevertheless, if for example, only one UE in close distance to FAPs are active while the rest of attached UEs are inactive, it is profitable to adapt transmitting power to guarantee good channel quality only between the active UE and the FAPs. In case when inactive UE changes its status to active, the FAPs can automatically increase transmitting power to cover this newly active UE. The merits of both proposed algorithm options are analyzed in Section 5.
The optimal value of is found experimentally by means of performed simulations addressed in Section 5. In the proposed algorithm, it is assumed that the adaptation step has constant size. However, the adaptive size of can be utilized for our purposes. Similarly, as in case of , this issue is an item for further future research.
3.5. Requirements Imposed by Proposed Mechanism
The advantage of our proposed power control mechanism is that it needs no additional hardware modifications to the MBS, FAPs, or UE. The only requirement is that the FAPs are capable to adjust its transmitting power by optimized adaptation step . Nevertheless, this functionality is required by all existing power schemes. Regarding software changes, the FAPs firmware needs to be updated to support proposed power adaptation algorithm. The algorithm computational complexity is low, since no difficult calculations are done; only several simple conditions are evaluated during every power adaptation cycle . As a consequence, the FAPs have to collect information regarding the channel quality of all its users in DL every adaptation cycle as well. Since in LTE, a periodic CINR measurement and its reporting can be scheduled from 2 ms to 160 ms , we consider values of varying between 10 ms to 80 ms. Thus, the proposal does not unnecessarily increase reporting overhead or FAPs processing load.
In order to implement the proposed algorithm to femtocell environments, two requirements need to be fulfilled: (i) the FAPs has to be aware of UEs' individual CINR and (ii) the FAPs has to able to evaluate current frame utilization in downlink direction. As mentioned earlier, the measurement of channel quality and its reporting to the FAPs are inherent procedure necessary for all wireless mobile technologies. Consequently, the FAPs can adjust the transmitting power as described in previous subsection. In addition, the other advantage of the proposed mechanism is that it does not increase the signaling overhead due to reporting of CINR as the reporting has to be done independently on the proposed power scheme. The second requirement is also satisfied, since the FAPs are continuously aware of downlink traffic and allocates radio resources to UEs. Thus, the FAPs are able to easily determine current frame utilization essential for proposed power adaptation scheme.
Frequency band f (GHz)
MBS channel bandwidth BW (MHz)
FAPs channel bandwidth BW (MHz)
3; 5; 10
Frame duration (ms)
Number of OFDM symbols per slot (−)
Max. FAPs transmit power (dBm)
Min. FAPs transmit power (dBm)
MBS transmit power (dBm)
Target frame utilization (−)
No. of FAPs
Loss of internal wall/external wall/window (dB)
Fade margin (dB)
Hysteresis margin (dB)
Length of simulation (s)
Figure 7 further shows the position of FAPs considered in the performed simulation. Several FAPs positions are chosen along the arrow in Figure 7 within the simulation. The position of FAPs directly next to the window represents the worst case scenario (highest number of undesired mobility event is generated), the position approximately in the middle of the household corresponds to the best scenario as the signal from the FAPs are highly attenuated by the walls.
Since the performance of proposed mechanism strongly depends on the amount of generated traffic by indoor users, two traffic model types based on  are defined. First traffic model type is an FTP model representing data transmission scenario. More than that, two types of the FTP model are considered (denoted in simulation as an FTP I and an FTP II). While the FTP I generates roughly 380 kb/s at an average per the simulation (corresponding to the light traffic case), the FTP II generates roughly 4.4 Mb/s at an average (corresponding to the heavy traffic case). The second type of model is a VoIP model representing voice transmission. Two path loss models are assumed. To simulate path loss in indoor environment, ITU-RP.1238 model is implemented. The path loss model for outdoor environment is based on Okumura Hata empirical model. Both path loss models are chosen, since these are widely used in evaluation of femtocell concept . More detailed parameters of both models can be found also in .
The performance of the proposed mechanism is demonstrated through the number of mobility events generated per whole simulation depending on the position of the FAPs within the household. The mobility event is triggered if pilot signal received from new cell is higher by 4 dB than from serving cell for a time of 500 ms (the values are taken from ). The simulation monitors both outdoor and indoor mobility events. Moreover, the throughput and level of transmitting power for selected scenarios is analyzed.
The worst performance is observed by ACS-MB, where significant number of the mobility events is generated. Especially if the FAPs are close to the house border, the passersby UEs are forced to perform the handover from the MBS or adjacent FAPs very often. Although the situation is improved by eACS-MB, which reduces the number of mobility events approximately to 50%, the results are still unsatisfactory. The overall number of mobility events decreases as the FAPs are placed closer to the house centre. The sharp drop of the mobility events between 3.5 m and 4 m is due to two reasons. The first reason is that the FAPs are removed from living room to the next room (see Figure 7). Thus, the FAPs power leakage out of house is reduced by attenuation of internal wall. The second reason is that the FAPs are transmitting at such power level to cover whole house, and the most problematic locality in our scenario is to cover a toilet positioned furthest from the FAPs. Thus, when the FAPs are moved from living room to the next room, the power of the FAPs are reduced approximately by 5 dB.
Percentual coverage of UEs by the FAPs.
FAPs position (m)
FAPs coverage (%)
The performance of the proposed mechanism is dependent on the selection of the appropriate adaptation step . If the adaptation step is set to the default value of 0.1 dB and PS I is considered, the number of mobility events is decreased roughly to 50% when compared to ACS-MB. The obtained results are only slightly better than in case of eACS-MB. Further minor improvement is achieved by utilizing of PS II. In order to improve the results obtained by PS, the optimal value for adaptation power step is necessary to be found as described in Section 3.3. The performance of PS II is also illustrated in Figure 8 for different values of . The results indicate that the number of mobility events is noticeably decreased if appropriate value for corresponding to 2 dB is selected (no improvement for values higher than 2 dB was observed in simulations). The important outcome is that due to optimization process, the results are even better than in case of SOS for FAPs position greater than 2 m from the house's edge.
If the PS scheme is used, the FAPs are always able to serve the same amount of data as in case of ACS-MB or eACS-MB. This is not valid for SOS method, as indoor users are not attached to the FAPs all the time. Consequently, the MBS has to serve these users which degrade the overall throughput. This is notable especially for heavy traffic load when FTP II together with VoIP is used for indoor users. Figure 10 further indicates that simple ACS-MB significantly degrades performance of outdoor users. Nevertheless, if the FAPs are close to the middle of house (FAPs distance from the house boundary is at least 6 m in our scenario), the results are comparable to SOS scheme as the FAPs transmitting power is the same for both methods. Significantly better results than those reached by ACS-MB are observed for eACS-MB when the results are even better than for SOS scheme. Nonetheless, this is true only for VoIP and FTP I + VoIP models. If FTP II + VoIP model is implemented, eACS-MB surpass ACS-MS only slightly, while SOS offers better result for FAPs position up to 5 m from the house boundaries.
Figure 10 also demonstrates that the PS scheme outperforms all conventional schemes in term of overall throughput for VoIP and FTP I + VoIP traffic loads. In case of heavy traffic load, our proposed scheme has always better results but for SOS scheme. Nonetheless, PS is still better than SOS scheme if the FAPs distance from house boundaries is at least 4 m (for bandwidth equal to 3 MHz) or 1 m (for bandwidth equal to 10 MHz), respectively. Although the SOS outperforms our schemes for FAPs position closer to the sidewalk, the performance of SOS scheme in general terms is not satisfactory. The main reason is that the FAPs transmitting power is adapted in dependence on the number of mobility events. Thus, the CINR experienced by passerby UEs is very low as the signal strength received from msB is only marginally higher than signal received from the FAPs; that is, low efficient MCS has to be utilized.
The paper proposes the power control mechanism, which dynamically adapts the transmitting power of FAPs depending on the current traffic load and signal quality received at the side of UEs. The results demonstrate that the optimized PS mechanism significantly outperforms both evaluated ACS schemes. Despite of this, the PS is able to guarantee the same QoS to FAPs users as in case of ACS-MB or eACS-MB. When compared to the SOS trying to mitigate mobility events while maximizing indoor coverage, the results achieved by our power control method are always better as long as the generated traffic is at light or medium levels and sufficient amount of radio resources is allocated to the FAPs. Nonetheless, with optimized power adaptation step equal to 2 dB, the PS outperforms SOS also at heavy traffic load if sufficient amount of radio resources is allocated to the FAPs while they still enable the coverage of all users in the house. The further benefit of the proposed power control scheme can be seen in its potential to minimize overall power consumption by the FAPs.
In the future, our intention is to investigate the impact of adaptive power control step and to analyze the effect of different target frame utilization on the system performance.
This work has been performed in the framework of the FP7 Project FREEDOM IST-248891 STP, which is funded by the European Community. The authors would like to acknowledge the contributions of their colleagues from FREEDOM Consortium (http://www.ict-freedom.eu/).
- Presentations by ABI Research, Picochip, Airvana, IP.access, Gartner, Telefonica Espana 2nd International Conference on Home Access Points and Femtocells, December 2007, http://www.avrenevents.com/dallasfemto2007/purchase_presentations.htm
- Golaup A, Mustapha M, Patanapongpibul LB: Femtocell access control strategy in UMTS and LTE. IEEE Communications Magazine 2009, 47(9):117-123.View ArticleGoogle Scholar
- Lopez-Pereze D, Valcarce A, Ladanyi A, de la Roche G, Zhang J: Intracell handover for interference and handover mitigation in OFDMA two-tier macrocell-femtocell networks. EURASIP Journal on Wireless Communications and Networking 2010., 2010:Google Scholar
- Hobby JD, Claussen H: Deployment options for femtocells and their impact on existing macrocellular networks. Bell Labs Technical Journal 2009, 13(4):145-160. 10.1002/bltj.20341View ArticleGoogle Scholar
- Claussen H: Performance of macro- and co-channel femtocells in a hierarchical cell structure. Proceedings of the 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC '07), September 2007 1-5.Google Scholar
- Bharucha Z, Haas H, Saul A, Auer G: Throughput enhancement through femto-cell deployment. European Transactions on Telecommunications 2009, 41: 311-319.Google Scholar
- Chandrasekhar V, Andrews JG, Gatherer A: Femtocell networks: a survey. IEEE Communications Magazine 2008, 46(9):59-67.View ArticleGoogle Scholar
- 3rd Generation Partnership Project : Technical specification group radio access network; evolved universal terrestrial radio access (E-UTRA); physical channels and modulation. June 2010., (3GPP TS 36.300 v 10.0.0):Google Scholar
- Jo HS, Yook JG, Mun C, Moon J: A self-organized uplink power control for cross-tier interference management in Femtocell networks. Proceedings of the IEEE Military Communications Conference (MILCOM '08), November 2008 1-6.Google Scholar
- Chandrasekhar V, Andrews JG, Muharemovic T, Shen Z, Gatherer A: Power control in two-tier femtocell networks. IEEE Transactions on Wireless Communications 2009, 8(8):4316-4328.View ArticleGoogle Scholar
- Chandrasekhar V, Andrews JG, Shen Z, Muharemovic T, Gatherer A: Distributed power control in femtocell-underlay cellular networks. Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM '09), November-December 2009 1-6.Google Scholar
- Claussen H, Ho LTW, Samuel LG: Self-optimization of coverage for femtocell deployments. Proceedings of the 7th Annual Wireless Telecommunications Symposium (WTS '08), April 2008 278-285.Google Scholar
- Claussen H, Pivit F, Ho LTW: Self-optimization of femtocell coverage to minimize the increase in core network mobility signalling. Bell Labs Technical Journal 2009, 14(2):155-184. 10.1002/bltj.20378View ArticleGoogle Scholar
- Claussen H, Ho LTW, Samuel LG: An overview of the femtocell concept. Bell Labs Technical Journal 2008, 13(1):221-246. 10.1002/bltj.20292View ArticleGoogle Scholar
- Choi SY, Lee T-J, Chung MY, Choo H: Adaptive coverage adjustment for femtocell management in a residential scenario. Proceedings of the 12th Asia-Pacific Network Operations and Management Symposium (APNOMS '09), 2009 5787: 221-230.Google Scholar
- Jo H-S, Mun C, Moon J, Yook J-G: Self-optimized coverage coordination in femtocell networks. IEEE Transactions on Wireless Communications 2010, 9(10):2977-2982.View ArticleGoogle Scholar
- Yun S, Cho D-H: Traffic density based power control scheme for femto AP. Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC '10), September 2010 1378-1383.View ArticleGoogle Scholar
- Mach P, Becvar Z: Dynamic power control procedure for femtocells based on frame utilization. Proceedings of the International Conference on Wireless and Mobile Communication (ICWMC '10), September 2010 498-503.Google Scholar
- Sesia S, Toufik I, Baker M: LTE—The UMTS Long Term Evolution—From Theory to Practice. 2009.Google Scholar
- Abe T: 3GPP Self-evaluation Methodology and results—assumptions. 3GPP LTE-Advanced Evaluation Workshop, December 2009, http://www.3gpp.org/ftp/workshop/2009-12-17_ITU-R_IMT-Adv_eval/docs/pdf/REV-090007%20SelfEvalulation%20assumption.pdfGoogle Scholar
- Chen Y, Wen X, Lin X, Zheng W: Research on the modulation and coding scheme in LTE TDD wireless network. Proceedings of the International Conference on Industrial Mechatronics and Automation (ICIMA '09), May 2009 468-471.Google Scholar
- Hoymann C: Analysis and performance evaluation of the OFDM-based metropolitan area network IEEE 802.16. Computer Networks 2005, 49(3):341-363. 10.1016/j.comnet.2005.05.008View ArticleGoogle Scholar
- IEEE 802.16m Evaluation Methodology Document, IEEE 802.16m paper No. 08/004r2, 2008Google Scholar
- Femto Forum : Interference Management in UMTS Femtocells. white paper, February 2010, http://www.femtoforum.orgGoogle Scholar
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