IEEE Globecom 2010 Workshop on Femtocell Networks
Power Control Based Interference Mitigation in Multi-tier Networks Shu-ping Yeh, Shilpa Talwar, Nageen Himayat and Kerstin Johnsson Intel Corporation Santa Clara, US
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performance. Hence, interference mitigation techniques are critical in multi-tier networks.
Abstract—Significant areal capacity gains and improved cellular coverage can be achieved by hierarchical deployment of Femto Access Points (FAP) over an existing cellular network. However, the introduction of FAPs, which use the same spectrum as the cellular network, can cause severe interference to network and drive users into outage. In order to resolve this issue, advanced interference mitigation (IM) techniques should be applied in multi-tier networks. In this paper, we design and evaluate power control based IM algorithms in cellular systems with femtocell overlay. Simulation results show that FAP power back-off helps lower macro-user outage probability at the cost of femto-user rate reduction. For control channels with low data rate requirement, FAP power control can be a potential IM solution. Keywords-component; multi-tier interference mitigatio; power control.
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network;
This paper provides techniques to manage downlink interference in single frequency multi-tier networks. We explain and justify the algorithms in the femtocell overlay network where FAPs and MBSs are deployed onto the same geographical area, but the idea can be applied in other types of multi-tier networks as well. The approach we investigated for solving the interference mitigation problem is applying power control on FAPs. By adjusting FAP transmit power level, we manage interference coming from femtocells to the macronetwork as well as optimize capacity of the overall multi-tier network.
femtocell;
Performance of different algorithms was evaluated via static system level simulation. Results show that FAP power control helps reduce outage for outdoor users and alleviate degradation in macro-user performance resulting from femtocell interference. The power control solution is especially useful for control channels where interference to macro-users is of primary concern, and can lead to erroneous decoding of important control information. However, for data channels, FAP power back-off sacrifices femto-users’ data rate in order to improve macrocell coverage. Therefore, more advanced interference mitigation algorithms, such as frequency planning, should be adapted to optimize data channel performance.
INTRODUCTION
Multi-tier networks are cost-effect network architectures that achieve significant areal capacity gain and coverage improvement. The idea is to overlay low-power and low-cost devices on coverage holes or capacity-demanding hotspots to supplement conventional single-tier cellular networks. These devices can be open access to every subscriber. In which case, they are usually operator deployed public infrastructure, e.g., Picocell base stations (BS) and relay stations. An alternate scenario, called the closed subscriber group (CSG), allows access permission to only restricted users. This use case is typical for femtocells where users deploy their privately owned Femto access points (FAP). Both open access and CSG devices can help off-load traffic from Macro-BS (MBS). It has been shown that with multi-tier network architectures, a potential areal throughput gain over 100x can be achieved [1].
Power control as a potential solution for the multi-tier interference problem has been studied for both uplink [5][6] and downlink [7][8] scenarios. The focus of our paper is to solve the downlink interference problem. In [7], power control algorithms are developed to optimize energy efficiency under macro/femto users QoS constraints. A carrier sensing based power control is proposed in [8] for multi-antenna FAPs. In both [7] and [8], slow-fading is ignored when analyzing the problem. We evaluate our power control schemes under more realistic setting with both path-loss and slow-fading considered.
As spectral resources are limited, multi-tier networks target full reuse of the spectrum being used by the MBSs and FAPs. Therefore, all devices share the same frequency band and the highest spatial reuse gain is achieved. However, under cochannel operation, interference becomes a major issue that limits the performance of the network. The problem is even more prominent in CSG femtocells, due to the additional coverage holes created by FAPs for users without access permission. As FAP deployment density increases, a growing proportion of macro-users are driven into outage due to the increased interference, leading to unsatisfactory macro
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This paper is structured as follows. In section 2, we explain the details of the power control schemes being investigated. Simulation settings and results are presented in section 3. Finally, we conclude the paper in section 4. II.
FEMTO-AP POWER CONTROL
The transmit power level of a FAP affects its coverage range and the amount of interference it generates in the
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network. Though higher FAP transmit power can provide wider coverage and better signal quality, it can, at the same time, cause tremendous interference to surrounding users. Properly selecting the FAP transmit power level can help manage the interference from FAPs to macro-users, while maintaining femtocell performance. Therefore, our proposed solution is to mitigate interference caused by FAPs via FAP power control.
iv. Ensure that FAP transmit power does not exceed the maximum power constraint. v. (Optional) Users re-associate to best BS/AP generating maximum received signal power after FAP power backoff. In this scheme, FAPs transmit sufficient power to support femto-user QOS. This requires FAPs to transmit at power level above the interference level from the MBSs. Hence, FAPs transmit with higher power near cell center where the interference from MBSs is high.
In this paper, three power control algorithms are developed and evaluated. We first consider fixed power level operation where all FAPs within certain region transmit at the same network-defined power level. Then, two additional adaptive FAP power control algorithms are designed: a) Femto-QoS power control, which performs FAP power back-off under the constraint of a minimum quality of service (QoS) at femtousers being maintained, and b) Macro-QoS power control, which limits FAP interference to the macro-network by certain requirements of macro-user performance. We detail the three power control schemes in the following subsections.
The Femto-QoS power control scheme adapts FAP transmit power from femto-users’ point of view. There is no guarantee for macro-users performance. To better understand the FAP power selection problem, we develop the next scheme that adjusts FAP transmit power from macro-user’s aspect. C. Macro-QoS Power Control Since macro-users are the main victims of interference in femtocell overlay networks, we design a Macro-QoS power control scheme that helps protect macro-users. The idea is to limit FAP interference to macro-users according to a certain criteria. Each FAP transmits at a power level such that limited interference is caused to their surrounding macro-users.
A. Fixed Power Level This is the simplest approach, in which all Femto-APs within certain region operate at the same power level, namely P0. This power level is a function of density of FAPs, and can be provided by a central network entity such as SON server, or can be determined by FAPs based on a self-organizing algorithm. The power level is fixed after deployment or slowly updated as the network evolves, and it should be always be lower than the maximum available power level of a FAP.
We summarize the power control procedure is as follows. i. Macro-users measure the received signal level of interference from all MBSs and the noise level. Denote the sum of interference power from all MBSs and the noise power as IMacro+N.
When the power level is determined by the network, the power control procedure is as follows.
ii. Each macro-user then identifies strong femto interferers. When the interference from one FAP is above a certain threshold relative to IMacro+N, this FAP is categorized as a strong femto interferer.
i. Network coordinators gather the FAP density information and decide the FAP operating power level. ii. Network coordinators broadcast the power level information. All FAPs transmit at the same power level advertised from the network.
iii. For each strong femto interferer, macro-users compute the required power adjustment. The principle is to have the FAP lower its transmit power so that it results in an interference power that is x dB less than IMacro+N.
This scheme is also useful in separate channel operation scenarios where femto and macro networks use different carrier frequencies. However, for co-channel operation, one of the adaptive approaches described below may be preferred.
iv. Macro-users report the FAP ID of their strong femto interferers and the required power adjustment to the serving MBS.
B. Femto-QoS Power Control The goal of this scheme is to ensure femto-user QoS while minimizing femto-to-macro interference. The idea is to have each FAP transmit at the minimum power required to meet a specific QoS constraint for users they serve.
v. MBSs communicate with FAPs via backbone or overthe-air and inform them of the required power adjustment. vi. FAPs modify their transmit power level based on the FAP power adjustment information from MBSs. FAPs should select the lowest advertized power level from MBSs and the power level cannot exceed the maximum FAP power constraint.
The power control procedure is described in the following. i. Each FAP receives the QoS constraint from the network. The QoS constraint can be in the form of a target SINR value, such as the required SINR for femto-users to avoid outage, e.g., the SINR corresponds to the lowest modulation and coding scheme (MCS).
vii. (Optional) Users re-associate to best BS/AP generating maximum received signal power after FAP power backoff.
ii. Femto-users report their SINR measurements to their serving FAPs.
This scheme protects macro-user at the cost of femto-user performance degradation since there is no protection to femtousers. Another drawback of this scheme is that it requires more
iii. Each FAP adjusts their transmit power to ensure the weakest femto-user they serve achieves target SINR.
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network communication. Thus, it is more difficult to update FAP power level in a timely manner and it may overload the network if a great number of FAPs are deployed. III.
BS SS FS
SIMULATIONS
A. Simulation Assumptions To evaluate the performance of different power selection schemes, we conduct a system level simulation that involves multiple MBSs and FAPs. MBSs are deployed on a hexagonal grid with 866 meters site-to-site distance. There are 19 macrocells in the simulation with 3 sectors per cell site, for a total of 57 sectors. An example simulation deployment is shown in Figure 1. Only statistics of users associated with center cell MBSs and FAPs are collected. FAPs and users, denoted as SS in the figure, are deployed within a hexagon of radius 4 times the macrocell radius to better capture downlink interference behavior. We deploy around 50 FAPs per sector, and about 231 FAPs per km2. Each FAP is located in the center of a circular house with 10 meters radius. House locations are randomly selected from a square grid with 20 meters separation. The number of users inside a house ranges from 1 to 4. With 80% probability that there is only one user in the house; for 2, 3 and 4 users per house, probabilities are 12%, 6% and 2%, respectively. For a fair comparison, we assume the same number of outdoor users as indoor users. The assumptions for deployment within one sector are summarized in Figure 2.
Figure 1. Example deployment in system level simulation.
Only path loss and slow fading of the wireless channel are modeled. Neither frequency selective nor fast fading is considered. We adopt a combination of channel models from ITU-R M.1225 [2] and Winner [3]. For the wireless channel between MBSs and users, the ITU pedestrian model is used. For the wireless channel between FAPs and users, we use Winner A1 NLOS to model the channel between FAP and users in the same building and Winner A2 NLOS to model the channel between FAP and outdoor users. Additional outer wall for the channel between MBS and indoor users and the channel between FAP and neighbor indoor users is modeled by a random penetration loss with 12dB mean and 8dB standard deviation. The channel model is summarized in TABLE I.
X(1~4) Femto-AP
House x 50 Macro-BS
By considering only path loss and slow fading, we can compute the long term SINR. This static SINR is used for performance evaluation. We approximate the achievable data rate by the capacity formula with 3dB gap and assume maximum rate is 6 and rate granularity is 0.5. The spectral efficiency (SE) is computed according to the following formula:
SE = min 6, log 1 + SINR × 2 / 2 . 2 2
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(1)
Figure 2. Summary of deployment assumptions.
outdoor users, the cell association rule is to select the MBS with the maximum received signal power as the serving base station. The indoor users will compare the received signal from all MBSs and the FAP they can access and choose the one with maximum power as the serving BS. For the optional reassociation after FAP power back-off, we assume only outage
A user is in outage if the received SINR corresponds to SE less than 0.5. All FAPs are CSG devices. We assume only users inside the same house as the FAP have FAP access permission. For
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TABLE I. Scenarios Macro-BS to outdoor SS Macro-BS to indoor SS Femto-AP to indoor SS
CHANNEL MODEL SUMMARY
Macro-QoS scheme limits the interference level to macrousers. In current simulation, interference from a FAP is 6dB below Imacro+N. We can see from the table that the 50% outdoor user SINR degradation remains similar for maximum FAP power levels above 0dBm. This implies that for FAP power level above certain threshold, Macro-QoS scheme always limits the amount of interference from FAP to macrousers to a certain level so that macro performance remains similar. Since there is no protection to femto-users, the FAP power may decrease too much. We can see from the table that indoor outage increases. In addition, some femto-users have to switch to MBSs.
Path Loss ITU pedestrian: 40log10(R[km]) + 30log10(f[MHz]) + 49 ITU pedestrian
SF Penetration 10 0 dB 12 Mean 12dB, dB Std 8dB Winner A1 NLOS (through wall): 6 One light wall PLfree_space = 46.4 + 20log10(R[m]) + dB (3dB) every 3 20log10(f[GHz]/5) meters Femto-AP to Winner A2 NLOS: max( PLfree_space, PLB1) 7 PLtw=(14+15(1If d
