But scarce spectrum has pushed 3G and 4G wireless technologies to operate at 2 GHz and above. This, in turn, will lead to spotty coverage for indoor users as.
Distributed Power Control Mechanisms for HSDPA Femtocells Naveen Arulselvan, Vinod Ramachandran, Suresh Kalyanasundaram
Guang Han
Motorola India Private Limited, Bangalore
Motorola Inc, USA
Email: {naveen.a,vinodkumar,suresh.kalyanasundaram}@motorola.com {guang.han}@motorola.com
Abstract—Femtocells are low-cost, miniature basestations intended to improve indoor coverage in 3G networks and beyond. One of the main issues in adopting femtocells en masse is the surge in interference to the mobile users served by the macrocell arising from unplanned networks and private access. Therefore, distributed power control mechanisms for femtocells are essential to shield the existing users of the macrocell as well as to enable scalable femtocell deployments. This paper studies several such power control schemes that strike an effective balance between the throughput of the femto users and the degradation in macrocell performance.
I. I NTRODUCTION Recent years have witnessed price-wars among voice operators, and inspite of increasing number of subscribers, the average revenue per user (ARPU) for voice is declining [1]. Operators are starting to focus on home services, through bundled offerings with voice, television, data as the triple play, and mobile access adding a potential fourth dimension. But scarce spectrum has pushed 3G and 4G wireless technologies to operate at 2 GHz and above. This, in turn, will lead to spotty coverage for indoor users as signals tend to fade out faster at higher frequencies. Femtocells are low-cost cellular base-stations that can provide improved home coverage and increase the capacity for user traffic. Using an IP-based backhaul such as the user’s existing DSL connection, femtocells can provide cost-effective high-bandwidth wireless services. In combination with a macrocellular network for coverage, femtocells can significantly reduce the total network costs [2]. For mobile operators, femtocells also provide an opportunity to compete directly with fixed-line and Voice-over-IP (VoIP) service providers. The two most important deployment characteristics of femtocells are related to (a) frequency of operation and (b) access privileges to the user [3]. Femtocells can share a carrier with the existing macro network, which is referred to as co-channel deployment, or operate in their own frequency band as in dedicated channel deployments. Femtocells could be deployed in a Closed Subscriber Group (CSG) fashion in private offices and
homes, which implies that only registered users may establish connection with these femtocells. Alternatively, femtocells could have open access, where all subscribers of the operator can access these femtocells. Hot-spots such as cafes and hotel lobbies may opt for open-access deployments. Operating femtocells on a dedicated frequency and/or allowing open access remains a possibility; interference management is arguably simpler in such scenarios [4]. But co-channel operation with an existing macrocellular network is more rewarding for the operator due to increased spectral efficiency through frequency re-use. Moreover privacy issues of individual subscribers may preclude open access deployment at all times. As a result, we study the co-channel operation of femtocells with restricted access. Not only does this present more challenging problems, we also expect this to be the de facto deployment mode. Previous work in [5] and [6] have proposed methods where femtocells locally calibrate their DL transmission powers. Femtocell transmit power is computed so that minimum coverage is guaranteed for an imaginary macro user in the vicinity and the maximum data rate for a nearby femto user is fixed to control the interference to other femtocells. Such hard assumptions and errors in estimating physical locations will cause these calibration schemes to perform conservatively. In this work, we investigate two categories of power control algorithms for femtocells that can be performed locally with minimal network intervention. These power control schemes differ in their time-scale of operation. In the geo-static power control scheme, the transmit power of the femtocell is based on a simple function of the distance from the macrocell. The key idea behind the adaptive power control scheme is to adjust the transmit power of the femtocells so as to just achieve their target data rates. The target rate, in turn, is computed by the network to balance the degradation in macrocell performance and increase in femto user throughput. Using system-level simulations, we present coverage and capacity results for users served by both the macrocell and the femtocells.
978-1-4244-2517-4/09/$20.00 ©2009 IEEE
The paper is structured as follows. In section II, we study the effect of fixed transmit powers of femtocells on users in the macrocell. In section III, we discuss a class of power control schemes that operate on a slow time-scale. In section IV, we analyze a dynamic power control scheme.
TABLE I S YSTEM PARAMETERS
P arameter Cell Layout Inter-site dist Carrier frequency/ Bandwidth Total Macro Tx power Control channel power Data channel power Femto total Tx power Femto control channel power Wall penetration loss (WP)
V alue Hexagonal grid 19 cell sites, 3 sectors/site 1732 m 2 GHz/ 5 MHz 20 W 2W 14 W PF 0.25PF 10 dB σ=8db (towards macro) σ=10 dB (towards femto) 9 dB 3 km/h (for macro users only) 128.1 + 37.6log10 d(km)+WP 7 + 56log10 d(m)+WP 37 + 20log10 d(m) Proportional fair 25 m 15 m
II. F IXED TRANSMIT POWER FOR FEMTOCELLS In this section, we investigate the adverse impact of fixed femtocell powers on the macro users’ capacity and coverage. We observe a near fifty-percent reduction in capacity of the macrocell for even nominal femtocell densities. The results also show that femtocells with unregulated transmit power are bound to cause large dead zones (i.e., out-of-coverage areas) for users served by the macrocell. We consider a High-Speed Downlink Packet Access (HSDPA) system deployed in a sub-urban environment with parameters indicated in Table I. Two tiers of neighboring macrocells are considered for modeling interference, but the statistics for the center-cell alone are considered for the results. We note that the results presented in this section can be easily extended to other advanced 4G systems. The macro users are all assumed to be outdoors, whereas the femtocells and the users they serve are indoors. Each femtocell is assumed to have one static user randomly placed in a cell radius of 15 meters. The center macrocell contains 50 users with full buffer FTP traffic, while the femtocells serve one mobile user each. The path-loss values for macrocell transmissions as a function of the distance d to the user is given by LM (d), and the path-loss values for femtocell transmissions are given by LiF (d) or LoF (d), depending on whether the mobile user is indoor or outdoor. The fraction of femtocell control channel power constituting total transmit power is generally higher than for macrocells to ensure better coverage. The macro users will experience interference from the transmissions of the neighboring femtocells and other macrocells. The macrocell employs a proportionallyfair scheduler. To study the impact of control channel power of femtocells on the macrocell performance, we model the activity level of femtocells via an activity factor. Active femtocells have data transmissions, while inactive femtocells simply transmit control channel power.
and femtocell throughputs. We can observe that the macrocell throughput suffers significantly for even moderate femtocell transmit powers. On the other hand, femtocell throughputs are reasonably large even when their transmit power levels are low.
A. Impact on Macrocell Capacity
B. Impact on Macrocell Coverage
Consider 200 femtocells uniformly distributed in the center macrocell, each with an activity factor of 0.5. This corresponds to 100 effective femtocells transmitting at a fixed transmit power of PF and 100 other inactive femtocells transmitting only control signaling, which in turn is taken to be 0.25PF . Figure 1 gives the corresponding average macrocell
Common Pilot Control Channel (CPICH) is a downlink channel broadcast by the macrocell with constant power and a known bit sequence. The macrocell’s CPICH strength indicates the extent of macro UE coverage. In this section, we study the impact of femtocells on macro CPICH signal strength. The probability of a femtocell k being active is given by the activity factor
Log-normal shadowing UE noise figure Speed Macro to indoor UE (LM ) Femto to outdoor UE (LoF ) Femto to indoor UE (LiF ) Scheduler Min inter-femto distance Min femto-macro UE distance
Fig. 1.
Effect of fixed femtocell power
ak and the corresponding transmission power is PF,k . The inactive femtocells are assumed to transmit control control . Then for a macro UE i, the channel power PF,k Ec CPICH signal-to-noise ratio N is given by 0 Ec = N N0
PM,n n=1 LM,n
+
K
Pcpich LM i
control ak PF,k +(1−ak )PF,k k=1 Lo F,k
+W (1) where Pcpich is the CPICH power, W is the noise power, and N and K are the number of macrocells and femtocells respectively. The total transmit power is taken to be 20 dBm for all the femtocells. The CDFs of CPICH Ec /N0 are shown in Figure 2 for different activity factors. Here the femtocells are assumed to switch off their control channels when inactive. Figure 3 gives the CDFs of CPICH Ec /No for the case where femtocells continue to transmit control channel power when inactive. As expected, the macrocell coverage further deteriorates and is almost independent of the activity factor. These results corroborate the fact that number of active femtocells and the control channel of femtocells have a strong negative impact on macrocell performance.
,
Fig. 3.
Macro signal strength CDF for different activity factors
instead of scaling down both the control channel and the data channel powers by the same factor, we fix the femtocell control channel power and reduce the data channel power alone. This ensures optimum coverage for femto users and minimizes effect on macro users. Figure 4 shows the average macrocell and femtocell throughput when femtocells operate with a fixed control channel power of 25 mW while the data channel power is varied from 75 mW to 25 mW. We observe that this leads to approximately a ten percent improvement in the macrocell throughput. On the other hand, the femtocell throughput is large even with the reduced data channel power. Moreover, the femtocell coverage will not be impacted as the control channel power remains constant.
Fig. 2. Macro signal strength CDF for different activity factors (No control channel)
III. C ALIBRATION T ECHNIQUES In the next few sections, we propose several power control schemes that do not require the femtocells to change their transmit powers at a fast time-scale. A. Femtocells with Varying Data/Control Power Ratios Based on the results so far, it is evident that the femtocells are able to achieve a significantly larger throughput than the macrocell. However, they reduce the macrocell capacity, especially when operating at higher transmit powers. While reducing the transmit power of femtocells can help macro users, the femtocell coverage can be affected significantly. Therefore,
Fig. 4. ratio
Average cell throughput vs. femtocell data/control power
B. Geo-static Transmit Power First, we study the geographic impact of femtocell transmit power on macro layer coverage by looking at the CPICH coverage. For a macro user i, the CPICH SINR Ec/N o takes the form as in (1) with activity factor aj = 1 for all j, i.e., all femtocells are active.
We declare a macro user is in x percent-outage if its CPICH Ec/N o is below a threshold value to for a fraction of time larger than x. For to and x values of 25 dB and 2%, respectively, Figure 5 shows macrocell mobiles that are in coverage and outage for femtocell transmit power settings of 0.1 mW and 100 mW (only extremes shown due to space constraints). The positions shown in green and red indicate mobiles that are in coverage and outage, respectively. The outage probability of a macro user is influenced by both the proximity to the serving macrocell as well as the distance to the nearest interfering femtocell. From the figure, we observe that (a) the coverage probability of macro users close to the serving macrocell is not influenced by presence of femtocells, even for high transmit powers of the femtocells, and (b) The coverage probability of macro users in the cell edge is sensitive to the distance to its nearest femtocell interferer. This coverage probability will deteriorate rapidly as the femtocell transmit power increases. The network can set the transmit power of the femtocells according to the geographical zone in which they lie. Because femtocell deployments will be unplanned, the power zones of the femtocell can be segregated simply based on the distance to the macrocell. The zone and the power level of the femtocells can be pre-configured and/or modified over the broadcast channel or the DSL backhaul. The power setting will not change, except in the case of rare events like macrocell-splitting or femtocell relocation. An example of such a power-zone division is shown in Figure 6. Macro users in outage will be much fewer than when all femtocells transmit at the maximum power level.
Fig. 5.
Femto transmit power vs User-outage positions
Fig. 6.
Power Zone segregation for Femtocells
IV. A DAPTIVE T RANSMIT P OWER CONTROL For a given macro user i, we assume there are N macrocells and K femtocells. The downlink Signal to Interference and Noise ratio (SINR) for user i is then given by SIN Ri = N
Pi LM,i K PF,k k=1 Lo F,k
, +W (2) where Pi is the power in the shared data channel reserved for user i, PM,n is the power used by macrocell n, PF,k is the power used by femtocell k. Here α is a factor that arises from non-orthogonality between different channelization codes in the HSDPA system and Pres is the residual power of the serving cell after subtracting the power used for user i. The downlink bit-rate at time t is then given by the modified Shannon’s equation [7]: log2 (1 + 0.5 ∗ SIN Ri ) bps/Hz, (3) RM (t) = PM,n n=1 LM,n
+
+
αPres LM,i
i∈S(t)
where S(t) is the set of the users scheduled at time t and the factor of 0.5 is to account for the gap between the theoretical Shannon capacity and the capacity that can be achieved in practice with HSDPA. When all the femtocells use equal power, it is easy to see that SINR and hence macrocell throughput RM decreases with increasing femtocell density. The power allocation problem for multiple femtocells is similar to the non-cooperative game formulation studied in [8] for Digital Subscriber Lines (DSL). The authors developed an iterative algorithm with no centralized control and show that Nash Equilibrium (NE) is reached for the two-user case. We employ a similar approach where the network provides each femtocell k with a target bit-rate Tk . The network may take into account factors such as macrocell load, number of active femtocells, distance of the femtocell to the macrocell, and fading environment to determine Tk for a given femtocell. The femtocells collect the SINR measurements from the mobile users they serve and use this to schedule in each transmission opportunity.
The femtocells can determine the effective data rate RFk in the downlink using (3). Then the femtocells can regulate their transmit power so that their target bit-rates are just met. The power control algorithm executed in every femtocell k = 1, 2, · · · , K at every scheduling instant is as follows: • • •
Femtocell k checks to see if the DL bit-rate RFk is in the range [Tk , Tk + ], for some constant If not, the femtocell adjusts its transmit power level Pk accordingly The adjusted power level Pk is then constrained to lie in the permissible range [Pmin , Pmax ].
For the numerical studies, we assume identical target rates are set for all femtocells. Figure 7 gives the relationship between the total macrocell throughput and the number of femtocells. Small target bit-rate settings for femtocell give as much as 15 % macrocell throughput enhancement even when the femtocell deployment is relatively sparse. This benefit increases to around 33% as femtocell deployments get denser. Figure 8 shows the throughput distribution of all macro users and the bottom 50% macro users for 300 femtocells and a fixed target bit rate, when (a) femtocells perform no power control, (b) femtocells perform the adaptive power control described, and (c) there are no femtocells. This demonstrates that adaptive power control benefits apply fairly to all macro users and not just users with good channel conditions. We also note that the total cell throughput (i.e., the sum of throughputs of all femtocells and the macrocell) increases linearly with the number of femtocells. This is because, inspite of power control, the femtocells operate at much higher spectral efficiencies than their macro counterpart. As a result, the contribution from macrocell to the total throughput is negligible.
Fig. 8.
Macro user throughput distribution (300 femtocells)
V. C ONCLUSIONS We have studied the impact of femtocell interference on HSDPA macrocell capacity and coverage. We discussed the need for distributed transmit power control solutions for femtocells to enhance macro user performance and enable scalable deployments. We demonstrated the benefits of simply varying the ratio of femtocell data channel and control channel powers to improve macro users experience and maintain femtocell coverage. In the geo-static scheme, the transmit power of the femtocell is regulated as a function of its geographical location alone. In the adaptive power control scheme, femtocells locally achieve a target data rate that is centrally computed by the network. All these power control mechanisms provides efficient trade-offs between femtocell and macrocell performances, while varying in implementation complexity. VI. ACKNOWLEDGMENTS The authors would like to thank their colleague Rajeev Agrawal for several useful discussions. R EFERENCES
Fig. 7.
Macrocell throughput vs Femtocell density
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