Vtc2010 Distributed Channel Selection Principles For Ofdma Femtocells With Two Tier Interference
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Vtc2010 Distributed Channel Selection Principles For Ofdma Femtocells With Two Tier Interference

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  • 1. Distributed Channel Selection Principles for Femtocells with Two-tier Interference Li-Chun Wang1 , Chiao Lee1 , and Jane-Hwa Huang2 1 National Chiao Tung University, Taiwan 2 National Chi Nan University, Taiwan Abstract—It goes without saying that the femtocells will be interference. We also compare the random selection scheme, widely employed in the next generation wireless networks since which randomly selects the sub-channels for transmissions. the femtocells improve indoor capacity and coverage with low Obviously, using more sub-channels can increase femtocell power and less cost. However, as the femtocells become pop- ular, the femtocell users suffer from the complicated two-tier capacity. However, this increases the interference between interference, including the macrocell-to-femtocell and femtocell- femtocells, and degrades link reliability. Hence, the number of to-femtocell interference. Therefore, the femtocells pose a difficult sub-channels allowed for a femtocell is the major designing challenge on managing the interference in a autonomous and dis- parameter in the channel selection scheme. We investigate the tributed manner. In this paper, we investigate how to distributedly downlink femtocell capacity, with considering path-loss, shad- select the sub-channels for the OFDMA-based femtocell systems to reduce interference and to improve indoor capacity under a owing, frequency-selective fading channel. Simulation results link reliability requirement. We develop the channel-gain oriented demonstrate that the interference from macrocell and femto- and interference-avoidance oriented distributed channel selection cells significantly degrades link reliability. It is shown that schemes. Simulation results show that the interference from the with appropriately reduce the number of used sub-channels, macrocell and other femtocells significantly degrades femtocell the proposed distributed channel selection schemes can ensure link reliability and capacity. However, by properly adjusting the number of used sub-channels, the developed channel selection the link reliability and yield higher capacity than the random schemes can improve capacity and ensure the link reliability. selection scheme. Simulation results also provide the chan- nel selection principles for different spectrum allocation and femtocell density. I. I NTRODUCTION With the benefits of low power, low cost, backward com- In the literature, the capacity and coverage of femtocells patibility, and single-mode device, the femtocell is a very are studied in some depth. The work in [1] investigated promising technique to improve indoor coverage and capacity the capacity of a CDMA-based femtocell, with considering for the next-generation mobile system. The femtocell base the transmit power configuration for femtocells. In [2], the station (fBS) is a simple and low-priced plug-and-play device, capacity and coverage for the OFDMA-based femtocell was which can reuse the licensed spectrum in the indoor envi- investigated. Both the work in [1] and [2] considered a full- ronment. Compared to the macrocell base station (mBS), the loaded case. That is, the femtocell users are busy all the fBS can use lower power to achieve higher indoor throughput time and use the whole spectrum to transmit their data. In because of the shorter communication distance. However, as addition, the channel selection is not considered. In [3], the the fBSs are widely deployed, the femtocells will face not only authors compared channel selection methods in a OFDMA- the macrocell-to-femtocell interference but also the increasing based femtocell system. In [3], the whole spectrum is divided femtocell-to-femtocell interference. Therefore, how to reduce into three segments, and each femtocell user can choose one the interference to improve link quality is an essential task in segment. However, only the femtocell-to-femtocell interfer- femtocells. ence is considered in [3]. Different from the works in [1]-[3], In this paper, we investigate the distributed channel selection this paper develops the distributed channel selection schemes principles for the OFDMA-based femtocell networks. We for the OFDMA-based femtocell networks with considering consider two spectrum allocation schemes: shared-spectrum two-tier interference. In addition, the impact of the number of and exclusive-spectrum allocation schemes. In the first one, the sub-channels allowed to be used by a femtocell user on the femtocell and macrocell systems share the same spectrum. link reliability and capacity is investigated. Therefore, we should considered. In the second one, the femtocell and macrocell systems are exclusively allocated with different spectra, and femtocell users suffer from other The rest of this paper is organized as follows. Section II femtocells’ interference. We develop the distributed channel- introduces the system model, channel models and SINR for the gain oriented and interference-avoidance oriented channel se- femtocell system. Section III discusses the femtocell capacity lection schemes for the OFDMA-based femtocell network. maximization problem with the link reliability requirement. The channel-gain oriented scheme selects the sub-channels In Section IV, different distributed channel selection schemes with higher link gain to transmit data. The interference- are proposed. The simulation results are shown in Section V. avoidance oriented scheme chooses sub-channels with lower Concluding remarks are given in Section VI.
  • 2. TABLE I M ODULATION C ODING S CHEMES AND EESM PARAMETER (β) Code Rate Spectrum Minimum EESM Modulation (Repetition: Efficiency SINR factor default=1) (bit/s/Hz) (β, dB) QPSK 1/2(4) 0.25 -2.5 dB 2.18 QPSK 1/2(2) 0.5 0.5 dB 2.28 QPSK 1/2 1 3.5 dB 2.46 QPSK 3/4 1.5 6.5 dB 2.56 16-QAM 1/2 2 9 dB 7.45 16-QAM 3/4 3 12.5 dB 8.93 64-QAM 1/2 3 14.5 dB 11.31 64-QAM 2/3 4 16.5 dB 13.8 64-QAM 3/4 4.5 18.5 dB 14.71 GF S are the antenna gains of mBS and fBS. The channel gain Fig. 1. Femtocell Layout in regular grids between mBS and fBS user is Hj,m , and that between the kth fBS and fBS user is hk , including the effects of shadowing j,m II. S YSTEM M ODELS and fading. Therefore, the CINR of mth sub-carrier on the jth sub-channel for the user in the ith femtocell is defined as We consider the OFDMA-based femtocell system with two- pi GF S hi tier interference as shown in Fig. 1. We focus on the downlink j,m j,m L(di ) performance. Each femtocell user experiences interference γj,m = K . (2) Pj,m GBS Hj,m pk GF S hk from other fBSs and mBS. We consider the regular grids of 25 + j,m j,m + N0 L(D) L(dk ) femtocells in the macrocell with the coverage radius DM of k=1,k=i 500 m. The house size is 10m-by-10m. Each house has four rooms, and the fBS is located at the bottom-left corner of the C. Exponential Effective SIR Mapping (EESM) top-right room with a (0.1 m, 0.1 m) shift from the center of The exponential effective SIR mapping (EESM) method is the house. The separation distance between fBSs is dsf (m). to map a vector of the per sub-carrier SINR level to a single AWGN-equivalent SINR [7]. If there are M individual sub- A. Radio Channel Effects carriers in a sub-channel, the AWGN-equivalent SINR for the This paper considers the impacts of path-loss, shadowing sub-channel can be expressed as and frequency selective fading channel as follows. M 1) Path-Loss: The path-loss decays with propagation dis- 1 γj,m SIN Ref f,j = γef f,j = −β·ln( e− β ). (3) tance d between the transmitter and the receiver [4], [5]. M m=1 β is an EESM calibration factor to minimize the mean square LF S (d) = 20 log10 ( 4πd ) , for d ≤ dBP L(d) = λ d (1) error between the equivalent SINR by EESM method and LF S (dBP ) + 35 log10 ( dBP ) , for d > dBP . equivalent SINR from simulation. Table I shows the consid- The path-loss model is related to wavelength λ of operating ered modulation coding schemes (MCS), the corresponding frequency. The break-point distance is dBP = 5 m for the SINR threshold, and the EESM parameter β. According to indoor link and 30 m for the outdoor-to-indoor link. Table I, we can determine the MCS and the spectrum effi- 2) Penetration Loss: The penetration loss is assumed to be ciency SEEESM,j for the used channel with the equivalent 5 dB loss per internal wall for indoor link; and 10 dB per SINR γef f,j . external wall for outdoor-to-indoor link. 3) Shadowing: Shadowing is modeled by a log-normal D. Link Reliability X random variable 10 10 . X is a Gaussian distributed random The link reliability probability is the probability that ef- variable with zero mean. The standard deviation is 5 dB for fective SINR greater than a predefined SINR threshold γ . th the indoor link and 10 dB for the outdoor-to-indoor link. Consider that there are total J sub-channels. Each femtocell 4) Multi-Path Fading: The frequency-selective fading is de- selects ρJ sub-channels for transmission. The sub-channel scribed by the Stanford University interim-3 (SUI-3) channel usage ratio ρ is defined as the ratio of used sub-channels to model, which assumes 3 taps with non-uniform delays. the total sub-channels. Let ε be the utility function. If the j sub-channel j is selected to transmit data, εj = 1; otherwise, B. Carrier to Interference-and-Noise Ratio εj = 0. We define the average link reliability Prel as We consider the two-tier interference. Let Pj,m and pk j,m J be the transmission power of mBS and that of k-th fBS at 1 Prel = εj Pr [γef f,j ≥γth ] (4) the mth sub-carrier of jth sub-channel. Moreover, GBS and ρJ j=1
  • 3. where Pr [γef f,j ≥γth ] is the link reliability of jth sub-channel. A. Max-Min Channel-Gain Oriented Selection Scheme The SINR threshold γth means the minimum SINR require- We explain the procedures in the following. ment for data transmission. In Table I, we use γth = −2.5 dB (S1) Compare the individual sub-carrier gain in a sub-channel. as an example. The minimum sub-carrier gain in a sub-channel is hj = min {hi }, for j = 1, . . . , J j,m (8) m=1,2,...,M III. F EMTOCELL C APACITY M AXIMIZATION where M is the total number of sub-carriers in a sub-channel, Capacity and link reliability are both essential factors in and J is the the total number of sub-channels. (S2) Sort hj the distributed channel selection principle for the OFDMA- as h1 ≥ h2 ≥ ... ≥ hρJ ≥ ... ≥ hJ . based femtocell systems. From a link reliability perspective, (S3) Select the first ρJ sub-channels with higher link gain, decreasing the number of sub-channels allocated to a fBS can that is, hj > hρJ+1 , for j = 1, ..., ρJ. decrease the interference effect for the users around to the fBSs. However, from the link capacity standpoint, increasing B. Max-Avg Channel-Gain Oriented Selection Scheme the number of sub-channels allocated to a fBS can provide higher data rate. This scheme selects the sub-channel according to average To achieve the tradeoff between capacity and link reliabil- sub-carrier gain, as detailed in the following. ity, we formulate an optimization problem to determine the (S1) Compute the average sub-carrier gain of each sub- optimal number of sub-channels allocated to a fBS, aiming channel. M to maximize femtocell capacity subject to the link reliability 1 requirement. The femtocell capacity C is defined as the hj = hi , for j = 1, . . . , J. j,m (9) M m=1 aggregated throughput of a femtocell, which depends on the channel selection scheme, the number of used sub-channels, (S2) Follow the steps (S2) and (S3) in Section IV-A. and the adopted MCS of each sub-channel. Furthermore, according to the equivalent SINR γef f,j from the EESM C. Min-Max Interference-Avoidance Oriented Selection calculation and Table I, we can determine the used MCS Scheme and then the spectrum efficiency SEEESM,j . Assume that The procedures are described in the following. We consider Bj is the bandwidth of a sub-channel. Then, the femtocell the interference from mBS and other fBSs. J capacity is equal to C = j=1 εj Bj SEEESM,j . The decision (S1) Compare the interference for each sub-carrier of a sub- variable in the optimization problem is the channel usage ratio channel. The minimum interference for the sub-carriers in a ρ. Based on these considerations, the capacity maximization sub-channel is issue can be formulated as a nonlinear programming problem K as expressed in the following as Ij = max {Pj,m Hj,m + pk hk }. (10) j,m j,m m=1,2,...,M J k=1,k=i max C = εj Bj SEEESM,j (5) (S2) Sort Ij as I1 ≤ I2 ≤ ... ≤ IρJ ≤ ... ≤ IJ . ρ∈[0,1] j=1 (S3) Select the first ρJ sub-channels with lower interference, that is, Ij < IρJ+1 , for j = 1, ..., ρJ. subject to: 1 J D. Min-Avg Interference-Avoidance Oriented Selection ρ= (6) Scheme J j=1 This scheme selects the sub-channel according to average Prel ≥ Relth (7) interference for the sub-carriers of a sub-channel. (S1) Compute the average interference of a sub-channel. where εj ∈ {0, 1}, and Relth is the link reliability require-   M K ment. 1 Ij = Pj,m Hj,m + pk hk  . j,m j,m (11) M m=1 k=1,k=i IV. D ISTRIBUTED C HANNEL S ELECTION S CHEME (S2) Follow the steps (S2) and (S3) in Section IV-C. We develop two distributed channel selection principles for femtocell system: the channel-gain oriented and interference- V. S IMULATION R ESULTS avoidance oriented schemes. The first scheme aims to transmit We investigate the downlink capacity and link reliability data in the sub-channel with higher link gain. In the contrary, of the OFDMA femtocells by simulations. We consider the the second one transmits data in the sub-channel with lower in- shared-spectrum allocation and the exclusive-spectrum allo- terference. Both schemes can operate in a distributed manner. cation schemes for the femtocells and macrocell. We com- The key parameter is the sub-channel usage ratio ρ as shown pare the channel-gain oriented, interference-avoidance oriented in (5). We detail the developed channel selection schemes as distributed channel selection schemes and random selection follows. scheme. We assume the femtocell layout as shown in Fig. 1.
  • 4. TABLE II PARAMETERS IN W I MAX AND OFDMA SYSTEM 1 ≥γ ) th 0.95 Parameter Value eff Carrier frequency 2.5 GHz Success Probability (CINR 0.9 mBS/fBS Tx power 43,20 dBm Noise figure (fBS/MS) 5dB/7dB 0.85 mBS radius, DM 500 m 0.8 Separation distance between fBSs, dsf 20 m/40 m random interference avoidance oriented with minmax Antenna gain (mBS/fBS/MS) 8dB/3dB/3dB 0.75 interference avoidance oriented with minavg channel gain oriented with maxmin Receiver implementation loss 5 dB channel gain oriented with maxavg System bandwidth 10 MHz 0.7 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Data sub−channels usage ratio Sampling frequency 11.2 MHz FFT size 1024 Fig. 2. Link reliability versus the sub-channel usage ratio in dense deployment with the exclusive-spectrum scheme Sub-carrier bandwidth, Bj 10.9375 kHz Number of null/pilot/data sub-carriers 184,120,720 Number of sub-channels, J 40 1 Sub-carriers of each sub-channel, M 18 Link reliability requirement, Relth 90% ≥γ ) 0.95 th eff 0.9 Success Probability (CINR 0.85 There are 24 femtocells around the considered femtocell, and 0.8 the group of 25 femtocells is uniformly distributed in a macro- 0.75 random cell with the coverage of 500 m. The separation distances interference avoidance oriented with minmax interference avoidance oriented with minavg between fBSs are dsf = 20 m for the dense deployment case, 0.7 channel gain oriented with maxmin channel gain oriented with maxavg and 40 m for the sparse deployment case. The link reliability 0.65 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 requirement is Relth = 90%. The nominal system parameters Data sub−channels usage ratio are listed in Table II. Fig. 3. Link reliability versus the sub-channel usage ratio in dense deployment with the shared-spectrum allocation scheme A. Impact of Sub-channel Usage Ratio on Link Reliability B. Impact of Sub-channel Usage Ratio on Capacity Figure 2 shows the reliability probability against the data sub-channel usage ratio ρ with the exclusive-spectrum alloca- Figure 4 shows the capacity against the data sub-channel us- tion, where dsf = 20 m. This figure shows that the femtocell- age ratio ρ in the exclusive-spectrum scheme, where dsf = 20 to-femtocell interference significantly impacts the link relia- m. In this figure, when fBS uses more data sub-channels with bility probability. As the sub-channel usage ratio increases, a larger ρ in the random selection scheme, the femtocell user the link reliability probability decreases due to the increas- can yield higher capacity. Noteworthily, because the macrocell ing interference from other fBSs. Compare to the random does not interfere with the femtocell, the femtocell can use selection scheme, the developed distributed channel selection more sub-channels to sent data with a required link reliability. schemes has better link reliability. In this example, under Besides, the channel-gain oriented scheme can yield higher the link reliability requirement Prel ≥ 90%, the maximum capacity than other selection schemes since it can select the allowable channel usage ratio of the random selection scheme sub-channels with higher link gain. In this case, if the link is 0.5. However, the developed channel selection schemes can reliability requirement Prel ≥ 90% is given, the channel-gain increase the maximum channel usage ratio to 0.6. oriented scheme with ρ = 0.6 can achieve 42% higher capacity Figure 3 illustrates the reliability probability for various ρ, than the random selection scheme with ρ = 0.5. where dsf = 20 m. We consider the shared-spectrum allo- Figure 5 shows the femtocell capacity for various ρ in the cation scheme and two-tier interference. Compared to Fig. 2, shared-spectrum allocation scheme, where dsf = 20 m. It is this figure shows that the interference from mBS remarkably shown that the macrocell-to-femtocell interference degrades degrades the link reliability. For example, the link reliabil- the femtocell capacity remarkably. Since the macrocell in- ity probability for the random channel selection scheme at terferes with the femtocell, the femtocell have to use fewer ρ = 0.5 decreases by 8% as the macrocell and femtocells share sub-channels to ensure link reliability. In this situation, the the same spectrum. However, the proposed channel selection interference-avoidance oriented scheme is preferred, because schemes still can improve the link reliability. In the figure, it can effectively decrease interference and improve capacity. the sub-channel usage ratio ρ for the random selection scheme In this case, under the link reliability requirement Prel ≥ 90%. should be less than 0.2 to meet the link reliability requirement the interference-avoidance oriented scheme for ρ = 0.4 can Prel ≥ 90%. Nevertheless, the proposed channel selection achieve 121% higher capacity than the random selection schemes can use twice sub-channels for data transmission. scheme for ρ = 0.2.
  • 5. 8 P ≤ 0.9 0.96 rel ≥γ ) 7 th 0.94 eff 6 Success Probability (CINR Capacity (Mbps) 0.92 5 0.9 Prel ≤ 0.9 4 0.88 3 random random interference avoidance oriented with minmax 0.86 interference avoidance oriented with minmax interference avoidance oriented with minavg interference avoidance oriented with minavg 2 channel gain oriented with maxmin channel gain oriented with maxmin channel gain oriented with maxavg 0.84 channel gain oriented with maxavg 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Data sub−channels usage ratio Data sub−channels usage ratio Fig. 4. Capacity versus the sub-channel usage ratio in dense deployment Fig. 6. Link reliability versus the sub-channel usage ratio in sparse with the exclusive-spectrum scheme deployment with the shared-spectrum allocation scheme 7 12 Prel ≤ 0.9 6 10 P ≤ 0.9 rel Capacity (Mbps) 8 Capacity (Mbps) 5 Prel ≤ 0.9 4 6 3 4 random random interference avoidance oriented with minmax interference avoidance oriented with minmax 2 interference avoidance oriented with minavg 2 interference avoidance oriented with minavg Prel ≤ 0.9 channel gain oriented with maxmin channel gain oriented with maxmin channel gain oriented with maxavg channel gain oriented with maxavg 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Data sub−channels usage ratio Data sub−channels usage ratio Fig. 5. Capacity versus the sub-channel usage ratio in dense deployment Fig. 7. Capacity versus the sub-channel usage ratio in sparse deployment with the shared-spectrum allocation scheme with the shared-spectrum allocation scheme C. Impact of Femtocell Density both the femtocell-to-femtocell and the macrocell-to-femtocell Figure 6 illustrates the reliability probability against the interference significantly degrade the link reliability. We de- data sub-channel usage ratio ρ in the sparse deployment velop channel-gain oriented and interference-avoidance ori- case (i.e., dsf = 40 m) with the shared-spectrum allocation. ented channel selection principles to improve capacity and This figure shows that the channel-gain oriented selection link reliability. Simulation results show that the developed scheme can improve the link reliability, compared to the channel selection scheme can achieve at most 121% higher interference-avoidance oriented selection scheme. In a wireless capacity than the random selection scheme, under the link system, the link reliability is strongly related to the receive reliability requirement Prel ≥ 90%. It is also shown that the SINR. To improve the link reliability, we should decrease the interference-avoidance oriented selection scheme is suitable interference and/or increase the signal power. As the separation for the situation with higher interference to improve link distance dsf of fBSs increases, the interference from other reliability. In addition, the channel-gain oriented selection fBSs is reduced. In this situation, increasing signal strength can scheme can be used to enhance capacity for the case with improve the link reliability more significantly than reducing lower interference . the interference. Because the channel-gain oriented selection scheme can select the sub-channel with higher link gain to R EFERENCES enhance signal strength, it achieves better link reliability. [1] H. Claussen, L. T. W. Ho, and L. G. Samuel, “An overview of the Figure 7 llustrates the capacity for various ρ in the sparse femtocell concept,” Bell Labs Technical Journal, vol. 13, pp. 221–245, 2008. deployment case with the shared-spectrum allocation. It is [2] S. Yeh, S. Talwar, S. C. Lee, and H. Kim, “Wimax femtocells: a perspec- shown that the channel-gain oriented selection scheme can tive on network architecture, capacity, and coverage,” Communications achieve higher capacity than other schemes due to higher Magazine, IEEE, vol. 46, pp. 58–65, 2008. [3] H. Zeng, C. Zhu, and W. P. Chen, “System performance of self-organizing link gain. In this example, compared to the random selection network algorithm in wimax femtocells,” in WICON, Maui, Hawaii, USA, scheme with ρ = 0.6, the channel-gain oriented scheme with Nov. 17–19, 2008. ρ = 0.8 can improve capacity by 23% under the link reliability [4] Usage Models, IEEE 802.11n Working Group, IEEE 802.11-03/802r14, March 2004. requirement Prel ≥ 0.9. [5] Indoor MIMO WLAN Channel Models, IEEE 802.11n Working Group, IEEE 802.11-03/162r2, July 2003. [6] Simulating the SUI Channel Models, IEEE 802.16 Working Group, IEEE VI. C ONCLUSION 802.16.3c-01/53, April. 2001. [7] CINR measurement using EESM method, IEEE 802.16 Working Group, In this paper, we develop the distributed channel selection IEEE 802.16e-05/141r3, April 2005. principle to ensure the link reliability and improve capacity in the OFDMA-based femtocell systems. In the femtocells,