Soft QoS-based CAC Scheme for WCDMA Femtocell Networks Sang Bum Kang, Young Min Seo, Young Ki Lee, Mostafa Zaman Chowdhury, Won Sik Ko, Mohd Noor Irlam, Sun Woong Choi, and Yeong Min Jang Kookmin University, Korea
[email protected]
Abstract Key features desired from IMT-Advanced network include open architecture for productivity, increased end-user throughput, reduced latency, support for full mobility and end-to-end QoS. A femtocell is a small cellular base station designed for use in residential or small business environments. It connects to the service provider’s network via broadband (such as DSL or cable). The IMT-Advanced networks will make extensive use of femtocell, picocell and microcell technologies to deliver very high data rates in high-usage areas along with macro cells. In this paper, we propose a FMC (Fixed Mobile Convergence) network architecture using a femtocell concept. In this case, we propose a new CAC (Call Admission Control) scheme based on Soft QoS for resource allocation. The proposed scheme can effectively satisfy the QoS requirement. Keywords Femtocell, Soft QoS, FMC, IMS.
1. Introduction Femtocells provide end users with dedicated access to the cellular network in the home environment. The femtocell is a more developed term in the sense that it distributes a number of users within the cellular network. Although every household is equipped with a wire telephone, the use of mobile phones and mobile data in households is steadily increasing. According to a recently survey, the percentage of mobile phone usage inside households is as high as 50 to 60 percentage and 35 percentage of data usage takes place inside households. Hence, the femtocell which considers not only the voice service of existing home-zone service but also data service is appealing approach. The femtocell concept aims to combine fixed-line broadband access with cellular telephony using the deployment of low cost, low power 3G base station in the subscriber’s homes. The most important benefit of the cellular home gateway concept compared to the dual-mode Wi-Fi approach is that no new device is needed. A 3G home gateway must be able to communicate with any standard 3G phone on the market. The usage of data service will increase as a femtocell provides various and high-capacity multimedia services with low price and high efficiency. The picocell and femtocell could be integrated because they use the wireless technology of the Wide Area Network (WAN) system which is the same as the microcell of wireless operators. It is possible because they use the same spectrum. The small cellular stations of the femtocell connected to the broadband router will provide the voice and data services with
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low price and high efficiency of 3G as well as existing 2G. In case of seamless handover, the network needs to manage the handover when devices enter/leave the femtocell coverage. This handover procedure must be transparent to the user, just like for normal cell handover. We propose a new CAC scheme based on soft QoS for femtocell networks. The proposed scheme considers the actual traffic load of each call while the existing CAC considers the allocated bandwidth only. Since the traffic load can abruptly change, we use exponential smoothing. Through exponential smoothing, we can obtain more stable traffic load by estimating current and past traffic load. Thus, the proposed scheme is a promising approach to diverse multimedia services not only for the femtocell networks, but also for other 4G networks such as WCDMA, HSDPA, WLAN, WiMax, and so on. This paper is organized as follows. In Section 2 of the paper, the femtocell network architecture is described. A soft QoS based CAC is described in Section 3. Section 4 of the paper provides numerical results for our proposed CAC. We draw our conclusion in Section 5.
2. Femtocell Architecture The architectures of the picocell and femtocell are installed indoor as a low-powered station, and integrated and connected to the existing Internet and core networks of wireless operators by cable, DSL, optical cable, or similar backhaul technology. Data goes through the public Internet and only the voice traffic goes through the IMS network as shown in Figure 1 which shows the structure of the IMS and SIP-based femtocell. It allows to have the interworking architecture in which protocols are converted through SIP gateway for IMS and it is taken as interworking with PSTN in IMS after going through MGW (Media Gateway) and MGCF (Media Gateway Control Function). Figure 2 based on the structure shown in Figure 1 shows the end-to-end QoS call flow in the IMS and SIP typed femtocell. It is expected not to carry a load because only the voice traffics are handled in IMS network although IMS network is connected to numerous femtocells. Users can have more and various services at a lower price because data are serviced without going through IMS network. As a result, more multimedia services will be introduced to users. In addition, the handovers and capacity of numerous calls in numerous femtocells could be a burden and it could
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cause unexpected requests in DSLAM (DSL Access Multiplexer) which is connected to a number of femtocells and high-speed Internet modems. Therefore, it would be necessary to control as many calls as possible in a limited capacity to provide the users high-capacity multimedia services at their satisfaction level.
is determined by the reserved bandwidth. Let wi be the actually allocated bandwidth of the connection i, respectively. Then, we have wi ≤ ri , where ri is the requested bandwidth by the connection i. In hard QoS scheme, wi = ri . The bandwidth ratio is defined by normalizing the allocated bandwidth by the network to requested bandwidth by the connection, that is, wi ri . The bandwidth ratio is graded from 0 to 1; a value of 1 means that the allocated bandwidth is sufficient to achieve the desired application performance. There is a point called the critical bandwidth ratio which is the value that results in minimum acceptable user-level satisfaction. Let ξ i be the critical bandwidth ratio. To guarantee an acceptable user-level satisfaction of connection i, we have to satisfy the equation,
wi ≥ ζ i . The critical ri
bandwidth ratio depends on the application type. It is known that the critical bandwidth ratio of voice traffic ranges from 0.8 to 0.9 while that of video ranges from 0.6 to 0.8.
Figure 1. Femtocell Architecture
3.2 Soft QoS based CAC Algorithm We introduce a Soft QoS based CAC algorithm. In soft QoS based CAC, when there is not enough bandwidth, we may consider reducing the allocated bandwidth up to ξ i and borrowing its remaining bandwidth for the admitted connections. If we make enough bandwidth for new connection while we continue to provide acceptable user-level satisfaction to all admitted connections, then the new connection can be admitted. Suppose a new connection is arrived and it requests rnew bandwidth. The pseudo codes for the proposed scheme are shown below: Algorithm Existing Soft-QoS-CAC n
1. bremain = residual_bandwidth = C –
Figure 2. Femtocell based IMS&SIP End-to-end QoS Call Flow
∑r
i
i
3. CAC Algorithm 3.1 Soft QoS Soft QoS has been introduced in [6]. Certain QoS applications can tolerate some degree of traffic loss. For adaptive multimedia applications, effective network resource allocation can be achieved by exploiting the robustness of application performance to bandwidth outage. The QoS requirements of adaptive multimedia applications can be conceptually represented by a softness profile that describes the ability of the application to gracefully scale its performance with the available network bandwidth. According to the softness profile, network can allocate less bandwidth to the connection than the requested bandwidth by the connection. The user-level satisfaction of each connection
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2. wnew = rnew * new 3. if wnew i * ri 9. then if wi - i * ri > wnew – Bremain 10. then wi = wi – (wnew – Bremain) 11. Bremain = Bremain + (wnew - Bremain) 12. accept the new connection 13. else wi = ξ i ⋅ ri 14. Bremain = Bremain + (wi - i * ri ) 15. end if 16. end if 17. if i >= n && wnew > Bremain
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18. then reject the new connection 19. end if 20. end for 21.end if
Based on the existing soft QoS, we apply the exponential smoothing method to obtain estimated values and compare them and repeat it until the value requested by new call is satisfied.
3.3 Proposed CAC Algorithm based on Soft-QoS
Algorithm Proposed Soft-QoS-CAC
Hard QoS and soft QoS among the QoS methods do not consider the actual traffic load. It could cause inefficiency of soft QoS because it does not consider the traffic actually used. Yet, the measured traffic that is currently used is not always correct. It is because the traffic load could abruptly increase or decrease at the point of measurement. Exponential smoothing allows to have more accurate values for the current traffic load that can be measured abnormally. Next data can be estimated using the past and current traffic of each call. When the value is smaller than the value of soft QoS applied, Expontial smoothing ensures more aggressive bandwidth application using more flexible calls while providing the same user satisfaction as the existing soft QoS. There is a difference in the exponential smoothing method in the sense that it uses all data from the past and puts changeable weight on the past data. It gives more weight value on the recent data while giving less weight value on the older data. The equations for exponential smoothing are shown as:
1. bremain = residual_bandwidth = C –
n
ST = αXT + (1 - α)ST-1 . ST = αXT + α(1 - α)XT-1 + α(1 – α)2ST-2.
(1) (2)
In the equations, α is the weight value which is between 0 and 1. Exponential smoothing is useful in catching the current value but vulnerable to errors. And the relationship between α and N of moving average is mathematically proven. Therefore, we could get almost the same estimated result as moving average by assigning α value according to the equation, α = 2 / (N + 1).
∑r
i
i
2. wnew = rnew * new 3. ci = wi ’s exponential smoothing 4. if wnew I * ri 10. then if wi - i * ri > wnew – Bremain 11. then wi = wi – (wnew – Bremain) 12. Bremain = Bremain + (wnew - Bremain) 13. accept the new connection 14. else if ri – ci > ri * (1 - i) 15. then Bremain = Bremain + (ri – ci) 16. else wi = ξ i ⋅ ri 17. Bremain = Bremain + (wi - i * ri ) 18. end if 19. end if 20. if i >= n && wnew > Bremain 21. then reject the new connection 22. end if 23. end for 24.end if
4. Numerical Results We will look at the result of numerical analysis which is improved from the soft QoS technique in femtocell-based environment. The test environment requires a regular bandwidth for each call as VoD(Video on Demand) using MPEG-4. It is set to 250kbps and the total capacity to 5Mbps. And the value applied to soft QoS is set to 0.8. Figure 4 shows that our proposed soft QoS can accept more calls than hard QoS and the existing soft QoS scheme because soft QoS takes away bandwidth of all calls. In other words, our proposed scheme can be more reliable to accommodate more calls for the resource allocation. Our proposed soft QoS scheme increases the utilization of total bandwidth. When the value is set to 0.8 in the user satisfaction, the satisfaction level of the 25th call is shown in Figure 6. Sequence number of call in the x-axis means the total 20 calls allowed before soft QoS is applied. Satisfaction ratio stays above 0.8 in the traditional soft QoS. In other words, it ensures a specific level of satisfaction ratio(SR) for ith user. SRi = ( CRequested_i *
) / CReal_i
Figure 3. Proposed Soft QoS Flow chart
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(3)
CRequested_i is 250Kbps, which is the data rate of the initially requested call and the value is set to 0.8 as mentioned above. And CReal_i is the actually measured traffic size of each call.
traffic amount for each call is estimated with consideration of the past and present. The proposed soft QoS scheme using exponential smoothing is a promising approach for CAC.
5. Conclusion
Figure 4. Number of rejected calls according to number of requested call
The existing soft QoS does not consider the actual use of traffic amount. Hence, we propose soft QoS based CAC using exponential smoothing for the prediction models. The results show that the network utilization is higher than the traditional soft QoS and hard QoS. Our proposed scheme could accommodate more calls than the traditional schemes. The proposed soft QoS scheme may decrease the user’s satisfaction level a bit, as the user needs to release some of his bandwidth for other users. However, the proposed scheme increases the overall performance of the system. Thus, the proposed scheme is a promising approach for diverse multimedia resource allocation in the femtocell network environment. Acknowledgment This research was supported by the MIC (Ministry of Information and Communication), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Advancement)” (IITA-2007-(C1090-0603-0019)). This work was also supported by the 2007 research fund of Kookmin University and Kookmin research center UICRC in Korea. REFERENCES
Figure 5. Total throughput
Figure 6. The satisfaction level of 25th call applying soft QoS
But there is a worse case that satisfaction ratio of proposed soft QoS without exponential smoothing is lower than the value. Especially, there is no user satisfaction at all when the instant value measured is too low in proposed QoS scheme without using exponential smoothing. The traffic load actually measured using exponential smoothing is reliable because the
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[1] Yeong Min Jang, “Soft QoS-based Vertical Handover Between cdma2000 and WLAN Using Transient Fluid Flow Model,” ICOIN2005, LNCS3391, Feb. 2005. [2] ip.access white paper, 3G femtocell Architecture-the evolution to IMS [3] OVUM, “3G home gateways: opportunities and challenges,” January 2007. [4] 3GPP2 S.R0126-0, “System Enhancements for Femto and Pico Cells,” July 2007. [5] Young Min Seo and et al., “Network Composition and Soft QoS Scheme for Heterogeneous Networks,” Wireless Broadband World Forum 2007, Oct. 2007. [6] D. Reininger, “Soft QoS Control in the WATMnet Broadband Wireless System,” IEEE Personal Communication, Feb. 1999. [7] PicoChip, Wireless Communication System Solution, Feb. 2007. [8] 3GPP TR R3.020 V0.1, “Home (e)NodeB; Network aspects,” 2007. [9] A Kineto White Paper, “UMA: The 3GPP standard for Femtocell-to-Core Network Connectivity,” Aug . 2007. [10] Tatara System, “Mobile Service Convergence Accross Networks and Devices,” 2006. [11] Kineto Wierelss, ”The case for UMA-Enable Femtocell,” Jan. 2007. [12] Sonus networks, The Rationale, Characteristics and Technical Approaches to Integrating Fixed and Mobile Wireless Networks [13] AIRVANA, Femto Cells: Personal Base Stations [14] Peter Jarich, “ Femto Fray: The What and Why of Femtocells,” Oct. 2006. [15] 3GPP TS23.228 v7.6.0 “IP Multimedia Subsystem (IMS); stage 2(R7),” Feb. 2006. [16] Sung H. Kim, Yeong M. Jang, “Soft QoS-Based Vertical Handover Scheme for WLAN and WCDMA Networks Using Dynamic Programming Approach”, CIC 2002, LNCS 2524, 2003.
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