Utility Based Scheduling and Call Admission Control for Long Term Evolution Networks

Transcription

1 Journal of Computer Scence 2012, 8 (12), ISSN do: /cssp Publshed Onlne 8 (12) 2012 ( Utlty Based Schedulng and Call Admsson Control for Long Term Evoluton Networks 1 J. Vay Frankln and 2 K.Paramasvam 1 Faculty of Informaton and Communcaton Engneerng, Anna Unversty of Technology Combatore, TamlNadu, Inda 2 Department of Electroncs and Communcaton Engneerng, Bannar Amman Insttute of Technology, Sathyamangalam, TamlNadu, Inda Receved , Revsed ; Accepted ABSTRACT In ths study, we propose to desgn a call admsson control algorthm whch schedules the channels for Real tme and non-real tme users. In Long Term Evoluton (LTE) 3GPP Networks, several works were done on call admsson control but these works rarely consders schedulng of resources to the real tme and non-real tme users.when the system meets traffc orented performance degraton, maxmum resources are utlzed for load balancng and to mantan the consstent qualty. In order to avod the channel degradaton and mprove the Qualty of Servce (QoS), the call requests are classfed nto New Call (NC) request and Handoff Call (HC) request and the type of servces are classfed as VoIP and vdeo. Then based upon the Receved Sgnal Strength (RSS) value, the channel s estmated as good channel or bad channel. Resource allocaton s made for VoIP users based on traffc densty. Then non-voip users and the non-real tme users are allocated resource blocks usng the channel condton based margnal utlty functon. When there are no suffcent resources to allocate, t allocates the resources of bad channel users there by degradng ther servce. We have desgned the network topology wth G (n) and B (n) for representng the avalable good and bad channels. We nvestgate the performance degradaton when the real tme, Non real Tme, vdeo and VOIP envronments based on RSS threshold value.comparson s made wth the VOS n terms of the paramenters lke throughput,bandwdth,delay,farness and rate. Our proposed method provdes good performance and qualty.from our smulaton results we show that ths admsson control algorthm provdes channel qualty and prortzes the handover calls over new calls whch allocates resources to all knds of users. Key words: CBR, CAC, Long Term Evoluton (LTE), Qualty of Servce (QoS) 1. INTRODUCTION 1.1. Introducton-Long Term Evoluton (LTE) Networks LTE s homogeneous to 3GPP. When compared to the current rado access technologes, the newly evolved rado access technology (LTE or super 3G) s capable of provdng equvalent servce wthout exceedng the current fxed lne accesses n an economc way. The data rate and the spectral effcency of LTE can be ncreased effectvely due to the nvolvement of Orthogonal Frequency Dvson Multple Accesses (OFDMA) and Multple-Input Multple-Output (MIMO) technologes (Bae et al., 2009) Desgn Goals of LTE New and advanced moble broadband servces can be provded to LTE snce they are capable of provdng hgher data throughput to moble termnals. Below are few obectves of LTE When compared to the 3G evoluton lke HSDPA and enhanced uplnk, LTE provdes sgnfcantly Correspondng Author: J. Vay Frankln, Faculty of Informaton and Communcaton Engneerng, Anna Unversty of Technology Combatore, TamlNadu, Inda 2025

2 hgher data rates up to 100 Mb/s and 50 Mb/s for the downlnk and uplnk respectvely Related to the 3GPP Release 6 (Rel-6) systems, three to four tmes hgher average throughput need to be provded by LTE. Also, two to three tmes hgher cell-edge throughput should be provded by LTE compared to the HSDPA or enhanced uplnk. The spectrum effcency of LTE needs to three tmes more effcent compared to current standards LTE needs to provde a sgnfcant reduced control and user plane latency such that user plane RAN round-trp tme s lesser than 10 ms and channel setup delay s lesser than 100 ms The cost of operator and end user should be reduced effcently (Atayero et al., 2011) Relocaton nto other frequency bands can be smoothly provded by usng spectrum flexblty and by facltatng deployment n dfferent spectrum allocatons. The cellular technologes such as GSM and IS-95 are the second Generaton (2G) systems operatng n a dfferent frequency 1.3. Call Admsson Control n LTE Networks The enodeb n LTE provdes bass for the admsson control algorthm and s capable of operatng separately on a per cell bass (Spaey et al., 2010). Congeston avodance s the man am of CAC scheme whch lmts the number of ongong connectons n the system or denes new connecton request so that QoS can be mantaned and delvered to dfferent connectons at the target level.the below two condtons need to be satsfed n the CAC algorthm n order to admt the user to the network (Antonopoulos and Verkouks, 2010) Good Sgnal Strength Snce enb provdes maxmum sgnal, the moble selects ths node and shortage n coverage can be caused when sgnal goes below a certan threshold. The moble may get blocked n ths stuaton Resource Avalablty n the Selected enb Huge amount of physcal resources between a mnmum and maxmum threshold are provded by the moble. Avalable resources are checked by the enb once the ntal condton s checked. Call gets blocked once the enb goes below a mnmum resource threshold Schedulng n LTE Networks In LTE systems, there are three man groups n schedulng algorthms whch ncludes persstent schedulng algorthm group, the dynamc and the sempersstent one. In the persstent schedulng algorthm the persstent scheduler assgnments to the UEs are predefned. So durng DL perod and when the enb assgned resources to them, the UEs need to lsten to a group of predefned resources. There s no necessty to specfy UEs for every DL perod n ths knd of schedulng whch seems to be a maor advantage. Here the UEs can fnd the assgned RBs and the knd of modulaton and codng scheme used s dentfed. But n the dynamc schedulng scheme, the schedulng decsons are taken for every DL perod. The CQI feedbacks from the UEs are consdered for schedulng decsons and there are chances for DL to change to other perod (Parruca and Abt, 2011). Types of schedulng algorthms n LTE ncludes: Max-Prod Schedulng Algorthm Max_Sum Schedulng Algorthm Round Robn-Max_Sum Schedulng Algorthm Mult Groups- Max_Sum Schedulng Algorthm The users can be scheduled n two dmensons namely tme and frequency whch s consdered as the key feature of packet schedulng n LTE networks. For resource management, the aggregate bandwdth avalable s dvded n subcarrers of 15khz. A sub channel wth a bandwdth of 180khz can be formed by groupng twelve consecutve subcarrers (Dmtrova et al., 2010) Problem Identfcaton and Proposed Soluton In our prevous work (Frankln and Paramasvam, 2012) we have proposed call admsson control algorthm for LTE networks. The call requests are classfed nto Handoff Call (HC), New Call (NC), VoIP call and Vdeo type and prortzed. After the classfcaton of the call requests, the channel estmaton technque s based on the Receved Sgnal Strength (RSS) value. When a call request arrves to the network, t s checked for HC or NC. If t s a HC, then t s handled frst by the scheduler. After classfyng the call as HC or NC, the scheduler checks for ts class. If t s a VoIP call, then ts bandwdth requrement s checked. If t s less than total avalable bandwdth, the bandwdth can be reserved based on the traffc densty of the base staton. For vdeo calls, f the requested bandwdth meets the remanng avalable bandwdth, t can be admtted. If there are multple vdeo call requests, then the Tolerance of Latency (TOL) of each call s checked. The call wth low TOL can be admtted frst. 2026

3 1.8. Related Work Dmtrova et al. (2011) have dscussed the mutual nterference schedulng and nter-cell nterference has on each other. It has been dscussed that the partcular servce polcy used by the scheduler s the bass for nter cell nterference pattern. The mpact of nter-cell nterference on user performance at flow level s examned n ths study. Dmtrova et al. (2011) have presented a performance comparson of two dstnct schedulng schemes for LTE uplnk (far fxed assgnment and far work-conservng) takng nto account both packet level characterstcs and flow level dynamcs due to the random user behavor. Pro et al. (2010) have proposed a novel two-level schedulng algorthm. At the upper level, dscrete tme lnear control theory s the bass for ths novel approach. A proportonal far scheduler s customzed at the lower level. The performance and the complexty of the proposed scheme have been evaluated both theoretcally and by usng smulatons. Makara and Ventura (2011) have proposed a scheme that s optmzed for offerng mproved qualty of servce for a dverse mx of traffc ncludng real-tme VBR traffc n the downlnk of LTE networks. The applcaton qualty of servce requrements can be satsfed and the overall system throughput can be mproved n ths algorthm usng multuser dversty. The average delay experenced by the real tme packets n network needs to be mnmzed and the users n the sub channels whch experence the best lnk qualty are scheduled n order to mply hgher data rates. Yaacoub and Dawy (2011) have proposed a prcngbased power control scheme was n the presence of BS cooperaton. The nterference mtgaton schemes were mplemented n conuncton wth a low complexty schedulng algorthm. 2. MATERIALS AND METHODS 2.1. Resource Block Allocaton for Non VoIP Users We consder B resource blocks for each TTI for K moble users whch are servced by an enodeb. Among these users, W users run an applcaton wth actve connecton to a server. Ths server s connected to the packet data network whch s connected to enodeb. Ths system ncludes the followng parameters: d: D: t: The average data rate acheved by the th user at a tme t when a schedulng decson s to be made. The mnmum requred data rate for the th user at t. The playback delay threshold for the th user; maxmum allowable tme before the user s head of lne packet n ts queue can be delvered. brb(): Number of resource blocks allocated to the tme varable bt rate user n one TTI. bn rb (): Number of resource blocks allocated to a non real-tme user. η : The effectve data rate of the th user computed from the utlty functon of all the subcarrers (as f the user was allocated the whole of the system s avalable band). The number of resource blocks allocated to real tme VBR users s then s determned as: 1 d µ T D B rb() =. B µ+λ W 1 W d n= 1 n= 1 Tn D (1) In Eq. 1 the resource blocks for real tme user are assgned wth the ratos of d and D wth respect to tme of th user.the network s operator assgns the parameters µ and λ. These parameters are selected such that the rato sgnfes the amount of real tme users flowng through the network and amount of non-real tme users flowng through the network. For non real traffc, the followng rule s appled n the determnaton of resource blocks allocated: d λ η D B(n) rb(). = B W µ+λ ( ηn ) W d n= 1 D m= 1 In Eq. 2 derves the reservaton block B(n) based on the avalablty of the resources n the enodeb. In ths the utlty factor for the subcarrers are determned to formulate the bandwdth reservaton. Few resource blocks may be unallocated snce both the rules have components that are rounded down. In order to mprove the system s overall throughput users wth hghest utlty functon n each block s used for allocatng the remanng blocks (Makara and Ventura, 2011). (2) 2027

4 2.2. Selecton of Utlty Functon For ensurng channel qualty, here we consder the utlty functon wth RSS Hence, the utlty functon used n resource assgnment for real tme and non-real tme users s gven by: Y E ( ρ, δ ) N N sc,n ( N E ( N ρ, )) N δ = sc,n (3) N RSS Where: Y N = Utlty functon of user N E N = Rate ρ N = Transmt power on the subcarrer δ sc, N = Set of subcarrers In Eq. 3 shows the RSS N s the receved sgnal strength acheved by user N over the last T TTIs. The utlty functon s calculated based upon the set of subcarrers, transmt power and the Receved sgnal strength. Margnal utlty calculaton: = ( ( N,C N N ρ, N δ {c}) ( (, )) rb,n N N ρn δ (4) rb,n M Y E Y E In Eq. 4 derves the margnal utlty functon for the sub carrers. In ths δ rb,n = set of resource blocks and the margnal utlty M N,C, represents the gan n the utlty functon Y N when RB c s allocated to user N, compared to the utlty of user N before the allocaton of c (Yaacoub and Dawy, 2011). Algorthm: 3. RESULTS Consder the n user requests {R 1, R 2,.Rn}. Let us consder the user requests wth good channels as G = {G 1, G 2,... G k } and bad channels as B = {B 1, B 2,... Br}, where k, r<n. Among G, handover calls are represented as H = {H 1, H 2,.H m } and new calls as N = {N 1, N 2,.N p }, where m,p<k. Among H, the VoIP calls and the vdeo calls are represented as H v0 = {V 1,V 2, Vq} and H I = {I 1,I 2,... I t } respectvely, where q,t<m. Among H, the real tme users and the Non real tme users are represented as H R ={K 1, K 2,.. K t }and H N = {S 1, S 2, S t } respectvely. Table 1. Smulaton parameters No. of Servers 1 No of agw 1 No of enb 1 No. of UEs 5 Traffc Types CBR, Vdeo and VoIP Traffc Rate 10 to50 kb VoIP Codec GSM.AMR No. of VoIP frames per packet 2 Let necessary RSS condton for satsfyng handover be RSSv and the RSS threshold value be RSS L. Let η A be the total avalable bandwdth, η vot,, η t, η B, be the reserved bandwdth for VoIP, vdeo and bad channel classes, respectvely. Let M N,c be the margnal utlty functon. δ ava, N (c) be the set of avalable users, δ rb, N (c) be the set of resource blocks. c s the user and c-1 s prevous user. we smulate the proposed Utlty Based Schedulng and Call Admsson Control (UBSCAC) scheme usng Network Smulator (NS2) whch s a general-purpose smulaton tool that provdes dscrete event smulaton of user defned networks. We have used the LTE/SAE mplementaton model for NS2 (Qu et al., 2009). The smulaton parameters are gven n Table 1. In the smulaton settngs, we have one server to provde HTTP, FTP and sgnalng servces, one agw to provde HTTP cache and flow control, one enb to provde flow control nformaton and fve UEs.In ths model, ULArQueue s used for uplnk flows n the lnk between UE and enb. For the downlnk flow, (e) n the lnk between enb and UE, DLArQueue s used. For both the lnks, the lnk bandwdth s set as 500kb and lnk delay as 2ms. For the lnk between enb and agw, ULS1Queue s used and for the downlnk between agw and enb, DLS1Queue s used. For both the lnks, the lnk bandwdth s set as 5 Mb and lnk delay as 2ms.For the lnk between the server and agw, a smple DropTal queue s used wth lnk bandwdth as 50Mb and lnk delay as 2 ms.we compare the UBSCAC scheme wth the VBR-Optmsed Scheduler (VOS) scheme (Makara and Ventura, 2011) Case-1 (CBR) 4. DISCUSSION Based on rate: In ths experment, we vary the data sendng rate from kb to measure the receved bandwdth, farness, throughput and delay for the CBR non-real tme traffc. 2028

5 Fg. 1. Rate Vs bandwdth Fg. 4. Rate Vs throughput Fg. 2. Rate Vs delay Fg. 5. Rate VS bandwdth Fg. 3. Rate Vs farness It can be seen from Fg. 1, the receved bandwdth gradually ncreases when the rate s ncreased. We can see that the receved bandwdth of the UBSCAC s hgher then the exstng VOS scheme. From Fg. 2, we can see that the delay of the proposed UBSCAC s less than the exstng VOS scheme. Fgure 3 shows that UBSCAC provdes better performance over VOS when the envronment s n CBR. Fgure 4 shows that throughput of UBSCAC s hgher then exstng VOS scheme. Fg. 6. Rate Vs delay 4.2. Case-2 (Vdeo) Based on rate: In ths experment, we vary the data sendng rate from kb to measure the receved bandwdth, farness, throughput and delay for the Vdeo exponental traffc. From Fg. 5, we can see that the receved bandwdth of the proposed UBSCAC s hgher then the exstng VOS scheme. From Fg. 6, we can see that the delay of the proposed UBSCAC s less than the exstng VOS scheme. 2029

6 from our smulaton results we show that ths admsson control algorthm provdes channel qualty and prortzes the handover calls over new calls whch allocates resources to all knds of users. 6. REFERENCES Fg. 7. Rate Vs farness Fg. 8. Rate Vs throughput Fgure 7 and 8 show the farness and throughput obtaned, respectvely for the UBSCAC and VOS schemes. From the statstcs, t can be seen that, the throughput and farness of both schemes are ncreased, when the rate s ncreased from kb. 5. CONCLUSION In ths study, we have proposed to desgn a call admsson control algorthm whch schedules the channels for Real tme and non-real tme users. The call requests are classfed nto New Call (NC) request and Handoff Call (HC) request and the type of servces are classfed as VoIP and vdeo. Then based upon the Receved Sgnal Strength (RSS) value, the channel s estmated as good channel or bad channel. Resource allocaton s made for VoIP calls based on traffc densty and for vdeo calls, t s done based on the tolerance of lmt. For allocatng resources to other users, utlty functon s calculated based on the channel condton. Then the real tme users and the non-real tme users are allocated resource blocks based upon the hghest margnal utlty functon. When there are no suffcent resources to allocate, t allocates the resources of bad channel users there by degradng ther servce. Thus 1. Antonopoulos, A. and C. Verkouks, Traffc-aware connecton admsson control scheme for broadband moble systems. IEEE Commun. Lett., 14: DOI: /LCOMM Atayero, A.A., M.K. Luka, M.K. Orya and J.O. Iruem, GPP long term evoluton: Archtecture, protocols and nterfaces. Int. J. Inform. Commun. Technol. Res., 1: e/vol1no7/vol1no7_3.pdf 3. Bae, S.J., J.J. Lee, B.G. Cho, S. Kwon and M.Y. Chung, A resource-estmated call admsson control algorthm n 3GPP LTE system. Computatonal Sc. Appl., 5593: DOI: / _22 4. Dmtrova, D.C., H.V.D. Berg, R. Ltens and G. Heenk, Schedulng strateges for LTE uplnk wth flow behavour analyss. Proceedngs of the 4th ERCIM Workshop on emoblty, May 31-31, Lulea, Sweden Dmtrova, D.C., G. Heenk, J.L.V.D. Berg and S. Yankov, Scheduler-dependent ntercell nterference and ts mpact on LTE uplnk performance at flow level. Proceedngs of the 9th IFIP TC 6 Internatonal Conference on Wred/wreless Internet Communcatons, Jun , Sprnger Berln Hedelberg, Span, pp: DOI: / _24 6. Frankln, J.V. and K. Paramasvam, Effcent channel state based call admsson control for non real tme traffc n LTE (3GPP) networks. Int. J. Comput. Sc., 9: Makara, J. and N. Ventura, Downlnk packet schedulng for varable btrate traffc n LTE Networks. Unversty of Cape Town. ers/network_engneerng/187.pdf 2030

7 8. Parruca, E. and C. Abt, Napkn foldng devce. FPO IP Research and Communtes. tml 9. Pro, G., L.A. Greco, G. Bogga, R. Fortuna and P. Camarda, Two-level downlnk schedulng for real-tme multmeda servces n LTE networks. IEEE Trans. Multmeda, 13: DOI: /TMM Qu, Q.L., J. Chen, L.D. Png, Q.F. Zhang and X.Z. Pan, LTE/SAE model and ts mplementaton n NS 2. Proceedngs of the 5th Internatonal Conference on Moble Ad-hoc and Sensor Networks, Dec , IEEE Xplore Press, Fuan, pp: DOI: /MSN Spaey, K., B. Sas and C. Blonda, Selfoptmsng call admsson control for LTE downlnk. IBBT/Unversty of Antwerp. socrates.org/fles/presentatons/socrates_20 10_NGMN%20call%20- %20admsson%20control%20optmsaton.pdf 12. Yaacoub, E. and Z. Dawy, Jont Uplnk schedulng and nterference mtgaton n multcell LTE networks. Proceedngs of the IEEE Internatonal Conference on Communcatons, Jun. 5-9, IEEE Xplore Press, Kyoto, pp: 1-5. DOI: /cc