Uplink Channel Allocation Scheme and QoS Management Mechanism for Cognitive Cellular- Femtocell Networks

Transcription

1 62 Uplink Channel Alloation Sheme and QoS Management Mehanism for Cognitive Cellular- Femtoell Networks Kien Du Nguyen 1, Hoang Nam Nguyen 1, Hiroaki Morino 2 and Iwao Sasase 3 1 University of Engineering and Tehnology, Vietnam National University Hanoi, Vietnam 2 Shibaura Institute of Tehnology, Japan 3 Keio University, Japan, nguyendukien02@gmail.om, hoangnn@vnu.edu.vn, morino@shibaura-it.a.jp, sasase@is.keio.a.jp Abstrat: Cognitive radio and femtoell are promising tehnologies whih an satisfy the requirements of future mobile ommuniations in terms of dynami spetrum sharing and high user density areas. Providing quality-of-servie (QoS) guaranteed realtime servies is hallenging issue of future ognitive ellularfemtoell mobile networks. In this paper, we introdue a user s QoS management mehanism used to protet SINR of maro users from QoS violation aused by femtoell users. We design a novel uplink hannel alloation sheme (denoted as flexible sheme ) for real-time onnetions. The sheme uses the information of interferene level and hannel oupany olleted at ognitive femtoell aess points and their overing maro base station (MBS) and apply relevant seletion riteria to selet an appropriate hannel whih auses the minimums interferene to maro users of the overing MBS. Performane results prove that omparing with femtoell-aess-point (FAP)-based and MBS-based uplink hannel alloation shemes, the novel flexible sheme an provide lower unsuessful probability of new onnetion requests. Keywords: Cognitive radio, femtoell, hannel alloation, interferene management, QoS management, flexible sheme. 1. Introdution Reently, 4th generation (4G) mobile ommuniations has been standardized in whih the 4G mobile ommuniations is able to provide high transmission rate up to 1 Gbps in the downlink and hundreds Mbps in the uplink [1]. A question arises that what the beyond 4G mobile ommuniations (i.e. 4.5G, 5G) will offer to mobile ustomers. Considering the huge number of mobile ustomers, deployment senarios (indoor, outdoor, urban, suburban et.) and appliations (voie, video, Internet servies). It an be foreseen that future mobile ommuniations demands high apaity, intelligent overage and effiient resoure utilization [2] whih will be supported by deploying ognitive ommuniations arhiteture [1]. Despite the high ost of deploying and operating a large number of small ells, femtoell has been proposed as a high effiient solution to inrease indoor overage and apaity [3, 4]. At the beginning, femtoell is onsidered as a lowpower, short-range aess point for indoor environment [4]. Reently, the deployment of femtoell is expanded to outdoor environment where femtoells are used as traditional pio ells [3]. In the deployment, femtoells an be deployed by mobile operators in residential, enterprise and open areas. They will form a so-alled femto subsystem in whih interferene management beomes an important task [3, 4]. Cognitive ellular-femtoell systems were proposed reently in whih maro base stations and ognitive femtoell aess points (CFAP) are onsidered as primary and seondary systems, respetively. CFAPs are assumed to have ognitive funtionalities whih are able to sense the available spetrum and opportunistially onsume it for data transmission [4]. For radio resoure management in ognitive ellularfemtoell networks, reent published papers found in the literature have only foused to solve the problems of opportunisti hannel alloation [4, 5] for data (non realtime servies). Although the demand of providing real-time servies in femtoells is an important issue in future ognitive ellular-femtoell mobile networks, there is no detailed disussion and proposal of hannel alloation for real-time onnetions and QoS management mehanism of both maro users (MUs) and femtoell users (FUs) when providing real-time servies. In this paper, we first introdue a ognitive ellular-femtoell network model used for future mobile ommuniations. Issues of network arhiteture and radio resoure management are introdued and disussed. The uplink interferene management is more diffiult than that of downlink beause interferene management has to take into aount the interferene impats from all uplink soures. That brings hallenges to CFAPs when seleting an uplink hannel for a realtime onnetion request of a FU whih must not violate the QoS of other MUs using the same hannel [6]. In the paper, we propose a novel uplink hannel alloation sheme (denoted as flexible sheme ) for the realtime onnetion requests of ognitive ellular-femtoell networks. When a CFAP reeives a new realtime all request from a FU, by using the flexible sheme, the CFAP firstly tries to alloate a hannel whih is not onsumed by its overing MBS and the hannel has the minimum interferene level at the CFAP. If there is not any hannel satisfying the two requirements or the hannel QoS requirement of the FU, the CFAP will selet a hannel whih is onsumed by its overing MBS and has minimum interferene level measured at its overing MBS. After that, we investigate and ompare the performane of different uplink hannel alloation shemes for the ognitive ellular-femtoell network model.

2 63 Performane of three hannel alloation strategies are evaluated inluding FAP-based ognitive hannel alloation proposed by [5], MBS-based ognitive hannel alloation presented in [7] and the proposed flexible ognitive hannel alloation. We also present a QoS management mehanism and a hannel verifiation proedure whih are used in order to eliminate the problems of QoS violation in ognitive ellular-femtoell networks. The paper is organized as follows: the system model and onepts of physial layer QoS management are desribed and disussed in the next setion. QoS management mehanism and hannel verifiation proedure are presented in Setion 3. The next setion desribes seleted hannel alloation shemes inluding the novel sheme. Simulation model and parameters inluding standardized path loss models are desribed in setion 5. Performane omparison is presented and disussed in setion 6. Finally, the onlusion remarks are given in the last setion. 2. System model Femtoell was first proposed for overing small indoor areas. Reently, the deployment of femtoell is also proposed for outdoor overage in partiular senarios suh as in publi areas, in high density user loations e.g. airports, parks [3]. In urrent femtoell arhiteture, femtoells operate at frequenies whih are randomly seleted. Maro base station (MBS) Mobile RAN Management System Mobile Core Network (CS, PS, IMS) Closed Aess Femto Zone Cognitive Femto Aess Point (CFAP) Open Aess Femto Zone Internet Femto Management System Femto Gateways Figure 1. Cognitive ellular-femtoell network model for beyond 4G mobile ommuniations Fig. 1 shows a two-tier ognitive ellular-femtoell network model whih we onsider as a andidate for beyond 4G mobile ommuniations. In the ellular domain, we do not aim to fous on any speifi air interfae tehnologies beause the model is used as a general system model only. In this model, a CFAP an form a losed aess femto zone in whih only authorized/registered users an aess to the CFAP. In this senario CFAP operates equivalently as a private indoor aess point like a Wi-Fi devie. One or a number of CFAP an form an open aess femto zone whih aepts aess requests made by authentiated users. This senario is applied in publi loations e.g. shopping enters, airports, railway stations. Deploying CFAPs with small overage size aims to not only inrease the signal quality of mobile users but also redue the ross-tier interferene beause the transmission power of mobile users is dereased. In the sope of this paper, we investigate the methods in whih CFAPs perform uplink hannel alloation to new realtime all requests of FUs in the senario of fixed users. Assume that MBSs and CFAPs use the same frequeny range in whih MBSs operate as the primary system. Both of MBSs and CFAPs have ognitive funtionalities inluding spetrum sensing or hannel quality sensing. Cognitive radio reently is onsidered effetive for opportunisti aess [8] in whih hannels are alloated to seondary users in a ertain short period. However, real-time ommuniations have strit QoS requirements and normally, the hannel alloated to a real-time onnetion has to be available in a long period. That rises to the need of how to alloate stable spetrum/hannel to real-time onnetions. In the network model, we assume that a MBS will be able to interat with CFAPs whih are loated in the overage area of the MBS in order to exhange the urrent information of spetrum utilization of the overing MBS. By using ognitive funtionalities and interating with their overing MBS, CFAP monitors the interferene level of all hannels in order to selet the most appropriate hannel whih is satisfying the QoS of FUs while not violating QoS of MUs. We assume that Femto Management System (FMS) and Mobile RAN Management System (MRMS) are two ontrol entities. Control messages and information exhanged between these entities are transmitted via the ore network of ellular domain and the Internet so that they will not onsume the limited wireless radio resoure. The interation between these two entities is for supporting mobility management and radio resoure management by exhanging important information suh as the hannel usage ondition of MBSs or CFAPs. When we onsider the ase that a user moves between femto zones or between a femto zone to MBS s zone, the user needs the supports of loation update and onnetion handover. FMS and MRMS have to be able to support handover proedures suh as handover deision, ell seletion and resoure alloation. The FMS and MRMS also should be oordinated in radio resoure management. When a CFAP reeives a new real-time all request from a FU, it has to alloate radio resoure (hannel) to the FU. As MUs are onsidered as primary users whose QoS must be guaranteed [9], the CFAP has to selet the hannel whih auses minimum effets to the MUs of the overing MBS [3, 4]. In the sope of the paper, we aim to design an effetive uplink hannel alloation for new real-time all requests as it is more ompliated than downlink hannel alloation. Extension of the uplink hannel alloation sheme for handover all request is another diffiult task for future studies as handover management whih will have to onsider different senarios (ellular to femtoell, femtoell to femtoell). Regarding to QoS metri, we onsider the QoS metri at the physial layer. Regularly, QoS of an appliation means delay and throughput. In mobile ommuniations, in order to provide guaranteed throughput to a real-time

3 64 onnetion, the signal quality of mobile user must have a ertain signal-to-interferene and noise ratio (SINR) level. The SINR level of eah appliation type (voie, video, and data) is onsidered as the physial layer QoS (from now on denoted for short as QoS). SINR of a mobile user measured at MBSs or CFAPS is used as uplink QoS. Clearly, when a CFAP reeives a new all request from a FU, it should selet a hannel whih satisfies FU s SINR while not ausing strong interferene to other MUs using same hannel. In the next setion, we will introdue a QoS management mehanism and its hannel verifiation proedure. 3. QoS management mehanism FU CFAP FMS MRMS MBSs Call Request Call Reply Channel alloation Waiting for the verifiation reply Connetion verifiation QoS Verifiation Request QoS Verifiation Reply Waiting for a time out period QoS Verifiation Request QoS Verifiation Reply QoS Control Inquiry QoS Control Reply Figure 2. QoS management mehanism: hannel verifiation proedure Admission ontrol inluding the hannel alloation proedure and QoS management mehanism are illustrated in Fig. 2. In the figure, ontrol message exhanges are shown as blak lines, while ontrol proesses are shown in retangle bloks. When a new all request of a FU arrives to a CFAP, the CFAP first performs a hannel alloation sheme to alloate a hannel to the FU. In order to guarantee that QoS of ongoing onnetions of MUs is not violated, a QoS management mehanism inluding a hannel verifiation proedure is applied. The CFAP performs the hannel verifiation proedure to hek if the QoS of a MU, whih is onsuming the same hannel is violated. The new all request is onsidered unsuessful in two ases: either there is not available hannel or the alloated hannel auses QoS violation to a MU. After alloating a hannel k to a new all request, CFAP sends a verifiation request to the FMS to verify if the QoSs of other MUs using the hannel k are violated. The FMS forwards the verifiation request to the MRMS and waits for a time out period. The MRMS sends QoS ontrol inquiry to MBSs, whih are the overing MBS of the CFAP and neighbors of the overing MBS. If a MU using hannel k has QoS violation, the MBS overing of this MU will send QoS ontrol reply to MRMS. The MRMS forwards the QoS ontrol reply to the FMS. Then the FMS sends the QoS verifiation reply to the CFAP and terminates the time out period. While the CFAP is waiting for the verifiation reply, the FU is temporarily onneted with the CFAP and transmits probe signals. In the ase of there is not QoS violation at MUs, the CFAP permanently aepts the FU and alloates the hannel k to the FU. Otherwise, the CFAP will terminate the onnetion and also onsider that the realtime all request is unsuessful. In the next setion, we will desribe three hannel alloation shemes: FAP-based ognitive hannel alloation sheme [5], MBS-based ognitive hannel alloation sheme and the proposed flexible hannel alloation sheme whih alloates hannels to new realtime all requests aording to interferene data measured at both CFAPs and MBSs. 4. Channel alloation shemes Channel alloation shemes operate as desribed below under following assumptions. Assume that the ognitive ellular-femtoell network uses a pool of C orthogonal hannels for real-time onnetions. In a MBS or a CFAP, at any given time, a hannel is alloated to only one ongoing MU or one ongoing FU, respetively. MUs are primary users for whih a ertain physial layer QoS is guaranteed (as mentioned above, we onsider the QoS parameter is the required SINR). When a CFAP alloates a hannel to a FU, it first has to provide the required QoS of the FU. However, the FU must not ause the QoS degradation of the MUs whih are using the same hannel. Assume that updating the uplink interferene level of MBSs and the QoS of MUs is performed by the interation/information exhange of MRMS and FMS. Moreover the hannel alloation shemes in CFAP are performed after updating information from overing MBS. If the QoS of a MU is violated beause a new FU has been aepted to the network, the overing CFAP of the FU will be informed and then it an either try to alloate another hannel to this FU or to blok the FU s onnetion request. Operational proedures of three seleted hannel alloation shemes are as follows. 4.1 FAP-based ognitive hannel alloation sheme [5] In the FAP-based ognitive hannel alloation sheme (denoted as CFAP-based sheme), eah CFAP will measure the interferene level of all available hannels whih are not alloated to ongoing FUs of the CFAP. When a CFAP j reeives a onnetion request from an FU, it will selet the hannel k whih satisfies two riteria: 1) it is unused by any FUs of the CFAP and 2) it has the minimum interferene level, as desribed in Equation (1) below. k = arg min( I ),1 C (1) where I j j is the total interferene level of hannel is measured at the CFAP j. The interferene level of all hannels measured at the CFAP j is updated periodially. After being assigned a hannel k, the FU transmits a probe signal using an initial transmission power P i. Its SINR is measured by this equation: SINR = k Prj (2) + noise I k j

4 65 where k Pr j is the power reeived from the user at CFAP j. If the SINR of the probe signal by FU measured at the CFAP does not satisfy the FU s QoS, the CFAP asks the FU to perform a power ontrol proess. The power ontrol will omplete either when the FU s QoS is satisfied or the maximum transmission power of the FU is assigned. In the ase of the FU s QoS is still not satisfied after ompleting the power ontrol proess, the CFAP will release the alloated hannel k and onsider that the all request is not suessful or unsuessful. Otherwise, the CFAP alloates the hannel to the FU and then performs the hannel verifiation proedure as illustrated in Fig MBS-based ognitive hannel alloation sheme [7] When using the MBS-based ognitive hannel alloation sheme (denoted as MBS-based sheme), the ognitive ellular-femtoell network needs more frequent information exhange between the MRMS and FMS. A CFAP periodially updates interferene data of all hannels measured at its overing MBS. A MBS periodially sends a broadast paket to all CFAPs loating in its overage. This paket an be sent from the MBS to CFAPs via a broadasting hannel or through the ommuniations between MRMS and FMS. The paket ontains interferene information of all hannels measured at the MBS. When the CFAP reeives a onnetion request of a FU, it will selet the hannel k* whih satisfies two riteria: 1) it is unused by other ongoing FUs of the CFAP and 2) it has the k * minimum interferene level I M measured at the overing MBS M of the CFAP, as desribed in Eq. (3) below. k * = arg min( I ),1 C (3) M where I M is the total interferene level of hannel whih is measured at the overing MBS M of the CFAP. Seleting a hannel aording to Eq. (3) leads to minimize uplink interferene to the overing MBS of the CFAP. The hannel verifiation proedure is then performed similarly. 4.3 Flexible sheme of ognitive hannel alloation When performing simulation experiments, we realized that the CFAP-based sheme will loally assign a hannel k whih auses minimum interferene to CFAPs i.e. less effets to the QoS of surrounding FUs. The MBS-based sheme will produe a hannel k* whih auses minimum effet to MU s QoS [7]. Beause femtoell has small overage radius, hannels alloated to FUs often satisfy FUs s QoS. From these observations, we propose a more effetive hannel alloation sheme. We denote it as flexible sheme whih works as follows. Beside updating interferene information of all hannels to all CFAPs as desribed in MBS-based sheme, the overing MBS also send its CFAPs the list of hannels being oupied by MUs at the MBS. Aording to the updated data, a CFAP divides the hannel pool into two sets C 1 and C 2 in whih C= C 1 +C 2. C 1 is the set of the hannels not being used by MUs in the overing MBS, and C 2 is the set of the hannels being used by MUs in the overing MBS. When the CFAP j reeives a new onnetion request of a FU, the flexible sheme operation is desribed in two steps as follows: Step 1: If the set C 1 is empty, go to Step 2. Otherwise, the CFAP j selets the hannel C* whih satisfies three riteria: 1) it belongs to the hannel set C 1 (not being used by the overing MBS), 2) it is not used by other FUs of the CFAP j, and 3) it has the minimum total interferene level C * I j measured at the CFAP j, as shown in Eq. (4) below. C * = arg min( I ), 1 C 1 (4) where I j j is the total interferene level of hannel is measured at the CFAP j. After that, the hannel verifiation proedure introdued in Fig. 2 is performed similarly. If there is a MU of ellular domain (might belong to other neighbor MBSs) whih has QoS violation, the CFAP j will perform the one more attempt of hannel alloation by using Step 2 below. Step 2: The CFAP j will selet the hannel C** whih satisfies three riteria: 1) it belongs to the hannel set C 2, 2) it is not being used by other FUs of the CFAP j and 3) it has C ** the minimum total interferene level I M measured at its overing MBS M. Suh that: C ** = arg min( I ), 1 C 2 (5) M where I M is the total interferene level of hannel measured at the overing MBS M. The hannel verifiation proedure is then performed similarly. The new all request is onsidered unsuessful if the hannel C** does not pass the hannel verifiation. In the next setions, we will present the simulation model used for evaluating and performane omparison of above hannel alloations shemes. The performane metri is unsuessful probability defined below: Unsuessful probability = Number_ Of _ Unsuessful _ Re quest (6) Total _ Request 5. Simulation model The simulation program is developed using Matlab. Simulation senarios use the 7-ell simulation model as shown in Fig. 3. In future work, we will give the 19-ell simulation model for ognitive ellular-femtoell mobile ommuniations networks. In the simulation senarios, we do not are about physial layer model, modulation and oding shemes for ommuniations. We only onsider how CFAPs an alloate hannels to FUs suessfully with our sheme. As mentioned in the last setion, the performane metri is unsuessful probability of onnetion requests whih are alulated following the setion 3.

5 66 Figure 3. Layout of simulation model For more details, the simulation model inludes MBSs that eah MBS provides the ell overage radius of 500m with the antenna height of 30m. In eah maroell (MBS), a number of CFAPs (depending on simulation senarios) is uniformly distributed. MUs and FUs are also uniformly distributed in eah maroell and eah CFAP, respetively. A MBS alloates hannels to its MUs randomly. In the paper, we only onsider stationary MUs and FUs with its antenna the height between 1m and 3m, respetively. The femtoell overage radius is 15m and CFAP has antenna height between 1m to 5m. In all simulation senarios, MBSs and CFAPs manage the same number of uplink hannels N C = 100. Assume that only one uplink hannel is alloated for a MU at whole simulation time. The transmission power range of MUs is between 1mW and 125mW [10] whereas the transmission power of FUs is fixed at 1mW. Additionally, the uplink transmission power of MUs is ontrolled by a power ontrol proess with the SINR target of 3 db [5]. The FU s uplink QoS requirement (SINR) is set to 5dB. The uplink traffi load in eah CFAP is set aording to seleted simulation senarios. Consider CFAPs and FUs are indoor devies whereas MBSs and MUs are outdoor devies. Standardized path loss models used for alulating SINR in femtoell networks [10, 15] are given in Table 1. The signal transmitted between a base station and users an be lassified into four ases: indoor to indoor, indoor to outdoor, outdoor to outdoor and outdoor to indoor links. Cost231-Okumura-Hata is well-aepted by the mobile ellular ommunity. The expression of Cost231 for built-up areas is as follows: L(dB) = log 10 (f) 13.82log 10 (h b ) + ( log 10 (h b )) log 10 (d) F(h m ) + C, (7) With C = 0 db for small to medium-size ities. F(h m ) = (1.1log 10 (f) 0.7) h m (1.56log 10 (f) 0.8), (8) where f is the arrier frequeny [MHz]; h b is the base station height above ground level [m]; h m is the mobile station height above ground level [m]; d is the distane from the base station [km]. ITU P.1411 was designed for the planning of short range outdoor systems. P1411 line-of-sight street anyon method is reommended whih applies to situations where the two terminals are in LOS but are surrounded by buildings. In this paper, we used the lower bound for the path loss using the following expressions: L bp + 20log 10 (d/r bp ) for d R bp L(dB) = (9) L bp + 40log 10 (d/r bp ) for d > R bp, where the breakpoint distane is given by R bp = 4h b h m /λ and the basi transmission loss at the breakpoint distane is given by: L bp (db) = 20log 10 (λ 2 /(8πh b h m )), (10) with λ is the wavelength (m); h m and h b are the base station and the mobile unit s height above street level respetively (m); d is the distane from base station (m). ITU P.1238 predits path loss between two indoor terminals assuming an aggregate loss though furniture, internal walls and doors. The expression for the path loss is given by: L(dB) = 20log 10 (f) + Nlog 10 (d) + L f (n) 28, (11) where N is the distane power loss oeffiient; f is the arrier frequeny [MHz]; d is the separation distane (m) between the base station and portable terminal (where d > 1m); L f is floor penetration loss fator (db); n is number of floors between base station and portable terminal (n 1). In our simulation, we used N = 28, L f (n) = 4n and n = 1 for residential fator. Table 1. ITU path loss models Parameters Values External wall loss 20dB [10] Window loss 5dB [10] Indoor to indoor path loss modeling Indoor to outdoor path loss modeling Outdoor to outdoor path loss modeling Outdoor to indoor path loss modeling Frequeny ITU P.1238 [11] ITU P.1411 [12] + wall/window loss Cost231 [13]-Okumura-Hata [14] for edge of maro ell ases ITU P.1411 [12] for near maro ell ases Cost231[13]-Okumura-Hata [14] for edge of maro ell ases + wall/window loss ITU P.1411 [12] for near maro ell ases + wall/window loss 2000 MHz The ommon simulation parameters are summarized in Table 2 given below. Table 2. Common simulation parameters Simulation parameters Cell layout Values 7 ell model MBS sensitivity -121dBm [10] FAP sensitivity -116dBm [10] MBS overage radius 500m

6 67 FAP overage radius 15m MU transmission power range 1mW to 125mW [10] FU transmission power High range of FU and MU 1mW 1m to 3m High of MBS (h b) 30m [15] High range of FAP (h m) Number of hannel 100 1m to 5m MU s uplink QoS requirement 3dB [5] FU s uplink QoS requirement Indoor to indoor lognormal shadowing standard deviation Indoor to outdoor lognormal shadowing standard deviation Outdoor to outdoor lognormal shadowing standard deviation Outdoor to indoor lognormal shadowing standard deviation 6. Performane omparison 5dB 4dB [4] 12dB [4] 8dB [4] 10dB [4] Following simulation senarios are arried out in whih we ompare the unsuessful probability of hannel alloation shemes under different system onfiguration. Senario 1: The number of CFAPs in eah MBS (CFAPs/MBS) is 10. The maximum number of simultaneous ative FUs on eah CFAP is 10 or the uplink load of CFAPs is 10% of total N C hannels). Senario 2: The number of CFAPs/MBS is inreased to 20. The uplink load of CFAPs is 10%. Senario 3: The number of CFAPs/MBS is 10. The uplink load of CFAPs is inreased to 30%. Figure 4. Unsuessful probability versus number of MUs per maroell where 10 CFAPs/MBS and the uplink load of CFAP is 10% In the first simulation senario, the transmission power of MUs is ontrolled between 1mW and 125mW while the transmission power of FUs is fixed at 1mW. Eah CFAP has the uplink traffi load of 10%. The number of MUs in eah maro ell is varied between 10 and 100. The QoS of FUs is SINR = 5dB. The positions of CFAPs are uniformly distributed around MBS and in MBS s overage. As shown in Fig. 4, the flexible sheme an provide a muh smaller unsuessful probability than that of the CFAP-based and MBS-based shemes. At the MBS s load of 40 ative simultaneous MUs in eah MBS (MUs/MBS), the unsuessful probability of the flexible sheme is less than 1% whereas that of the CFPA-based and MBS-based shemes provide an impratial unsuessful probability of around 10% and 7%, respetively. The flexible sheme shows better performane at higher MBS s load and it an even provide low unsuessful probability of realtime onnetion requests at medium MBS s load (around 55 MUs/MBS). The reason is that when using the flexible sheme, the CFAP first selets the hannel whih has the loal minimum interferene level (at the CFAP) and is not used by ongoing MUs of overing MBS. Thus the CFAP an satisfy FU s QoS and does not ause interferene affeting to MU s QoS. Otherwise, the CFAP selets a hannel whih an be urrently used by the overing MBS but has minimum interferene at the overing MBS. That means it an ause minimum effets to QoS of the MUs onneted with the overing MBS. In this senario, when the number of ative MUs less than 30 (onsidered as a low MBS load), the performanes of MBS-based and CFAP-based shemes are nearly idential whereas the flexible sheme provides very small unsuessful probability. Figure 5. Unsuessful probability versus number of MUs per maroell where 20 CFAPs/MBS and the uplink load of CFAP is 10% In the seond simulation senario, it aims to observe the unsuessful probability of hannel alloation shemes in the ase of the number of CFAPs is inreased to 20 i.e. higher femtoell density while keeping the similar uplink traffi load of 10% in eah femtoell. The QoS of FUs is SINR = 5dB. The transmission power of FUs is set at the fixed value of 1mW and the transmission power of MUs is ontrolled between 1mW and 125mW. The positions of CFAPs are uniformly distributed around MBS and in MBS s overage. As shown in Fig. 5, the flexible sheme still shows smaller unsuessful probability than those of the CFAP-based and MBS-based shemes. Clearly, inreasing the number of CFAPs in the whole system will bring higher unsuessful probability of new realtime onnetion requests. However, at the low MBS s load, the flexible sheme still an keep almost the same unsuessful probability of the first simulation senario. It also shows that CFAP-based sheme offers muh worse performane than that of other shemes. It an ome to a onlusion that when onsidering only loal interferene information (i.e. loal spetrum monitoring), it

7 68 is not possible to provide realtime onnetion requests in ognitive ellular-femtoell mobile networks. Figure 6. Unsuessful probability versus number of MUs per maroell where 10 CFAPs/MBS and the uplink load of CFAP is 30% In the third simulation senario, it aims to ompare the unsuessful probability of hannel alloation shemes in the ase of the uplink traffi load of eah CFAP is 30% i.e. high apaity femtoell while keeping 10 CFAPs in eah MBS. As shown in Fig. 6, the unsuessful probability of all shemes inreases as the uplink traffi load of eah CFAP inreases. The flexible sheme still provides a muh better unsuessful probability than the CFAP-based and MBSbased shemes. In this senario, the flexible sheme an still keep the unsuessful probability less than 5% when the MBS s load reahes 50 simultaneous ative MUs. This figure proves that when CFAP s load of realtime servies inreases, it auses heavy interferene to ative MUs of the overing MBS. That means ognitive ellular-femtoell mobile networks should define a ertain realtime servie load of femtoells. It is an open and interesting researh topi for future study. Figure 7. Performane omparison in the ase of the same number of ative FUs (300FUs) in a maroell The flexible sheme has shown better performane gain omparing with other shemes. Now we evaluate and ompare the performane of the flexible sheme in the ase of the total number of ative FUs of both senarios is idential (300 ative FUs in a maroell). Fig. 7 shows when the uplink load of a CFAP is high (30FUs/CFAP and 10CFAPs/MBS) i.e. CFAPs are high-apaity aess points, the flexible sheme is able to maintain unsuessful probability of 10% when the offer load of the overing MU rises to 62% (62 ative MUs/ MBS). In the senario when the number of CFAPs is high and CFAPs are low-apaity aess points (10FUs/CFAP and 30CFAPs/MBS), the unsuessful probability reahes 10% when the offer loads of the overing MU raises to 46% (46 ative MUs/ MBS). From the olleted performane data, it shows that in ognitive ellular-femtoell mobile networks, deploying high-apaity CFAPs is better than deploying low-apaity CFAPs. Clearly, at theoretial point of view, when reduing the number of CFAPs i.e. low CFAP density there will be fewer CFAPs loating nearby MBSs. Therefore MBSs will have lower uplink interferene. This result is also used as the validation of our simulation tool. Simulation results have statistially demonstrated the effetiveness of the flexible sheme. When analyzing the operation of three hannel alloation shemes, we found that most of unsuessful requests happened beause ongoing MU of the overing MBS has QoS degradation. Following issues an verify the gains of the flexible sheme when omparing with CFAP-based and MBS-based shemes: - When using the CFAP-based sheme, a CFAP alloates to a FU a hannel whih has the minimum interferene measured at the CFAP. But at this time, the hannel an have strong interferene at the overing MBS. Thus the hannel verifiation proedure performed later would not be satisfied. This results in high unsuessful probability. - When using the MBS-based sheme, a CFAP will alloate to a FU a hannel (denoted as Channel-A) whih has minimum interferene measured at the overing MBS. A situation appears that the Channel-A might be onsumed by a MU of the overing MBS while another hannel (Channel-B), whih has higher interferene level measured at the CFAP but is free in the overing MBS. In the ase of the CFAP is nearby the overing MBS, alloating Channel-B is a better solution beause the Channel-B will not violate QoS of ongoing MU of the overing MBS. Also, as the CFAP is nearby the overing MBS i.e. it is far from other MBSs, the hoie of Channel-B will ause less interferene to other MBSs. When alloating the free Channel-B to the FU, this FU does not have interferene from the MU of the overing MBS i.e. better FU s SINR an be ahieved. - When using the flexible sheme, firstly a CFAP will selet a hannel (for a requesting FU) whih belongs to the set of hannels (C 1 ) not being onsumed by the overing MBS and has the smallest interferene (Channel-B) among the set C 1. Alloating this hannel surely will not ause QoS degradation of MUs in the overing MBS. The FU will not have diret interferene aused by MU of the overing MBS. If the CFAP is loated nearby the overing MBS, it will not ause strong interferene to other MBSs. When Channel-B still ause QoS degradation to MUs of neighbor MBSs (due to high system load or the CFAP is in overlap areas of MBSs), the flexible sheme has the seond step to selet a hannel from the set C 2. If the hannel does not have strong interferene level in the neighbor MBSs, it an pass the hannel verifiation proedure.

8 69 In the last simulation experiment, the unsuessful probability of hannel alloation shemes is evaluated in the ases of CFAPs loated nearby the MBS (approximately 50m around MBS). The simulation result shown in Fig. 8 demonstrates our above verifiation. Figure 8. Unsuessful probability versus number of MUs per maroell where CFAPs are loated nearby the MBS (approximately 50m around MBS) 7. Conlusions In this paper, we have presented a feasible ognitive ellularfemtoell mobile network arhiteture where ognitive radio and femtoell deployment are two key aspets whih are expeted to fulfill important requirements of beyond 4G mobile ommuniations in terms of overage and spetrum utilization. We introdue a physial layer QoS management mehanism and proposed a novel uplink hannel alloation sheme denoted as flexible sheme for new realtime onnetion requests. Performane results obtained by omputer simulation show that the proposed flexible hannel alloation sheme outperforms both CFAP-based and MBSbased shemes in terms of low unsuessful probability. In order to ahieve high system apaity and resoure utilization in ognitive ellular-femtoell networks, the interation of MRMS and FMS will play important role. It is suggested that deploying high-apaity CFAPs would bring better performane than deploying low-apaity CFAPs when providing realtime servies. For future works, we would fous on solving tehnial problems appeared in the ase of mobile MUs and FUs. In this ase, high-performane mobility management will be the key for the suess of ognitive ellular-femtoell mobile ommuniations networks. 8. Aknowledgment This work has been supported by Vietnam National University Hanoi (VNU) under the researh projet QG Referenes [1] S. Patel, M. Chauhan, K. Kapadiya, 5G: Future Mobile Tehnology-Vision 2020, International Journal of Computer Appliations, Vol. 54, No. 17, pp. 6-10, Sept [2] S. Patil, V. Patil, P. Bhat, A Review on 5G Tehnology, International Journal of Engineering and InnovativeTehnology (IJEIT), Vol. 1, Issue. 1, pp , January [3] J. G. Andrews, H. Claussen, M. Dohler, S. Rangan, M. C. Reed, Femtoells: Past, Present, and Future, IEEE Journal on Seleted Areas in Communiations, Vol. 30, Issue. 3, pp , April [4] D. C. Oh, H. C. Lee and Y. H. Lee, Cognitive Radio Based Femtoell Resoure Alloation, 2010 International Conferene on Information and Communiation Tehnology Convergene (ICTC2010), pp , Nov [5] Y-y. Li and E. S. Sousa, Cognitive uplink interferene management in 4G ellular femtoells, 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communiations, pp , Sept [6] N. Meghanathan, A Survey on the Communiation Protools and Seurity in Cognitive Radio Networks, International Journal of Communiation Networks and Information Seurity (IJCNIS), Vol. 5, No. 1, April [7] K. D. Nguyen, H. N. Nguyen and H. Morino, Performane Study of Channel Alloation Shemes for beyond 4G Cognitive Femtoell-Cellular Mobile Networks, 2013 IEEE Eleventh International Symposium on Autonomous Deentralized Systems (ISADS), pp. 1-6, Marh [8] S. Tang and Y. Xie, Performane Analysis of Unreliable Sensing for an Opportunisti Spetrum Sharing System, International Journal of Communiation Networks and Information Seurity (IJCNIS), Vol. 3, No. 3, Deember [9] D. T. Ngo, L. B. Le, T. L. Ngo, E. Hossain, and D. I. Kim, Distributed Interferene Management in Femtoell Networks, IEEE Vehiular Tehnology Conferene (VTC Fall) 2011, pp. 1-5, Sept [10] The femto forum, White Paper Interferene Management in UMTS Femtoells, Deember [11] International Teleommuniation Union, ITU R Reommendations P.1238: Propagation data and predition models for the planning of indoor radio ommuniations systems and radio loal area networks in the frequeny range 900MHz to 100GHz, Geneva, [12] International Teleommuniation Union, ITU R Reommendations P : Propagation data and predition methods for the planning of short range outdoor radio ommuniation systems and radio loal area networks in the frequeny range 300 MHz to 100 GHz, Geneva, [13] Commission of the European Communities, Digital Mobile Radio: COST 231 View on the Evolution Towards 3rd Generation Systems, L 2920, [14] Y. Okumura, E. Ohmori, T. Kawano and K. Fukuda, Field strength and its variability in VHF and UHF land mobile radio servie, Rev. Eletr. Commun. Lab., Vol. 16, pp , [15] The femto forum, White Paper Interferene Management in UMTS Femtoells, Deember 2010.