Advanced wireless networks 4g technologies phần 9 ppt

JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 MULTITIER WIRELESS CELLULAR NETWORKS 683 parameters. TSC * = TSC max m max 1 =  TSC max /γ 1  a 1 = 3 √ 2λ 0 1 /2 a 2 = 3 √ 2λ 0 2 /2 b 1 = (3 + 2 √ 3)V 1 /9μ 1 b 2 = (3 + 2 √ 3)V 2 /9μ 2 c =  2 √ 3A/9 while (m min 1 ≤ m 1 ≤ m max 1 ) do R 1 = c/ √ m 1 λ 1 = a 1 R 2 1 h 1 = b 1 /R 1 while (1 ≤ C 1 < C) do N 1 =  C 1 / f 1  N 2 =  ( C − C 1 ) / f 2  P L (1) = { [ λ 1 (1 + h 1 )]/[μ 1 (1 + 9h 1 ) ] } N 1 /N 1 !  N i j=0 { [ λ 1 (1 + h 1 )]/[μ 1 (1 + 9h 1 ) ] } j /j! for (k = 1;; k++) do m 2 = 1 + 3k(k +1) TSC = γ 1 m 1 + γ 2 m 1 (m 2 − 1) if (TSC > TSC * ) then break R 2 = R 1 / √ m 2 λ 2 = a 2 R 2 2 h 2 = b 2 /R 2 P L (2) = { [ λ 2 (1 + h 2 )]/[μ 2 (1 + 9h 2 ) ] } N 2 /N 2 !  N 2 j=0 { [ λ 2 (1 + h 2 )]/[μ 2 (1 + 9h 2 ) ] } j /j! PLT = λ 0 1 P L (1) + λ 0 2 P L (2) λ 0 1 + λ 0 2 if (PLT < PLT max ) and [P L (1) < P max L (1)] and [P L (2) < P max L (1)] then break end for JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 684 NETWORK DEPLOYMENT if (TSC < TSC * ) then ˆ k = k m ∗ 1 = m 1 m ∗ 2 = m 2 R ∗ 1 = R 1 R ∗ 2 = R 1 / √ m 2 C ∗ 1 = C 1 C ∗ 2 = C − C 1 end if end while end while The outputs are: TSC ∗ , m ∗ 1 , m ∗ 2 , R ∗ 1 , R ∗ 2 , C ∗ 1 and C ∗ 2 . 17.3.2 Performance example To generate numerical results, a system with the parameters shown in Table 17.1 is used [21]. The performance of the two-tier system is compared with that of a one-tier system. To obtain results for a one-tier system the optimization algorithm with R 1 = R 2 was run. This results in both tiers sharing the same cells and m 2 = 1. The total cost is then computed as TSC = m 1 γ 1 . Table 17.1 Example system parameters Parameter Value/range Units A 100 km 2 C 90 Channels S 2 λ 0 1 0.23.0 Calls/(min km 2 ) λ 0 2 5.040.0 Calls/(min km 2 ) μ 1 , μ 2 0.33 Calls/min γ 1 10.0 $ (in 1000 s)/base γ 2 1.0 $ (in 1000 s)/base V 1 30540 km/h V 2 1.512.0 km/h f 1 , f 2 3 TSC max 10 000–20 000 $ (in 1000 s) PLT max 0.01 P max B ( * ) 0.01 P max D ( * ) 0.01 JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 LOCAL MULTIPOINT DISTRIBUTION SERVICE 685 0 200 400 600 800 1000 1200 0 41012 Average tier 2 mobile speed (km/h) Total system cost ($1000s) Two-tier system One-tier system 2 6 8 Figure 17.12 Comparison of the total system costs between the one-tier and two-tier systems, λ 0 1 = 1[calls/(min km 2 )] and λ 0 2 = 20[calls/(min km 2 ).] Figure 17.12 depicts the total system cost as a function of tier 2 mobile speed, while tier 1 mobile speed is fixed for one-tier and a two-tier systems. The tier 1 mobile speeds considered are 30, 90, 180, 270, 360 and 540 km/h. The main conclusion from Figure 17.12 and many other similar runs [21] is that, for the parameter ranges used in this study, the two-tier system outperforms the single-tier system for all the values of the slower and faster mobile speeds. 17.4 LOCAL MULTIPOINT DISTRIBUTION SERVICE Wireless systems can establish area-wide coverage with the deployment of a single base station. The local multipoint distribution service (LMDS) offers a wireless method of access to broadband interactive services. The system architecture is considered point-to-multipoint since a centralized hub, or base station, simultaneously communicates with many fixed subscribers in the vicinity of the hub. Multiple hubs are required to provide coverage over areas larger than a single cell. Because of the fragile propagation environment at 28 GHz, LMDS systems have small cells with a coverage radius on the order of a few kilometers. Digital LMDS systems can flexibly allocate bandwidth across a wide range of bi-directional broadband services including telephony and high-speed data access. Multiple LMDS hubs are arranged in a cellular fashion to reuse the frequency spectrum many times in the service area. Complete frequency reuse in each cell of the system is attempted with alternating polarization in either adjacent cells or adjacent hub antenna sectors within the same cell. Subscriber antennas are highly directional with roughly a 9 inch diameter (30–35 dBi) to provide additional isolation from transmissions in adjacent cells and to reduce the received amount of multipath propagation that may cause signal degradation. Since cells are small and the entire spectrum is reused many times, the overall system capacity is quite high, and backhaul requirements can be large. Backhaul networks will probably be a combination of fiber-optics and point-to-point radio links. JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 686 NETWORK DEPLOYMENT The system capacity comes mainly from the huge radio frequency (RF) bandwidth avail- able: blockA, 1150 MHz(27.50–28.35, 29.100–29.250 and31.075–31.225 GHz); andblock B, 150 MHz (31.000–31.075 and 31.225–31.300 GHz). For the purpose of frequency plan- ning for two-way usage it is essential to solve the problem of LMDS spectrum partitioning for the upstream and downstream. The standard duplexing options, frequency-division du- plex (FDD) and time-division duplex (TDD), are applicable in LMDS too and will not be discussed here in any more detail. Instead, as a wireless point-to-multipoint system, the deployment of LMDS will be assessed by the basic parameters of cell size and capacity. Obviously, an operator would want to cover as large an area as possible with a minimum number of cell sites, hence maximizing cell size. The modulation and coding, and the ensu- ing E b /N 0 , are factors in determining cell size. However, because of high rain attenuation at LMDS frequencies, there is a major trade-off between cell size and system availability determined by the rain expectancy for a given geographical area. In most of the United States, for the forthright aim of providing ‘wireless fiber’ availability of 0.9999–0.99999, the cells would only be between 0.3 and 2 miles [23]. Consequently, the deployment of LMDS will extensively involve multicell scenarios. In the following we review the meth- ods of optimizing system capacity in these scenarios through frequency reuse. The main problem related to frequency reuse is the interference between different segments of the system. Therefore, patterns that create bound and predictable values of S/I are essential to device deployment. Frequency reuse and capacity in interference-limited systems have been discussed in previous sections for mobile cellular and personal communications ser- vices (PCS) systems. As the basic methods and principles also apply to fixed systems, there are several major differences in the treatment of fixed broadband wireless systems such as LMDS. Unlike mobile cellular, in LMDS the subscriber antennae are highly directional and point toward one specific base station. This, together with the nonmoving nature of the subscriber, results in much lower link dynamics. The channel can mostly be described as Rician (with a strong main ray) and not Rayleigh-like in mobile cellular. Since the subscriber employs directive antennae, it is compelled to communicate with only one base station, which excludes the use of macro diversity (or cell diversity) – a very beneficial method with mobile cellular, but one that complicates the interference and frequency reuse analysis. Also, mobile cellular service was originally intended for voice; therefore, it is designed for symmetric loading, while broadband wireless services generally have more downstream traffic than upstream. This reflects in the main issue of concern for interference study, which in PCS and mobile cellular is upstream interference because the base station receiver has the hard task of receiving from a multitude of mobiles transmitting through nondirectional antennae and suffering different fast fading. In LMDS the upstream is usually lower-capacity and employs lower-order modulation, which offers better immunity. Also, the slower fading environment allows a closed-loop transmission power control system to operate relatively accurately. Consequently, upstream most subscribers transmit at a power lower than nominal, unlike the downstream transmis- sion. Also, the narrow beam of their antennae is an interference-limiting factor. Therefore, downstream interference is the most problematic, as opposed to the mobile cellular case. Another parallel with mobile cellular refers to cellular patterns. Owing to the mobile nature of its subscribers, a mobile cellular system has to provide service from the start to a JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 LOCAL MULTIPOINT DISTRIBUTION SERVICE 687 whole area (town, region), with a large number of adjacent cells. The number of sectors is relatively low (2–4); otherwise, the mobile would go through frequent handoffs. In LMDS, in the long run, owing to the small cell size, the ever increasing hunger for bandwidth and the availability of radio and networking technologies, deployment is also expected to be blanket coverage. However, the economics of LMDS do not require this from the beginning. Operators will probably first offer the service in clusters of business clients with high data bandwidth demands and with the financial readiness for the new service, and later will gradually expand the service to larger areas. Second, the sectorization will be in denser patterns determined by the increasing demand for bandwidth and not limited by the requirement for handoff. The narrower sectors employing higher antenna gain in the base station also provide for larger cell size. Frequency reuse in one cell isillustrated in Figure 17.13 with threeexamples of frequency reuse by sectorization. The first step in frequency planning is to assume the division of the available spectrum into subbands, so adjacent sectors will operate on different subbands. Also, the sector structure has to be designed as a function of the capacity required and the S/I specification of the modem used. The need to divide into subbands is a function of base station antenna quality, specifically the steepness of the rolloff from the main lobe to sidelobes in the horizontal antenna pattern. If the antenna sidelobes roll off very steeply after the main lobe, it is possible to reuse the frequency every two sectors, resulting in patterns of the type A, B, A, B, . . . , as in Figure 17.13(b). In this context the reuse factor, F R ,isthe number of times the whole band is used in the cell, which for the simplified regular patterns is the number of sectors divided by the number of subbands; in this case F R = 3. In a more conservative deployment the frequency is reused only in back-to-back sectors as in Figure 17.13(a), which has six sectors with reuse pattern A, B, C, A, B, C. Figure 17.13(c) shows a higher-capacity cell where the pattern A, B, C, . . . , is repeated in 12 sectors, resulting in F R = 4. Obviously, to keep the equipment cost low, we want a low number of sectors; schemes where we divide the spectrum in as few subbands as possible (two is best). With present antenna technology at 28 GHz it is possible to achieve sidelobes under −33 dB, but the radiation pattern of the deployed antenna is different. The sidelobes are significantly higher because of scattering effects such as diffraction, reflection or dispersion caused by foliage. The very narrow beamwidth of the subscriber antenna (which at 28 GHz can be reasonably made 3 ◦ or lower) helps limit the scattering effect. Obviously, the sum of such effects depends on the millimeter-wave effects in the specific buildings and terrain in the area, and have to be estimated through simulation and measurements for each particular case. Another uncertain factor in the estimation of S/I is thefading encountered by the direct signal. As a starting assessment, we shall consider the above-mentioned effects accountable for increasing the equivalent antenna sidelobe radiation to −25 dB. Based on this, the following estimations of S/I are only orientative. For each particular deployment the worst case has to be estimated considering the particular conditions. 17.4.1 Interference estimations To allow A, B, C, . , type sectorization, in Figure 17.13(a) and (c) the base station antenna sidelobe is α =−25 dB at an angle more than 2.5 B 3dB from boresight, where B 3dB is the −3dB beamwidth (the main lobe is between ±0.5 B 3dB ). In Figure 17.13(a) and (b), JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 688 NETWORK DEPLOYMENT F R = 4 F R = 3 F R = 2 A A A A B B B B C C C C A A B CC B AB BA x y B A Sub 1 Sector 1 A A A A B B B B C C C C A A B B AB BA x y B A (a) (b) (c) Figure 17.13 Cells with reuse factors of 2, 3 and 4. B 3dB = 60 ◦ , while in Figure 17.13(c) B 3dB = 30 ◦ . In Figure 17.13(b), better-quality anten- nas are considered, which would achieve the same sidelobe rejection at 1.5 B 3dB , driving frequency reuse higher for the same number of sectors. 17.4.2 Alternating polarization Figure 17.14(a) shows how a high reuse factor of 6 can be achieved in 12 sectors by alternating the polarity in sectors. The lines’ orientations show the polarization, horizontal (H) or vertical (V). The amount of discrimination that can be achieved depends on the environment. Although the antenna technology may provide for polarization discrimination of 30–40 dB, we shall consider that the combination of depolarization effects raises the cross-polarization level to p =−7 dB. The interference is reduced, so thesame frequency at the same polarizationcomes only in the fourth sector. The problem is that a deployment has to allow for gradual sectorization – start by deploying minimum equipment, then split into more sectors as demand grows. However, if alternating polarization is employed in sectors, the operator would have to visit the subscriber sites in order to reorient the antennas. A more conservative approach would be to set two large areas of different polarity, as in Figure 17.14(b). This does not reduce the close-in sidelobes but reduces overall interference and also helps in the multiplecell design. JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 LOCAL MULTIPOINT DISTRIBUTION SERVICE 689 F R = 4 F R = 6 (a) (b) Figure 17.14 Twelve-sector cells with cross-polarization. Following is an approximation for the S/I: S I = S  i I i + N R = S  i α i S i +  j p j α j S j + N R (17.23) where S i are the transmission powers in other sectors using the same subband, I i the interferers, and N R the receiver input noise. Later the case will be considered where all transmission powers in sectors are equal to S i = S, and, N R is neglected. N 1 and N 2 are the number of sectors with the same polarization and the cross-polarized ones, respectively. As well, the worst case values α and p will be taken for the sidelobe gains and cross- polarization: S I = 1 α(N 1 + N 2 p) . (17.24) Thus, in a first approximation [24], by applying Equation (17.24), the S/I level (or co-channel interference, CCI) at the subscriber receiver is given in Table 17.2. The type of modulation and the subsequent modem S/I specification have to be specification have to be Table 17.2 The S/I level at the subscriber receiver Figure 17.13(a) Figure 17.13(b) Figure 17.13(c) Figure 17.14(a) Figure 17.14(b) S/I in dB 25 22 20 22 25 JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 690 NETWORK DEPLOYMENT specified with sufficient margin. A modem receiver operates in a complex environment of challenges of which the S/I or CCI is only one. Other impairments such as equalizer errors, adjacent channel interference, phase noise and inter-modulation induced by the RF chain limit the S/I with which the modem can work in the real operation environment. The above technique can be extended to multiple cell scenario. Details can be found in Roman [24]. 17.5 SELF-ORGANIZATION IN 4G NETWORKS 17.5.1 Motivation Self-organisation is an emerging principle that will be used to organise 4G cellular networks [25–40]. It is a functionality that allows the network to detect changes, make intelligent decisions based upon these inputs, and then implement the appropriate action, either mini- mizing or maximizing the effect of the changes. Figure 17.15 illustrates a multitier scenario where numerous self-organizing technologies potentially could be applied. Frequency planning discussed so far in this chapter was performed by choosing a suitable reuse pattern. Individual frequencies are then assigned to different base stations according to propagation predictions based on terrain and clutter databases. Global cell Microcells Macrocells Base station bunchingRadio resource management Intelligent handover Intelligent relaying Dynamic charging Picocells Self-organization Adaptive cell sizing Situation awareness Figure 17.15 Multitier scenario with self-organising technologies. JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 SELF-ORGANIZATION IN 4G NETWORKS 691 The need to move away from this type of frequency planning has been expressed in the literature [28] as well as being emphasized by ETSI in the selection criteria for the UMTS air–interface technique. The main reason for this departure is the need for very small cell sizes in urban areas with highly varying morphology, making traditional frequency planning difficult. Another reason lies in the difficulty associated with the addition of new base stations to the network, which currently requires extensive reconfiguration. In view of these two arguments, a desirable solution would require the use of unconfigured base transceiver stations (BTSs) at all sites; these BTSs are installed without a predefined set of parameters and select their operating characteristics on the basis of information achieved from runtime data. For instance, they may operate at all the available carriers and select their operating frequencies to minimize mutual interference with other BTSs [28]. The increasing demand for data services means that the next generation of communi- cation networks must be able to support a wide variety of services. The systems must be location- and situation-aware, and must take advantage of this information to dynamically configure themselves in a distributed fashion [29]. There will be no central control strategy in 4G, and all devices will be able to adapt to changes imposed by the environment. The devices are intelligent and clearly employ some form of self-organization [30, 31]. So far in our previous discussion, coverage and capacity have been the two most important factors in cellular planning. To have good coverage in both rural and urban environments is important so as to enable customers to use their terminals wherever they go. Coverage gaps mean loss of revenue and can also lead to customers moving to a different operator (which they believe is covering this area better). On the other hand, some areas may not be economically viable to cover from the operator’s point of view due to a low population density. Other locations, for instance a sports stadium, may only require coverage at certain times of the day or even week. Capacity is equally important. Without adequate capacity, users will not be able to enter the network even though there might be suitable coverage in the area. Providing the correct capacity in the correct location is essential to minimize the amount of infrastructure, while ensuring a high utilization of the hardware that has actually been installed. Based on the traffic distribution over the duration of a day reported in Lam et al. [32], an average transceiver utilizationof only35 % has beenestimated. Improving this utilizationis therefore of great interest. A flexible architecture is essential to enable the wide variety of services and terminals expected in 4G to co-exist seamlessly in the same bandwidth. In addition, future upgrades and reconfigurations should require minimum effort and cost. The initial investment, the running costs and the cost of future upgrades are expected to be the three most important components in determining the total cost of the system. 17.5.2 Networks self-organizing technologies Capacity, both in terms of bandwidth and hardware, will always be limited in a practical communication system. When a cell becomes congested, different actions are possible. The cell could borrow resources, bandwidth or hardware, from a neighboring cell. It could also make a service handover request to a neighbor in order to minimize the congestion. Thirdly, a service handover request could be made to a cell in a layer above or below in the hierarchical cell structure. Finally, the cell could try to reduce the path loss to the mobile JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 692 NETWORK DEPLOYMENT terminal to minimise the impact of other cell interference. If neighboring cells are unable to ‘assist’ the congested cell, the options left for the cell are to degrade the users’ service quality (if it is interference limited) or to try and influence the users’ behavior. This can be achieved through service pricing strategies. The pricing scheme can be regarded as a protection mechanism for the network. Since it cannot create capacity, only utilise what it already has, it needs to force the users to adapt their behavioral pattern until the network is upgraded or there is more capacity available. Self-organizing technologies fall into one of these categories. 17.5.2.1 Bunching of base stations In a micro- and picocellular environment there will be severe fluctuations in traffic demand, user mobility and traffic types. This highly complex environment will require advanced radio resource management (RRM) algorithms and it will be beneficial to have a central intelligent unit that can maximize the resource utilization. The bunch concept has been proposed as a means to deal with this issue. It involves a central unit (CU) that controls a set of remote antennas or base stations (which have very little intelligence). The central units will deal with all decisions on channel allocation, service request and handover. Algorithms for layers 1 and 2 (such as power control) may be controlled by the remote unit itself. The bunch concept can be viewed simply as a very advanced base station with a number of small antennas for remote sensing. The central unit will therefore have complete control over all the traffic in its coverage area and will be able to maximize the resource utilization for the current traffic. This provides opportunities for uplink diversity and avoids intercell handovers in its coverage area. The bunch approach will typically be deployed in city centres, large buildings or even a single building floor. 17.5.2.2 Dynamic charging The operators need to encourageusers to utilizethe network more efficiently, somethingthat can be achieved through a well thought-out pricing strategy. Pricing becomes particularly important for data services such as e-mail and file transfer as these may require considerable resources but may not be time-critical. A large portion of e-mails (which are not time- critical) could, for example, be sent during off-peak hours, hence improving the resource utilization. In this area two main approaches are used, user utility method and maximum revenue method. User utility algorithms assume that the user associates a value to each service level that can be obtained. The service level is often referred to as the user’s utility function and it can be interpreted as the amount the user is willing to pay for a given quality of service. It is assumed that the user acts ‘selfishly’, always trying to maximize their own utility (or service). The whole point with a pricing strategy is to enable the operator to predict how users will react to it, something which is not trivial. Current proposals do not try to determine the exact user’s utility function, but rather to postulate a utility function which is based on the characteristics of the application or service. Two prime examples are voice and data services, which exhibit very different characteristics. Although speech applications are very sensitive to time delays, they are relatively insensitive to data errors. Similarly, although data services are relatively insensitive to time delays, they are very sensitive to data errors. [...]... 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In most of the United States, for the forthright aim of providing wireless fiber’ availability of 0 .99 99 0 .99 999 , the cells would only be between 0.3 and 2 miles [23]. Consequently, the. (MIB). The MIB functions as Advanced Wireless Networks: 4G Technologies Savo G. Glisic C  2006 John Wiley & Sons, Ltd. 699 JWBK083-18 JWBK083-Glisic February 23, 2006 5: 59 Char Count= 0 700 NETWORK. 1, 199 9 pp. 47– 59. JWBK083-17 JWBK083-Glisic February 23, 2006 5:36 Char Count= 0 696 NETWORK DEPLOYMENT [21] A. Ganz, C.M. Krishna, D. Tang and Z.J. Haas, On optimal design of multitier wireless cellular