蜂窝无线通信系统地研究英文翻译.doc

wordRESEARCH OF CELLULAR WIRELESS MUNATION SYSTEM一：ConceptionAbstractCellular systems is also called the "village" system. Is all the areas covered by divided into several village, each district the radius of the visual user distribution density in 1 10 km or so. Set up a base station in every munity service for users within the scope of this area. And through the district division to further improve the system capacity.This system by mobile services switching center (MSC), base station (BS) equipment and mobile station (MS) (the user equipment) and the exchange center to the base station of a transmission line, as shown in the figure below. At present in the operation of the 900 MHZ (TACS) first generation mobile munication system simulation system and the second generation mobile munication (GSM) digital system belong to this category.Is the movement of the mobile station exchange center and the public telephone network (PSTN) is what we usually call telephone network is linked together, between the mobile switching center is responsible for the connection between the base station munication, call process, the mobile station (such as mobile phones) and subordinate to the base station to establish contact, by the base station connected to the mobile switching center again, finally access to the public telephone network.Cellular munication systems allow a large number ofmobile usersto seamlessly and simultaneously municate to wireless modemsat fixed basestations usingalimited amount of radio frequency (RF) spectrum.TheRFtransmissions received at the base stations from each mobile are translatedtobaseband, or to a wideband microwave link, and relayed to mobile switchingcenters(MSC), which connect the mobile transmissions with the Public SwitchedTelephoneNetwork (PSTN). Similarly, munications from the PSTN are sentto the basestation, where they are transmitted to the mobile. Cellular systemsemploy eitherfrequency division multiple access (FDMA), time division multipleaccess (TDMA),code division multiple access (CDMA), or spatial division multipleaccess (SDMA).二：IntroductionA wide variety of wireless munication systems have been developed toprovideaccess to the munications infrastructure for mobile or fixed users in a myriadof operating environments. Most of todays wireless systems are based on thecellularradio concept. Cellular munication systems allow a large number ofmobile usersto seamlessly and simultaneously municate to wireless modemsat fixed basestations usingalimited amount of radio frequency (RF) spectrum.TheRFtransmissions received at the base stations from each mobile are translatedtobaseband, or to a wideband microwave link, and relayed to mobile switchingcenters(MSC), which connect the mobile transmissions with the Public SwitchedTelephoneNetwork (PSTN). Similarly, munications from the PSTN are sentto the basestation, where they are transmitted to the mobile. Cellular systemsemploy eitherfrequency division multiple access (FDMA), time division multipleaccess (TDMA),code division multiple access (CDMA), or spatial division multipleaccess (SDMA) .Wireless munication links experience hostile physical channel characteristics,such as time-varying multipath and shadowing due to large objects in thepropagationpath. In addition, the performance of wireless cellular systems tendsto be limited by interference from other users, and for that reason, it is importantto have accuratetechniques for modeling interference. These plex channel conditionsare difficult to describe with a simple analytical model, although severalmodels do provideanalytical tractability with reasonable agreement to measuredchannel data . However, even when the channel is modeled in an analyticallyelegant manner, in thevast majority of situations it is still difficult or impossibleto construct analytical solutions for link performance when error control coding,equalization, diversity, and network models are factored into the link model. Simulationapproaches, therefore, are usually required when analyzing the performanceof cellular munication links.Like wireless links, the system performance of a cellular radio system is mosteffectivelymodeled using simulation, due to the difficulty in modeling a large numberof random events over time and space. These random events, such as the locationofusers, the number of simultaneous users in the system, the propagation conditions,interference and power level settings of each user, and the traffic demandsof each user,bine together to impact the overall performance seen by a typicaluser in thecellular system. The aforementioned variables are just a small samplingof the many key physical mechanisms that dictate the instantaneous performanceof a particular user at any time within the system. The term cellular radio system,therefore, refers to the entire population of mobile users and base stationsthroughout the geographicservice area, as opposed to a single link that connects asingle mobile user to a single base station. To design for a particular system-levelperformance, such as thelikelihood of a particular user having acceptable servicethroughout the system, it is necessary to consider the plexity of multiple usersthat are simultaneously usingthe system throughout the coverage area. Thus, simulationis needed to consider the multi-user effects upon any of the individual linksbetween the mobile and the basestation.The link performance is asmall-scale phenomenon, which deals with theinstantaneouschanges in the channel over a small local area, or small time duration, overwhich the average received power is assumed constant . Such assumptions aresensible in the design of error control codes, equalizers, and other ponents thatserve to mitigate the transient effects created by the channel. However, in order todetermine the overall system performance of a large number of users spread over awide geographic area, it is necessary to incorporate large-scale effects such as thestatistical behavior of interference and signal levels experienced by individual usersover large distances, while ignoring the transient channel characteristics. One maythink of link-level simulation as being a vernier adjustment on the performance ofamunication system, and the system-level simulation as being a coarse, yetimportant, approximation of the overall level of quality that any user could expectat any time.Cellular systems achieve high capacity (e.g., serve a large number of users) byallowingthe mobile stations to share, or reuse a munication channel in differentregions of the geographic service area. Channel reuse leads to co-channel interferenceamong users sharing the same channel, which is recognized as one of themajorlimiting factors of performance and capacity of a cellular system. An appropriateunderstanding of the effects of co-channel interference on the capacity andperformance is therefore required when deploying cellular systems, or when analyzingand designing system methodologies that mitigate the undesired effects ofco-channelinterference. These effects are strongly dependent on system aspects ofthemunication system, such as the number of users sharing the channel andtheirlocations. Other aspects, more related to the propagation channel, such aspath loss,shadow fading (or shadowing), and antenna radiation patterns are alsoimportant in thecontext of system performance, since these effects also vary withthe locations ofparticular users. In this chapter, we will discuss the application ofsystem-levelsimulation in the analysis of the performance of a cellular municationsystem under the effects of co-channel interference. We will analyze a simplemultiple-usercellular system, including the antenna and propagation effects of atypical system.Despite the simplicity of the example system considered in thischapter, the analysispresented can easily be extended to include other features ofa cellular system.三： Cellular Radio SystemSystem-Level Description：Cellular systems provide wireless coverage over a geographic service area by dividingthe geographic area into segments called cells as shown in Figure 2-1. Theavailable frequency spectrum is also divided into a number of channels with a groupof channels assigned to each cell. Base stations located in each cell are equippedwith wireless modems that can municate with mobile users. Radio frequencychannels used in the transmission direction from the base station to the mobile arereferred to as forward channels, while channels used in the direction from the mobileto the base station are referred to as reverse channels. The forward and reversechannels together identify a duplex cellular channel.When frequency divisionduplex(FDD) is used, the forward and reverse channels are split in frequency. Alternatively,when time division duplex (TDD) is used, the forward and reverse channelsare on the same frequency, but use different time slots for transmission.Figure 2-1 Basic architecture of a cellular munications systemHigh-capacity cellular systems employ frequency reuse among cells. This requiresthat co-channel cells (cells sharing the same frequency) are sufficiently farapart from each other to mitigate co-channel interference. Channel reuse is implementedby covering the geographic service area with clusters of N cells, as shownin Figure 2-2, where N is known as the cluster size.Figure 2-2 Cell clustering:Depiction of a three-cell reuse patternThe RF spectrum available for the geographic service area is assigned to eachcluster, such that cells within a cluster do not share any channel . If Mchannelsmake up the entire spectrum available for the service area, and if the distribution ofusers is uniform over the service area, then each cell is assigned M/N channels. Asthe clusters are replicated over the service area, the reuse of channels leads to tiers ofco-channel cells, and co-channel interference will result from the propagation of RFenergy between co-channel base stations and mobile users. Co-channel interferencein a cellular system occurs when, for example, a mobile simultaneously receivessignals from the base station in its own cell, as well as from co-channel base stationsin nearby cells from adjacent tiers. In this instance, one co-channel forward link(base station tomobile transmission) is the desired signal, and the other co-channelsignals received by the mobile form the total co-channel interference at the receiver.The power level ofthe co-channel interference is closely related to the separationdistances among co-channel cells. If we model the cells with a hexagonal shape, asin Figure 2-2, the minimum distance between the center of two co-channel cells,called the reuse distance , is 2-1where R is the maximum radius of the cell (the hexagon is inscribed within theradius). Therefore, we can immediately see from Figure 2-2 that a small clustersize (smallreuse distance ), leads to high interference among co-channel cells.The level of co-channel interference received within a given cell is also dependenton the number of active co-channel cells at any instant of time. As mentioned before,co-channel cells are grouped into tiers with respect to a particular cell of interest.Thenumber of co-channel cells in a given tier depends on the tier order and thegeometryadopted to represent the shape of a cell (e.g., the coverage area of anindividual base station). For the classic hexagonal shape, the closest co-channelcells are located in the first tier and there are six co-channel cells. The secondtier consists of 12 co-channelcells, the third, 18, and so on. The total co-channelinterference is, therefore, the sumof the co-channel interference signals transmittedfrom all co-channel cells of all tiers. However, co-channel cells belonging to the firsttier have a stronger influence on the total interference, since they are closer to thecell where the interference is measured.Co-channel interference is recognized as one of the major factors that limitsthecapacity and link quality of a wireless munications system and plays animportant role in the tradeoff between system capacity (large-scale system issue)and link quality(small-scale issue). For example, one approach for achieving highcapacity (largenumber of users), without increasing the bandwidth of the RF spectrumallocated to the system, is to reduce the channel reuse distance by reducingthe cluster size N of a cellular system.However, reduction in the clustersizeincreasesco-channel interference, which degrades the link quality.The level of interference within a cellular system at any time is random and mustbesimulated by modeling both the RF propagation environment between cells andtheposition location of the mobile users. In addition, the traffic statistics of eachuser andthe type of channel allocation scheme at the base stations determine theinstantaneous interference level and the capacity of the system.The effects of co-channel interference can be estimated by the signal-tointerferenceratio (SIR) of the munication link, defined as the ratio of thepower of the desiredsignal S, to the power of the total interference signal, I. Sinceboth power levels S andI are random variables due to RF propagation effects, usermobility and traffic variation, the SIR is also a random variable. Consequently, theseverity of the effects of co-channel interference on system performance is frequentlyanalyzed in terms ofthe system outage probability, defined in this particular caseas the probability that SIR is below a given threshold . This is 2-2Whereis the probability density function (pdf) of the SIR. Note the distinctionbetween the definition of a link outage probability, that classifies an outagebased on aparticular bit error rate (BER) or Eb/N0 threshold for acceptable voice performance, and the system outage probability that considers a particular SIR threshold for acceptable mobile performance of a typical user. Analytical approaches for estimating the outage probability in a cellular system, as discussed in before, require tractable models for the RF propagation effects, user mobility, and traffic variation, in order to obtain an expression for . Unfortunately, it is very difficult to use analytical models for these effects, due to their plex relationship to the received signal level. Therefore, the estimation of the outage probability in a cellular system usually relies on simulation, which offers flexibility in the analysis. In this chapter, we present a simple example of a simulation of a cellular munication system, with the emphasis on the system aspects of the munication system, including multi-user performance, traffic engineering, and channel reuse. In order to conduct a system-level simulation, a number of aspects of the individual munication links must be considered. These include the channel model, the antenna radiation pattern, and the relationship betw