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蜂窝无线通信系统的研究英文翻译

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郑州轻工业学院

本科毕业设计(论文)

——英文翻译

题 目 蜂窝无线通信系统的研究 学生姓名 耿永鹏 专业班级 信息工程07-1班 学 号 200707070111 院 (系) 计算机与通信工程学院 指导教师(职称) 张娜(讲师) 完成时间 2011 年 5 月 30日

英文原文

RESEARCH OF CELLULAR WIRELESS COMMUNATION

SYSTEM

Abstract

Cellular communication systems allow a large number of mobile users to seamlessly and simultaneously communicate to wireless modems at fixed base stations using a limited amount of radio frequency (RF) spectrum. The RF transmissions received at the base stations from each mobile are translated to baseband, or to a wideband microwave link, and relayed to mobile switching centers (MSC), which connect the mobile transmissions with the Public Switched Telephone Network (PSTN). Similarly, communications from the PSTN are sent to the base station, where they are transmitted to the mobile. Cellular systems employ either frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA), or spatial division multiple access (SDMA).

1 Introduction

A wide variety of wireless communication systems have been developed to provide access to the communications infrastructure for mobile or fixed users in a myriad of operating environments. Most of today’s wireless systems are based on the cellular radio concept. Cellular communication systems allow a large number of mobile users to seamlessly and simultaneously communicate to wireless modems at fixed base stations using a limited amount of radio frequency (RF) spectrum. The RF transmissions received at the base stations from each mobile are translated to baseband, or to a wideband microwave link, and relayed to mobile switching centers (MSC), which connect the mobile transmissions with the Public Switched Telephone Network (PSTN). Similarly, communications from the PSTN are sent to the base station, where they are transmitted to the mobile. Cellular systems employ either frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA), or spatial division multiple access (SDMA) .

Wireless communication links experience hostile physical channel characteristics, such as time-varying multipath and shadowing due to large objects in the propagation path.

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In addition, the performance of wireless cellular systems tends to be limited by interference from other users, and for that reason, it is important to have accurate techniques for modeling interference. These complex channel conditions are difficult to describe with a simple analytical model, although several models do provide analytical tractability with reasonable agreement to measured channel data . However, even when the channel is modeled in an analytically elegant manner, in the vast majority of situations it is still difficult or impossible to construct analytical solutions for link performance when error control coding, equalization, diversity, and network models are factored into the link model. Simulation approaches, therefore, are usually required when analyzing the performance of cellular communication links.

Like wireless links, the system performance of a cellular radio system is most effectively modeled using simulation, due to the difficulty in modeling a large number of random events over time and space. These random events, such as the location of users, the number of simultaneous users in the system, the propagation conditions, interference and power level settings of each user, and the traffic demands of each user,combine together to impact the overall performance seen by a typical user in the cellular system. The aforementioned variables are just a small sampling of the many key physical mechanisms that dictate the instantaneous performance of 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 stations throughout the geographic service area, as opposed to a single link that connects a single mobile user to a single base station. To design for a particular system-level performance, such as the likelihood of a particular user having acceptable service throughout the system, it is necessary to consider the complexity of multiple users that are simultaneously using the system throughout the coverage area. Thus, simulation is needed to consider the multi-user effects upon any of the individual links between the mobile and the base station.

The link performance is a small-scale phenomenon, which deals with the instantaneous changes in the channel over a small local area, or small time duration, over which the average received power is assumed constant . Such assumptions are sensible in the design of error control codes, equalizers, and other components that serve to mitigate

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the transient effects created by the channel. However, in order to determine the overall system performance of a large number of users spread over a wide geographic area, it is necessary to incorporate large-scale effects such as the statistical behavior of interference and signal levels experienced by individual users over large distances, while ignoring the transient channel characteristics. One may think of link-level simulation as being a vernier adjustment on the performance of a communication system, and the system-level simulation as being a coarse, yet important, approximation of the overall level of quality that any user could expect at any time.

Cellular systems achieve high capacity (e.g., serve a large number of users) by allowing the mobile stations to share, or reuse a communication channel in different regions of the geographic service area. Channel reuse leads to co-channel interference among users sharing the same channel, which is recognized as one of the major limiting factors of performance and capacity of a cellular system. An appropriate understanding of the effects of co-channel interference on the capacity and performance is therefore required when deploying cellular systems, or when analyzing and designing system methodologies that mitigate the undesired effects of co-channel interference. These effects are strongly dependent on system aspects of the communication system, such as the number of users sharing the channel and their locations. Other aspects, more related to the propagation channel, such as path loss, shadow fading (or shadowing), and antenna radiation patterns are also important in the context of system performance, since these effects also vary with the locations of particular users. In this chapter, we will discuss the application of system-level simulation in the analysis of the performance of a cellular communication system under the effects of co-channel interference. We will analyze a simple multiple-user cellular system, including the antenna and propagation effects of a typical system. Despite the simplicity of the example system considered in this chapter, the analysis presented can easily be extended to include other features of a cellular system.

2 Cellular Radio System

System-Level Description:

Cellular systems provide wireless coverage over a geographic service area by dividing

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the geographic area into segments called cells as shown in Figure 2-1. The available frequency spectrum is also divided into a number of channels with a group of channels assigned to each cell. Base stations located in each cell are equipped with wireless modems that can communicate with mobile users. Radio frequency channels used in the transmission direction from the base station to the mobile are referred to as forward channels, while channels used in the direction from the mobile to the base station are referred to as reverse channels. The forward and reverse channels together identify a duplex cellular channel. When frequency division duplex (FDD) is used, the forward and reverse channels are split in frequency. Alternatively, when time division duplex (TDD) is used, the forward and reverse channels are on the same frequency, but use different time slots for transmission.

Figure 2-1 Basic architecture of a cellular communications system

High-capacity cellular systems employ frequency reuse among cells. This requires that co-channel cells (cells sharing the same frequency) are sufficiently far apart from each other to mitigate co-channel interference. Channel reuse is implemented by covering the geographic service area with clusters of N cells, as shown in Figure 2-2, where N is known as the cluster size.

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