TRAFFIC TYPES, PROTOCOLS, AND SYSTEM PERFORMANCE IN WIRELESS NETWORKS Richard C. Bernhardt Principal Staff Engineer Motorola Boynton Beach, FL 33426
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often they are not; this is the case when radio spectrum is reused to achieve maximum system capacity, and when more than one application share the same spectrum (e.g., cellular voice service and CDPD). In the case of CDPD, circuit-switched and packet traffic are mixed. Here, both traffic and radio aspects must be considered for both directions of transmission (i.e. , downlink and uplink).[']
INTRODUCTION In the portable and mobile information age, the services delivered to the user will be primarily determined by the user. The radio and wireless network technologies used to deliver these services should enable them, not limit them. Thus, it is necessary to understarid the demands of wireless products, applications, and services from a top-down, layered point of view. The objective of this paper is to discuss how to usefully model the performance of wireless applications and their protocols without having to construct models so detailed in a layer by layer sense as to be impractical.
This paper examines some of the issues encountered in the above situations and suggest a methodology for approaching the complex problem of modeling and simulation of a heterogeneous system of wireless applications in a frequency reuse environme nt .L2lL31
Much of the modeling and performarnce analysis of wireless systems falls into one of two categories: a traffic-based model with minimal incorporation of the characteristics of the wire less channel such as cochannel interference and fading. Or, a physical level model of the channel with concentration on signal waveforms, link characteristics, and media access protocol. Sometimes these approaches are sufficient, but
THE QUA L ITY/TH R 0UGHPUT 5ELATlONSHlP In most wireless telecommunication systems there is a tradeoff between system performance and the quality of service perceived by users and the system operator. Figure 1 illustrates the relationships between independent and dependent variables.
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The customer pool consists of users
into the understanding and design of a wireless information system.
that have voice and/or data ns applications. In eneral, term~nalsare capable of /or non-real time
Figure 2 shows the c o ~ h a n ~ e ~ interference scenario and how cochannel interference occurs in the normal operation of a wireless information network. Two users have active radio links through stations that coincidentally hav same channel assigned to the part of a previously establishe channel assignment plan. Because of path loss characteristics, the transmission of the terminal labeled interferer at the base serving the other user, labeled victim, may exceed a tolerable level and thus cause information loss and service delay.
c depends on service , arrival rates, required
er satisfaction is also related to response time for interactive applications. Each customer, depending on service as a certain expectation of put and delay targets.
Figure 3 shows the signal that gives rise to cochannel interference as a function of time for concurrent cochannel transmissions as they would exist in a heavily utilized system. Independent datagrams, messages, and circuitswitched calls are transmitted by cochannel terminals. Each time a packet, message, or circuit-switched connection begins or ends, it results in transition of the total power on the channel, denoted by X. (For clarity, the signals in Figure 3 are shown as on/off waveforms with the same amplitude. Actual signals would undergo fading from obstructkms, corruption from noise, and have amplitudes at the receiving point that are a function of distance and the propagation environment). The effect on other users sharing that channel is a time variation in interference. Dividing the desired signal power by the total cochannel
Finally, the system operator, in ition to satisfying customers, chieve acceptable utilization of e~uipmentand spectrum to justify ita1 outlays and operating costs.
less services that depend on nnel reuse are subject to oc~annelinterference that varies in e and space according to the d o n and motion of users. Thus, hannel impairments are directly both user behavior and service application characteristics. This can introduce great complexity
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interference power yields the signalto-interference ratio or SII, which can be used as a metric for transmission quality as well as determining the probability of a bit or symbol error for a specific digital modulation.
in Figure 3, i.e., the transmission of datagrams, messages, or the starting and ending of circuitswitched calls. It may be reasonable to assume that users are independent for a large diverse population. Thus, a traffic model based on a input Poisson process of arrivals and departures of transmissions is appropriate.
To assess the performance of a wireless application or specific service, ix model of the transport protocol is required. The complexity of the model must be tolerable to produce a practical simulation program in terms of run-time and flexibility. This requires judgment and intuitnon about what aspects of the model critically affect performaiirce as perceived by the user and system operator.
Figure 4 is a flowchart of a discrete event simulation written. With respect to Figure 4: An elementary event is defined by whether it is an arrival or departure of an application transmission and the type of application. The system state is defined by the state of infrastructure resources, the current signals in the system, and state of all user applications. Protocol processing includes or encapsulates the effect of radio channel impairments.
Protoco1 models must be defined for each type of transport method used: e Datagram e Message 0 Binary file e Real-time voice
CONCLUSION A discrete time simulation of a multiple service wireless network can be constructed to take into account a mix of traffic types and transport protocols. The detail of the lower layers of protocols can be encapsulated or explicitly modeled to the extent necessary or economical to provide a platform for testing wireless services in a trafficdriven frequency reuse envi ro nment
A discrete! event simulation based on Figure 3 is constructed by associating an offered traffic process with each member of a pool of users in the service area. Each user has a service or application type, along with use c:haracteristics. Elementary event types for such a discrete event simulation can be based on the starting and ending of the indivicilual transmissions shown
I
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[I] ‘The Integrated Modeling of o and Traffic Performance for a uency-Reuse Portable Radio stem”, R. C. Bernhardt, Bellcore mposium On Performance deling, May 1990. I Performance in a ncy Reuse Digital Portable , R. C. Bernhardt, ions on Vehicular I. 40, November 1991, pp. 777-785. [3] “Call Performance of a TDMA se”, R. C. Bernhardt, OM, December 2-5,
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