Wireless Channel Characterization for the 5 GHz Band Airport Surface Area ∗
3.1 Introduction
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Wireless Channel Characterization for the 5 GHz
communication link range, optimal channel/subchannel bandwidths, and system performance (bit error ratio, throughput, latency, etc.) for any potential waveform used over the channel [4]. The use of channel models to evaluate transmission and reception schemes at the PHY layer is illustrated in Figure 3.1.
Figure 3.1 can pertain to one or more simultaneously operating wireless links. In this figure, performance requirements of the communica-tion system specify values for parameters of the transmission scheme (e.g., required bit rate, spectral characteristics), and also for the recep-tion scheme (e.g., required packet error probability). For a selected transmission/reception scheme, the performance evaluation metrics can depend upon the channel model(s) used. If the performance evalua-tion outputs indicate the system will meet its requirements, then the system design can proceed on to the higher layers of the protocol stack. If the performance evaluation metrics indicate that the transmission/recep-tion scheme will not meet requirements, then, with knowledge of the channel, appropriate remedies can be added at the transmit (Tx) or receive (Rx) or both ends of the link, and the evaluation repeated.
The physical layer performance characterization is indispensable for the design and performance prediction for higher layers in the communications Figure 3.1 Illustration of use of channel models in evaluation of PHY Tx/Rx schemes.
protocol stack, which depend upon the physical layer for message transfer [5]. The physical layer performance directly affects the data link, MAC, and network layers, and through these, the performance of all higher layers.
Several system PHY and data link layer design parameters upon which the channel characterization has a significant effect include the following [6]:
Modulation(s) and corresponding detection schemes [6] Forward error correction coding and associated interleaving schemes [7] Antenna characteristics, including diversity antenna parameters [8] Receiver processing algorithms, including those for synchronization, interference suppression, combining, and so on, all of which are adaptive [9] Signal bandwidths [4] Adaptation algorithms for resource allocation in time, frequency, and spatial domains [10] Physical facility siting rules [11] Duplexing and multiplexing schemes [9] Security techniques (against eavesdropping, jamming, spoofing, etc.) [12]Accurate channel models contain mathematical descriptions that can be used for analysis, but often analysis becomes intractable, at which point evaluations can be conducted and extended via computer simula-tions [13,14]. Simulasimula-tions are extensively used to assess and design modern communication systems. Thus, the channel model consists not only of mathematical descriptions, but also the“software implementation” of these mathematical descriptions. Ultimately, if a wireless communication system is deployed without a thorough channel characterization, the system will most certainly be suboptimal. Well-known performance limits that can arise from not accounting for channel characteristics include an irreducible channel error rate that can preclude reliable message transfer and severely limited data carrying capacity.
3.1.2 Channel Definitions
A definition for the wireless channel is the set of all parameters for all transmission paths taken by an electromagnetic signal from transmitter to receiver, in a frequency band of interest, over an area (or spatial volume) of interest. These parameters include the amplitude, phase, and delay for each path or component. In general, all parameters can be temporally or spatially varying. This is in contrast to guided wave transmission schemes
(those that use wires, cables, waveguides, light guidefibers, etc.), which are largely time invariant.1
Strictly, one could define as many types of channel models as there are types of communication links. In practice, this is neither desirable – because of complexity – nor necessary – since many channels exhibit similar characteristics. For wireless systems, the channel is not typically under the direct or complete control of the system designer or operator.
For the simplest cases, or for specific well-defined (often time-invariant) environments, the channel can be defined with high accuracy. In this case, models for the channel can be deterministic. In more complex cases, with mobility of Tx and/or Rx and/or objects in the environment, or when a model is to represent a range of environmental conditions, statistical channel models are apt. As with guided wave versus wireless channel models, another classification is deterministic versus statistical models.2 From the perspective of electromagnetic field theory, any wireless channel could be viewed as being purely deterministic, and hence channel characteristics could be calculated to any arbitrary degree of precision, at any point in space at any time– if one had knowledge of all geometry and electrical parameters of all objects in the environment, and if one could solve thefield theory equations (Maxwell’s equations) rapidly and accu-rately enough. In many settings though, particularly with mobility, the required knowledge translates to a very large amount of data, and hence renders this approach impractical. This motivates the use of statistical channel models. Interested readers are referred to available texts, for example, Ref. [16], for deterministic treatments of wireless channels.
There are also additional classifications of wireless channels, which include terrestrial versus aeronautical, maritime, or satellite, line of sight (LOS) versus non-LOS (NLOS), indoor versus outdoor, classifications by frequency band or primary propagation mechanism, and so on. Examples of useful texts either dedicated to wireless channel modeling or with
1 Guided wave channels can exhibit time variation when either anomalous events, such as accidental cutting of cables, occur or over the very long term, when cable materials degrade or their characteristics change with temperature, aging, and so on. Nonetheless, for modern communication systems that transfer messages over durations of seconds, minutes, or even hours, guided wave channels are well modeled as time invariant.
2 Note that strictly speaking, the term deterministic must be used with some caution, since in wireless settings, even the most careful design cannot account for all contingencies, atypical events may occur, and these can be treated as random. A famous example of this was when Penzias and Wilson of Bell Laboratories werefirst discovering the cosmic microwave background radiation [15], for which they eventually won the Nobel Prize. After carefully calibrating their system and finding themselves unable to explain results, a close inspection of their receive antenna revealed a nest of birds, whose presence altered the antenna characteristics.
multiple detailed chapters include Refs. [11] and [17–24]. Additional information, much standardized, is also available from the International Telecommunication Union (ITU) in its Recommendation series on propagation [25].
For essentially all cases, wireless channels are modeled as linearfilters, and hence are characterized completely by their channel impulse response (CIR), or equivalently, their channel transfer function (CTF), the Fourier transform of the CIR. The discussion here thus focuses upon this response and its characterization.
3.1.3 Airport Surface Area Channel
The airport surface area is defined here as all outdoor area on airport property. This includes runways, taxiways, areas near gates, maintenance areas, and all areas in between. As is well known, this area is a dynamic environment where airline activities such as baggage handling, fueling, and catering take place throughout the day and night, while aircraft are taking off and landing, taxiing, pushing into and pulling out of gates, while airport security vehicles and other ground vehicles are moving about.
Figure 3.2, from Ref. [2], shows a photograph taken from the air traffic control tower (ATCT) at JFK International Airport, illustrating features in the airport surface environment.
The airport surface area (ASA) channel is defined as the channel between the antenna at the ground site and the antenna on some mobile
Figure 3.2 View of some large airport features at John F. Kennedy International Airport, taken from air traffic control tower (ATCT) [2].
device located on the airport surface. The ground site antenna is often atop the ATCT, but may also be located on an airport building roof, or on a small tower on the ASA itself. The mobile devices on the airport surface may be aircraft, ground vehicles, or carried by persons. Most of our results pertain to the channel with the ground-site antenna at the ATCT, and the mobile device contained within a vehicle on the ASA; some results with the ground-site antenna located at an airportfield site on the ASA are also provided. The ASA channel is a terrestrial, point-to-multipoint channel with some features in common with other terrestrial mobile channels; the distinguishing features are those unique to the ASA, for example, large metallic aircraft and an open area often containing very large buildings on its perimeter.
Worth mentioning is that airports are of various sizes, and in Refs [2]
and [3], we created a three-level classification of airports as small, medium, and large. Large airports are busy, with many large jet airplanes (e.g., 747’s and 777’s), and at least several hundred aircraft arriving and departing per day, typically 80 or more during a busy hour [26]. The diameter of most large airports is typically no more than 5 km. Examples of large airports include JFK and Miami International Airport (MIA). The medium airport class has much in common with the large airports.
Medium-sized airports have buildings on the airport surface, but these are not as large or as numerous as in the large airport class. These airports also typically do serve the largest jets. An example of medium-sized airport is Cleveland Hopkins International Airport (CLE). The medium airports are still significantly bigger and busier than small, general aviation (GA) airports, which may have a single runway and only one building structure.
Several distinct propagation channel regions exist within most airports.
As with terrestrial channel models, this includes LOS and NLOS regions.
Many terrestrial channel models are also specific to an environment type [6], for example, urban, suburban, or rural. Defining such region types objectively can be difficult, and can often lead to further specifica-tion into subclasses [27].
In Refs [2] and [3], we classified ASA propagation regions into three types: LOS-Open (LOS-O), NLOS-Specular (NLOS-S), and NLOS. The LOS-O areas are those clearly visible from the ATCT (or ground-site antenna), with no significant scattering objects nearby, for example, runways and portions of taxiways. The NLOS-S regions are those in between the other two and exhibit mostly NLOS conditions, but have a distinct specular,first-arriving component in the CIR, in addition to lower energy multipath components (MPCs). An example of NLOS-S region would be ground vehicle lanes near terminal buildings, where a significant diffracted signal component is received. The NLOS regions are those that
have a completely obstructed LOS to the ATCT. These regions are near airport gates or behind large airport buildings.
Aircraft and ground vehicles may traverse all three types of regions as they move about the ASA. This has consequences for statistical channel models that will be addressed subsequently. Afinal comment on the ASA channel regards the spatial distribution of MPCs: scattering is almost never isotropic about the mobile terminal.