Tight profit margins and increasing global competition are driving industrial operations to achieve maximum efficiencies. This level of performance requires optimal orchestration of human and material resources, ensuring that the right personnel, equipment, and raw materials are in the right place at the right time.
Originally, management systems dedicated to this task were grounded in the RFID world, and the technology acted as a database management system with readers that informed the database as to where a tag was last observed. Today the systems have evolved into real-time location systems (RTLS) that bring the function of resource tracking to the forefront. These systems can use a range of wireless technologies to deliver industrial RTLS functionality. In the wireless world certain technologies and techniques are more developmental than others, with new advances appearing on a monthly basis.
This article is the first of a three-part series that looks at wireless technologies used in RTLS. Part 1 lays the foundation for the discussion by examining the challenges posed by industrial wireless environments and by providing the tools and techniques used to grapple with the mechanics of communications within this context.
Challenges of Industrial Environments
An industrial setting presents RF and environmental conditions that may be more taxing on a wireless system than almost any other site. The quantity of reflective and absorptive surfaces associated with these "canyons of metal" lead to variable attenuation and multipath conditions frequently dovetailed into requirements for the wireless systems that have to operate in non-line-of-sight (LOS), explosive environments (see "The Realities of Dealing with Wireless Mesh Networks"). This combination places considerable strain on the performance, reliability, and maintenance of the components that make up RTLS.
For example, similar to the free-space propagation loss, higher frequencies attenuate faster than lower frequencies. Therefore, 5 GHz RF signals typically have higher attenuation than 2.4 GHz transmissions, although there are a few exceptions. Figure 1 shows the attenuation (dB) introduced by various objects to RF signals at the 2.4 and 5 GHz bands. Of particular note are the attenuation values for concrete, a material used widely in industrial facilities. The disparity in the values shown arises from various types of concrete materials used in different parts of the world. In addition, the thickness and coating differ, depending on whether it's used in floors or interior or exterior walls. Brick walls usually have attenuation at the lower end of the range.
|2.4 GHz||5 GHz|
|Wood door (hollow-solid)||3-4||6-7|
|Glass/Window (not tinted)||2-3||6-8|
|Double-pane coated glass||13||20|
|Steel/fire exit door||13-19||25-32|
Not included in Figure 1 are attenuation values for other materials commonly found in these environments. Measurements of signal attenuation caused by water reveal higher relative attenuation in the 5 GHz ISM bands than in the 2.4 GHz segment, as shown in Figure 2. Also, consider the effects that rain and fog have on performance. Signals in the 2.4 GHz band can be attenuated by as much as 0.08 dB/mile by torrential rain (4 in./hr). Thick fog produces attenuation up to 0.03 dB/mile. At 5.8 GHz, torrential rain can produce attenuation up to 0.8 dB/mile, and thick fog up to 0.11 dB/mile. Even though rain itself does not cause major propagation problems, it will collect on the leaves of trees and produce attenuation until it evaporates. In addition, human bodies, which are composed predominantly of water, attenuate RF signals approximately 3 dB in the 2.4 GHz range and 5 dB in the 5 GHz range.
Figure 2. Attenuation values of oxygen and water
Numerous industry groups have arisen to claim their share of the potential market for industrial asset tracking. In most cases, an organization aligns itself with a wireless technology that has been adapted for this application. A sampling of such technologies is provided in Figure 3. The comparison is relatively subjective, with ample room in each category to discuss the noted value (e.g., battery lifetime). The information is based on public forum presentations.
Figure 3. A comparison of candidate technologies applicable for industrial asset tracking
Six technologies that play significant roles in industrial RTLS include RFID, GPS-based, chirped frequency-based, received signal strength indicator (RSSI)-based, RuBee (IEEE P1902), and ultra-wideband (UWB)-based systems. Each has its own unique infrastructure requirements to provide comparable location resolution.
Classic Communications—Equations, Definitions, and Methods
The performance of point-to-point communications systems used to be dictated almost universally by a calculation of the received signal level. The classic method of determining the probable system performance begins with a path analysis or link power budget. This step provides the designer with the necessary equipment parameters to prepare a block diagram of the terminal or repeater configuration, making it possible to go on to specify equipment requirements both quantitatively and qualitatively. Next, frequency assignments are made, and the signal-to-noise ratio (SNR), signal energy per bit to noise spectral density ratio (Eb/N0), and the bit-error rate (BER) of the link are computed. The received signal strength is calculated following Equation 1's radar range (or some variant):
|λ||=||wavelength of the signal|
|Gt, Gr||=||respective gains of the transmit and receive antennas|
|R||=||receiver-transmitter separation distance|
This form of LOS path analysis is good for radio links in the sub-10 GHz band. The performance of radio links operating at frequencies higher than 10 GHz are affected by excess attenuation due to additional factors, such as rainfall and gaseous absorption.
Calculations continue following the standard form of determining core values, such as the free space loss that the signal encounters as it goes from the transmitter to the receiver, separated by a distance of R, and then computing the effective isotropic radiated power from the transceiver pair (see Telecommunications Primer: Data, Voice and Video Communications by E.B. Carne). Additional factors, such as the Fresnel zone clearance (the height required for the signal to clear any envisioned obstacle) would also be calculated and accounted for.
Many of these somewhat cumbersome methods have been implemented as Web-based tools, available at various Web sites, obviating the task of doing it by hand. A representative, or typical, path analysis scheme can be obtained from the Open Domain Association.
The result is a starting point for the system's SNR, the implications of which are immediate in terms of the BER for a given data rate. Engineering aside, the definition of performance of a communications channel frequently gets entangled in a debate in which some proponents champion BER while others favor packet-error rates. For this review, understanding that it is digital data being transmitted across the wireless channels, we'll define performance as the BER (the number of errors encountered during the transmission of a certain amount of data).
The coupling between BER and SNR is a logical one. In general, the higher the SNR, the fewer the errors in the channel transmission; or simply stated, as the SNR increases, the BER decreases. Conversely, as the SNR decreases, the BER will increase, at which point the communications channel typically reduces the data rate (making each bit a little longer) in an attempt to reduce the number of errors in the transmission. A representative graph of SNR vs. BER for a standard digital communications transmission is shown as Figure 4. Notice that as the SNR decreases, there is a graceful degradation, or roll-off, in channel performance. For example, as a 5.8 GHz signal's SNR is degraded, the channel will tend to remain operational, albeit at a reduced data rate. The figure also shows a quadrature amplitude modulation (QAM) digital communications channel's performance. Note the roll-off in performance for each type of QAM.
Figure 4. SNR vs. BER for a standard wireless channel
The system designer has a range of choices with which to optimize the communications channel performance, such as the signaling method (e.g., amplitude, frequency, phase, and hybrid) and modulation format to use. Each combination has its own particular attributes, which result in a performance characterization similar to that shown in Figure 3. The use of error-correction codes, acknowledgement-based protocols, and similar techniques to verify that the information transmitted was correctly received/deciphered serves to modify the classic BER performance graph of Figure 3.
Coming Up Next
Part 2 of this series, which will appear next month, provides a technological overview of RFID-, GPS-, and chirped frequency-based asset tracking systems.
FOR FURTHER READING
1. Carne, E.B. 1999. Telecommunications Primer: Data, Voice and Video Communications, Prentice Hall, Upper Saddle River, NJ
2. CCITT Rec. G.821, Fascicle III.5, IXth Plenary Assembly. 1988. Error Performance of an International Digital Connection Forming Part of an Integrated Services Digital Network, Melbourne, Australia
3. Freeman, R. 1997. Radio Systems Design for Telecommunications, John Wiley & Sons, Hoboken, NJ
4. Linkabit Corp. July 1976. Error Control Handbook, San Diego, CA, under USAF Contract F44620-76-C-0056
5. Rappaport, T.S. 1996. Wireless Communications Principles and Practice, Prentice Hall, Upper Saddle River, NJ
6. Viterbi, A.J. Oct 1971. Convolutional Codes and Their Performance in Communications Systems, IEEE Trans. on Comm. Tech., Vol. Com-19
The figures in Parts 1–3 of this series are numbered consecutively.