- Research Article
- Open Access
A Path Loss Model for Non-Line-of-Sight Ultraviolet Multiple Scattering Channels
© Haipeng Ding et al. 2010
- Received: 1 December 2009
- Accepted: 30 March 2010
- Published: 10 May 2010
An ultraviolet (UV) signal transmission undergoes rich scattering and strong absorption by atmospheric particulates. We develop a path loss model for a Non-Line-of-Sight (NLOS) link. The model is built upon probability theory governing random migration of photons in free space, undergoing scattering, in terms of angular direction and distance. The model analytically captures the contributions of different scattering orders. Thus it relaxes the assumptions of single scattering theory and provides more realistic results. This allows us to assess the importance of high-order scattering, such as in a thick atmosphere environment, where short range NLOS UV communication is enhanced by hazy or foggy weather. By simulation, it is shown that the model coincides with a previously developed Monte Carlo model. Additional numerical examples are presented to demonstrate the effects of link geometry and atmospheric conditions. The results indicate the inherent tradeoffs in beamwidth, pointing angles, range, absorption, and scattering and so are valuable for NLOS communication system design.
- Path Loss
- Elevation Angle
- Path Loss Model
- Scatter Phase Function
- Arrival Probability
In free space optical communication, the deep ultraviolet (UV) spectrum with wavelength 200 280 nm is regarded as an appealing choice to overcome solar background radiation and relax pointing and tracking . High altitude ozone absorbs most solar radiation in this band, yielding negligible background noise at sea level . And, atmospheric scattering is very strong, enabling non-line-of-sight (NLOS) communications where the transmitter is not necessarily within the receiver field of view (FOV). However, in addition to scattering, strong atmospheric absorption leads to significant signal attenuation and so limits achievable rates.
These properties have motivated development of UV signal propagation models and communication systems for military and civilian applications, for example, long-range communication based on high-power UV lasers since the 1960s [5–8]. Recent progress in deep UV light emitting diodes (LEDs)  and avalanche photodiodes (APDs) [10, 11] offers promise for deployment of low-cost/power and moderate bandwidth short-range UV communication systems [12, 13], including underwater communications [14, 15] and sensor networks [16, 17].
NLOS channel modeling is more complex than traditional LOS links. In addition to wavelength and device characteristics, NLOS path loss is a function of system geometry, including transmitter (Tx) beamwidth, communication range, receiver (Rx) FOV, the pointing elevation angles, as well as the optical properties of the atmosphere.
For simplicity and tractable analysis, single scattering models for NLOS communication links were developed [1, 18], with a corresponding single scattering assumption imposed; that is, each photon undergoes only a single interaction with the atmosphere before it reaches the detector. Recently the model has been further simplified for improved analytical tractability . However, the single scattering assumption does not always lead to accurate link performance prediction, especially as the range increases, and with beam pointing at low elevation angles. Multiple scattering may occur when the particle density is large and/or the propagation distance is long. Alternatives to the single scattering model include an empirical path loss model  and a Monte Carlo statistical path loss model . Those models are applicable for predicting path loss in a variety of scenarios and are generally more accurate than the single scattering model.
In this paper, following the same physical scattering law as the Monte Carlo statistical method [2, 21], we develop a stochastic analytical NLOS UV channel path loss model. We apply a stochastic analytical technique [22, 23] to theoretically derive the th scattered signal energy collected by the detector. The model assumes that the photons are stochastically scattered and/or absorbed by the atmospheric particles and involves probabilistic modeling of photon random moving direction, distance, energy loss, and receiver capture after a specified number of scatterings. In order to obtain the th-order scattered signal at the receiver, we trace the migration routes of a single photon through the medium. Its scattering distance and scattering angles follow certain probability distribution functions (PDFs) . The propagation of a photon between two consecutive scatterers is modeled as a single scattering event. The probability of the photon arriving at the receiver is a function of the scattering events encountered. A similar technique has been applied to model multiply scattered lidar returns in cloudy media where significant scattering occurs . To account for a divergent UV beam profile, the contributions of photons at all possible directions within the beam are integrated .
We assume a homogeneous atmosphere with constant scattering and absorption coefficients and ignore atmospheric turbulence. This assumes that different types of particles are well mixed and the environment is stationary. Photons are scattered elastically which conserves energy but incurs energy loss during propagation. The detector is assumed small in size compared with the propagation space and is regarded as a point detector with finite FOV.
Our model offers an analytical formulation for NLOS scattering channel path loss and provides a reference to easily check other models in a variety of system parameter settings. We consider the effects of different optical pointing geometries and find that path loss is relatively insensitive to the Tx beam angle but increases considerably with increased Tx/Rx elevation angles and decreased Rx FOV for medium communication range. Not surprisingly, numerical tests demonstrate good agreement with Monte Carlo simulation . However, the current analytical approach can distinguish the contributions of different orders of multiple scattering, whereas Monte Carlo modeling can only capture the total scattering effect. A similar comparison of Monte Carlo simulation and analytical methods has also been described by Lavigne et al. .
The model reveals when high-order scattering plays a role, and thus offers more insight into the channel behavior. Extensive numerical tests show that high-order scattering may play a significant role for scenarios with large baseline ranges and elevation angles. Atmospheric conditions also affect the multiple scattering contributions. A tenuous atmosphere generally leads to higher path loss at a small range than a thick or extra thick atmosphere where rich multiple scattering enhances received signal strength. As a by-product, when contributions from only single scattering are retained, the corresponding single scattering path loss shows a good match with that predicted by Reilly's analytical single scattering model . A disadvantage of the proposed model is that it cannot provide pulse spreading information, while the Monte Carlo model can .
The organization of this paper is as follows. The stochastic path loss model based on a general NLOS UV channel configuration is developed in Section 2. It consists of modeling photon direction, distance traveled, probability of arrival at the receiver after scattering times, and total path loss. Numerical analysis for the multiple scattering NLOS channel is carried out and path loss performance is compared with both the single scattering model and Monte Carlo simulation in Section 3. Channel characteristics under different geometric parameters are analyzed in Section 4. Finally some conclusions are drawn.
A NLOS UV channel involves rich scattering and absorption because of abundant suspended particulates in the atmosphere. For NLOS UV communication, scattering serves as the vehicle for information exchange between the Tx and Rx. The scattered photons that reach the receiver depend on the link geometry, the atmospheric optical properties, and their random migration, as described next.
2.1. Link Geometry
2.2. Atmospheric Optical Properties
From the communications viewpoint, scattering and absorption are two dominant types of photon interactions with the atmosphere. To describe a homogeneous atmospheric medium related to UV communication, we adopt the following coefficients [1, 26]: the Rayleigh (molecular) scattering coefficient , Mie (aerosol) scattering coefficient , absorption coefficient , and extinction coefficient . The total scattering coefficient is defined as the sum of the two scattering coefficients , and the extinction coefficient is given by the sum of the scattering and absorption coefficients as .
2.3. Elementary Events for Photon Random Migration
where is given by (9), by (10), and by (11). The integration limits for all variables cover their full ranges except the following: from to to ensure integration inside the source beam, and and within the solid angle of the receiver determined by the receiver area and distance . Note that no integration over is needed because it is a function of the other variables. Thus, there are a total of integration variables.
where for notational convenience represents the integrand product of functions over all , and for all differentials . During the process, we truncate the infinite integration limit for all (up to ) at a sufficiently large number to ensure that the integrand has decayed sufficiently close to zero. We have found generally that using a limit of several times works well.
It is important to clarify the difference between the Monte Carlo integration of a definite integral as used here and the Monte Carlo simulation of a stochastic process . Even though both belong to the Monte Carlo family and involve random realizations, Monte Carlo integration is a numerical method based on the approximation of the averaged deterministic integrand function, whereas Monte Carlo simulation is a technique that relies on repeated samplings (numerous realizations) of a random process to compute a statistical expectation.
2.5. Energy Loss Model
Note that when , the energy represents the total received energy contributed by all scatterings and path loss represents the actual link performance. If we adopt decibels for path loss, then it becomes .
In this section we study modeling performance in terms of the received energy ratio and path loss results for different geometry scenarios. Through numerical simulation, multiple scattering effects are observed and analyzed. These results are also compared with Reilly's analytical single scattering model  as well as the Monte Carlo simulated multiple scattering model , respectively, under the same geometries and atmosphere parameters. We demonstrate good agreement with  when single scattering is of concern, and with  when multiple scatterings are considered.
Since NLOS UV channel characteristics are crucial to communication system design, in this section, we apply the proposed multiple scattering model to further study the effects of different system parameters on the channel path loss, including link geometries and two typical atmosphere conditions. Referring to Figure 1, we study angle sensitivity by varying one angle and keeping the others fixed.
This paper proposed an analytical energy loss model for NLOS UV communication channels based on the probability theory of scattering and absorption. The model was developed by employing the PDFs of scattering distance and scattering angles. Multiple scattering was incorporated and contributions of different scattering orders were identified. The total energy loss was modeled by summing over the scattering order. The path loss predicted using only the contribution from the first-order agreed with Reilly's analytical single scattering model, as illustrated with different optical geometries. Multiple scattering becomes more dominant for some cases, especially longer propagation distance and larger elevation angles. Our model also provided results that are consistent with the Monte Carlo simulation model. Channel characteristics were investigated in detail, including the effects of varying system geometry and the effects of different atmosphere conditions.
Further study will be conducted to develop an analytical NLOS UV channel impulse response model from which our path loss model can be further validated and channel bandwidth can be predicted. An analytically more tractable path loss model is also a future topic of interest, which can enable more intuitive analysis for the effects of system geometry and parameters.
The authors gratefully acknowledge R. Drost for his help with the coding examples. This work was supported in part by the U.S. Army Research Office under Grant W911NF-09-1-0293 and the Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011.
- Reilly DM, Warde C: Temporal characteristics of single-scatter radiation. Journal of the Optical Society of America A 1979, 69(3):464-470. 10.1364/JOSA.69.000464View ArticleGoogle Scholar
- Ding H, Chen G, Majumdar AK, Sadler BM, Xu Z: Modeling of non-line-of-sight ultraviolet scattering channels for communication. IEEE Journal on Selected Areas in Communications 2009, 27(9):1535-1544.View ArticleGoogle Scholar
- Xu Z, Sadler BM: Ultraviolet communications: potential and state-of-the-art. IEEE Communications Magazine 2008, 46(5):67-73.View ArticleGoogle Scholar
- Koller LR: Ultraviolet Radiation. 2nd edition. John Wiley & Sons, New York, NY, USA; 1965.Google Scholar
- Harvey GL: A survey of ultraviolet communication systems. Naval Research Laboratory, Washington, DC, USA; March 1964.Google Scholar
- Sunstein DE: A scatter communication link at ultraviolet frequencies, B.S. thesis. MIT, Cambridge, Mass, USA; 1968.Google Scholar
- Junge DM: Non-line-of-sight electro-optic laser communications in the middle ultraviolet, M.S. thesis. Naval Postgraduate School, Monterey, Calif, USA; December 1977.Google Scholar
- Ross WS, Kennedy RS: An investigation of atmospheric optically scattered non-line-of-sight communication link. In type. Army Research Office Project Report, Research Triangle Park, NC, USA; January 1980.Google Scholar
- Shatalov M, Zhang J, Chitnis AS, et al.: Deep ultraviolet light-emitting diodes using quaternary AlInGaN multiple quantum wells. IEEE Journal on Selected Topics in Quantum Electronics 2002, 8(2):302-309. 10.1109/2944.999185View ArticleGoogle Scholar
- Bai X, Mcintosh D, Liu H, Campbell JC: Ultraviolet single photon detection with Geiger-mode 4H-SiC avalanche photodiodes. IEEE Photonics Technology Letters 2007, 19(22):1822-1824.View ArticleGoogle Scholar
- Shen SC, Zhang Y, Yoo D, et al.: Performance of deep ultraviolet GaN avalanche photodiodes grown by MOCVD. IEEE Photonics Technology Letters 2007, 19(21):1744-1746.View ArticleGoogle Scholar
- Shaw GA, Siegel AM, Model J, Greisokh D: Recent progress in short-range ultraviolet communication. Unattended Ground Sensor Technologies and Applications VII, March 2005, Orlando, Fla, USA, Proceedings of SPIE 214-225.View ArticleGoogle Scholar
- Chen G, Abou-Galala F, Xu Z, Sadler BM: Experimental evaluation of LED-based solar blind NLOS communication links. Optics Express 2008, 16(19):15059-15068. 10.1364/OE.16.015059View ArticleGoogle Scholar
- Arnon S, Kedar D: Non-line-of-sight underwater optical wireless communication network. Journal of the Optical Society of America A 2009, 26(3):530-539. 10.1364/JOSAA.26.000530View ArticleGoogle Scholar
- Kedard D, Arnon S: Subsea ultraviolet solar-blind broadband free-space optics communication. Optical Engineering 2009, 48(4):-7.Google Scholar
- Shaw GA, Siegel AM, Model J, Nischan M: Field testing and evaluation of a solar-blind UV communication link for unattended ground sensors. Unattended/Unmanned Ground, Ocean, and Air Sensor Technologies and Applications VI, April 2004, Orlando, Fla, USA, Proceedings of SPIE 5417: 250-261.View ArticleGoogle Scholar
- Kedar D, Arnon S: Non-line-of-sight optical wireless sensor network operating in multiscattering channel. Applied Optics 2006, 45(33):8454-8461. 10.1364/AO.45.008454View ArticleGoogle Scholar
- Luettgen MR, Shapiro JH, Reilly DM: Non-line-of-sight single-scatter propagation model. Journal of the Optical Society of America A 1991, 8(12):1964-1972. 10.1364/JOSAA.8.001964View ArticleGoogle Scholar
- Xu Z, Ding H, Sadler BM, Chen G: Analytical performance study of solar blind non-line-of-sight ultraviolet short-range communication links. Optics Letters 2008, 33(16):1860-1862. 10.1364/OL.33.001860View ArticleGoogle Scholar
- Chen G, Xu Z, Ding H, Sadler BM: Path loss modeling and performance trade-off study for short-range non-line-of-sight ultraviolet communications. Optics Express 2009, 17(5):3929-3940. 10.1364/OE.17.003929View ArticleGoogle Scholar
- Witt AN: Multiple scattering in reflection nebulae—I: a Monte Carlo approach. The Astrophysical Journal Supplement Series 1977, 35: 1-6.View ArticleGoogle Scholar
- Gillespie DT: Stochastic-analytic approach to the calculation of multiply scattered lidar returns. Journal of the Optical Society of America A 1985, 2(8):1307-1324.View ArticleGoogle Scholar
- Gillespie DT:Calculation of -scattered lidar retrens for large n in an idealized cloud. Journal of the Optical Society of America A 1987, 4(3):455-464. 10.1364/JOSAA.4.000455MathSciNetView ArticleGoogle Scholar
- Gandjbakhche AH, Nossal R, Bonner RF: Scaling relationships for theories of anisotropic random walks applied to tissue optics. Applied Optics 1993, 32(4):504-516. 10.1364/AO.32.000504View ArticleGoogle Scholar
- Bissonnette LR: Multiple-scattering lidar equation. Applied Optics 1996, 35(33):6449-6465. 10.1364/AO.35.006449View ArticleGoogle Scholar
- Lavigne C, Roblin A, Outters V, Langlois S, Girasole T, Rozé C: Comparison of iterative and Monte Carlo methods for calculation of the aureole about a point source in the Earth's atmosphere. Applied Optics 1999, 38(30):6237-6246. 10.1364/AO.38.006237View ArticleGoogle Scholar
- Zachor AS: Aureole radiance field about a source in a scattering-absorbing medium. Applied Optics 1978, 17(12):1911-1922. 10.1364/AO.17.001911View ArticleGoogle Scholar
- Prahl SA, Keijzer M, Jacques SL, Welch AJ: A Monte Carlo model of light propagation in tissue. Dosimetry of Laser Radiation in Medicine and Biology, 1989, Proceedings of SPIE IS 5: 102-111.Google Scholar
- Leon-Garcia A: Probability and Random Processes for Electrical Engineering. Addison-Wesley, Reading, Mass, USA; 1994.Google Scholar
- Wikipedia : Monte Carlo integration. http://en.wikipedia.org/wiki/Monte_Carlo_integration
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.