University at Buffalo Optical Wireless An Overview Chintan Shah December 9, 2004

University at Buffalo Outline Introduction What is Optical Wireless? Applications Transmitter and Receiver Topologies Challenges and Limitations Topology Control and Routing Conclusion

University at Buffalo What is Optical Wireless? Optical Wireless a.k.a. Free Space Optics (FSO) refers to the transmission of modulated light beams through the atmosphere to obtain broadband communication Line-of-sight technology Uses lasers/LEDs to generate coherent light beams

University at Buffalo What is Optical Wireless? Data rates of up to 2.5 Gbps at distances of up to 4km available in commercial products

University at Buffalo Last Mile problem Connecting the user directly to the backbone high speed fiber optic network is known as the Last Mile problem FSO as the low cost bridging technology

University at Buffalo More Applications Allows quick Metro network extensions Interconnecting local-area network segments spread across separate buildings (Enterprise connectivity) Fiber backup Interconnecting base stations in cellular systems

University at Buffalo Transmitter FSO uses the same transmitter technology as used by Fiber Optics Laser/LED as coherent light source Wavelengths centered around 850nm and 1550nm widely used Telescope and lens for aiming light beam to the receiver

University at Buffalo Safety while using Lasers

University at Buffalo Eye Safety 650 nm (visible) 880 nm (infrared) 1310 nm (infrared) 1550 nm (infrared) Class 1Up to 0.2 mWUp to 0.5 mWUp to 8.8 mWUp to 10 mW Class mWN/A Class 3A1-5 mW mW mW10-50 mW Class 3B5-500 mW mW mW mW Table1: Laser safety classification for point-source emitter Class 1 eye safety requirement for lasers used indoors Array of LEDs are used Class 3B eye safety requirement for laser used outdoors 1550 nm lasers are generally chosen for this purpose Classifies light sources depending on the amount of power they emit

University at Buffalo Receiver Photodiode with large active area Narrowband infrared filters to reduce noise due to ambient light Receivers with high gain Bootstrap receivers using PIN diode and avalanche photodiode (APD) used

University at Buffalo Simplified Transceiver Diagram

University at Buffalo Point-to-Multipoint Topology

University at Buffalo Point-to-Point Topology

University at Buffalo Ring with Spurs Topology

University at Buffalo Mesh Topology

University at Buffalo Typical Topology in a Metro

University at Buffalo Challenges Physical Obstruction Atmospheric Losses Free space loss Clear air absorption Weather conditions (Fog, rain, snow, etc.) Scattering Scintillation Building Sway and Seismic activity

University at Buffalo Physical Obstruction Construction crane or flying bird comes in path of light beam temporarily Solution: Receiver can recognize temporary loss of connection In packet-switched networks such short- duration interruptions can be handled by higher layers using packet retransmission

University at Buffalo Free space loss Proportion of transmitted power arriving at the receiver Occurs due to slightly diverging beam Solution: High receiver gain and large receiver aperture Accurate pointing

University at Buffalo Clear Air Absorption Equivalent to absorption loss in optical fibers Wavelength dependent Low-loss at wavelengths ~850nm, ~1300nm and ~1550nm Hence these wavelengths are used for transmission

University at Buffalo Weather Conditions Adverse atmospheric conditions increase Bit Error Rate (BER) of an FSO system Fog causes maximum attenuation Water droplets in fog modify light characteristics or completely hinder the passage of light Attenuation due to fog is known as Mie scattering Solution: Increasing transmitter power to maximum allowable Shorten link length to be between m

University at Buffalo Scattering Caused by collision of wavelength with particles in atmosphere Causes deviation of light beam Less power at receiver Significant for long range communication

University at Buffalo Scintillation Caused due to different refractive indices of small air pockets at different temperatures along beam path Air pockets act as prisms and lenses causing refraction of beam Optical signal scatters preferentially by small angles in the direction of propagation Distorts the wavefront of received optical signal causing ‘image dancing’ Best observed by the simmering of horizon on a hot day

University at Buffalo Scintillation (cont…) Solution: Large receiver diameter to cope with image dancing Spatial diversity: Sending same information from several laser transmitters mounted in same housing Not significant for links < 200m apart, so shorten link length

University at Buffalo Building Sway and Seismic activity Movements of buildings upsets transmitter-receiver alignment Solution: Use slightly divergent beam Divergence of 3-6 milliradians will have diameter of 3-6 m after traveling 1km Low cost Active tracking Feedback mechanism to continuously align transmitter- receiver lenses Facilitates accelerated installation, but expensive

University at Buffalo Empirical Design Principles Use lasers ~850 nm for short distances and ~1550 nm for long distance communication with maximum allowable power Slightly divergent beam Large receiver aperture Link length between m in case of adverse weather conditions Use multi-beam system

University at Buffalo Limitations of FSO Technology Requires line-of-sight Limited range (max ~8km) Unreliable bandwidth availability BER depends on weather conditions Accurate alignment of transmitter- receiver necessary

University at Buffalo Topology Control and Routing Given: Virtual topology: List of backbone nodes and potential links, Directed Graph G = (V, E) Number of interfaces a node can have Traffic profile of aggregate traffic demands between different source destination pairs Required: Optimal topology for maximizing the throughput from the traffic profile, i.e. subgraph G’ = (V, E’) so that interface and capacity constraints are met and network has maximum throughput

University at Buffalo Solution Strategy The algorithm consists of two parts: Offline phase It computes the sub-graph Gives the routes and bandwidth reservation for every ingress-egress pair in the traffic profile Online phase Uses the topology computed in offline phase to exercise admission control Routes individual flows

University at Buffalo Solution Strategy (cont) The order in which the traffic demands are considered for link formation decides the throughput of the system Task of finding sub-graph that will maximize throughput while restricting degree of each vertex is computationally prohibitive Hence, Rollout algorithm is used to obtain near optimal solution

University at Buffalo Basic Rollout Algorithm General method for obtaining an improved policy for a Markov decision process starting with a base heuristic policy One step look ahead policy, with the optimal cost-to-go approximated by the cost-to-go of the base policy

University at Buffalo Basic Rollout Algorithm (Math) Consider problem: Maximize G(u) over set of feasible solutions U and each solution consist of N components u = (u 1, u 2, …, u N ) The base-heuristic algorithm (H) extends a partial solution (u 1, u 2, …, u k ), (k < N) to a complete solution (u 1, u 2, …, u N )

University at Buffalo Thus, H(u 1, u 2, …, u k ) = G (u 1, u 2, …, u N ) The rollout algorithm (R) takes a partial solution (u 1, u 2, …, u n-1 ) and extends it by one component. Thus, R(u 1, u 2, …, u n-1 ) = (u 1, u 2, …, u n ) where u n is chosen so as to maximize H(u 1, u 2, …, u n ) Basic Rollout Algorithm (Math)

University at Buffalo Path Computation Find k paths for each entry in traffic profile i = 0, d0 = 0, d = aggregate demand for this ingress-egress pair Repeat following until we cannot find a path or whole demand is routed or i = k Find a path using constrained shortest path first (CSPF) that accommodates (d-d i )/(k-i), bandwidth and finalize links temporarily Constraints are limited transmitter-receiver interfaces and limited link capacity Route as much bandwidth of this demand on this route, call it d i+1, Decrement link capacity by d i+1, and i = i + 1 This algorithm routes whatever we can on these paths

University at Buffalo Base Heuristic Partial topology by routing demands (t 1,…,t n ) is formed The base heuristic routes the remaining demands in decreasing order of magnitude

University at Buffalo Index Rollout Algorithm Suppose demands (t 1,…,t n ) have been routed For all possible next candidate demands, throughput is calculated using base heuristic t n+1 is chosen as the one that produces maximum throughput when base heuristic is used to route remaining demands

University at Buffalo Comments Let: N = # of nodes M = # of communicating ingress-egress pairs k = # of paths calculated for each communicating pair Computational Complexity: Offline phase: O(kM 3 N 2 ), for constant number of communicating ingress-egress nodes Online phase: O(k) The base heuristic is such that the rollout works at least as good as the heuristic

University at Buffalo Conclusion This presentation gave an overview of Optical Wireless technology We started with applications of FSO to provide motivation for its study Transmitter and receiver designs were discussed We looked at the challenges faced by this technology and techniques to deal with them Finally had a brief look at the problem of Topology Control and routing of Bandwidth Guaranteed flows

University at Buffalo References D.J.T.Heatley, D.R.Wisely, I.Neild and P.Cochrane, “Optical wireless: The story so far”, IEEE Communications Magazine 36(12) (1998) H.A.Willebrand and B.S.Ghuman, “Fiber Optics Without Fiber”, IEEE Spectrum Magazine, August 2001, pp A.Kashyap, M.K.Khandani, K.Lee, M.Shayman, “Profile-Based Topology Control and Routing of Bandwidth-Guaranteed Flows in Wireless Optical Backbone Networks”, University of Maryland