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Networking Cognitive Radios • Interaction Problem • Role of Policy • Techniques for designing network • Commercial standards 1 The Interaction Problem Outside World • Outside world is determined by the interaction of numerous cognitive radios 2/67 • Adaptations spawn adaptations Cognitive Radio Technologies, 2007 Dynamic Spectrum Access Pitfall • Suppose – g31>g21; g12>g32 ; g23>g13 2 • Without loss of generality – g31, g12, g23 = 1 – g21, g32, g13 = 0.5 • Infinite Loop! 3 1 – 4,5,1,3,2,6,4,… Interference Characterization Chan. Interf. (0,0,0) (0,0,1) (0,1,0) (0,1,1) (1,0,0) (1,0,1) (1,1,0) (1,1,1) (1.5,1.5,1.5) (0.5,1,0) (1,0,0.5) (0,0.5,1) (0,0.5,1) (1,0,0.5) (0.5,1,0) (1.5,1.5,1.5) 3/67 0 1 2 Cognitive Radio Technologies, 2007 3 4 5 6 7 Implications • In one out every four deployments, the example system will enter into an infinite loop • As network scales, probability of entering an infinite loop goes to 1: – 2 channels – k channels p loop 1 3 / 4 n p loop 1 1 2 C3 k 1 n Ck 1 • Even for apparently simple algorithms, ensuring convergence and stability will be nontrivial 4/67 Cognitive Radio Technologies, 2007 Locally optimal decisions that lead to globally undesirable networks • Scenario: Distributed SINR maximizing power control in a single cluster • For each link, it is desirable to increase transmit power in response to increased interference • Steady state of network is all nodes transmitting at maximum power Power SINR Insufficient to consider only a single link, must consider 5/67 interaction Cognitive Radio Technologies, 2007 (Radio 2’s available actions) Network Analysis Objectives 1. Steady state characterization 2. Steady state performance 3. Convergence 4. Stability/Noise 5. Scalability NE3 NE3 a2 NE2 NE1 NE1 a1 a1 (Radio 1’s available actions) a3 Scalability Convergence Stability/Noise Performance Steady State Characterization As Are How these donumber initial system outcomes of variations/noise devices desirable? impact increases, the impact system the system? steady state? Is itthe possible toconditions predict behavior in the system? What Do these How processes steady is outcomes thestates system will outcomes maximize lead change impacted? to steady with the system statevariations/noise? conditions? target parameters? Howthe many different are small possible? How Is convergence Do long previously does itaffected take optimal to by reach steady system thestates steady variations/noise? remain state?optimal?6/67 Cognitive Radio Technologies, 2007 Cognitive Radio Network Modeling Summary • Radios • Actions for each radio • Observed Outcome Space • Goals • Decision Rules • Timing • i,j N, |N| = n • A=A1A2An • O • uj:O (uj:A) • dj:OAi (dj:A Ai) • T=T1T2Tn 7/67 Cognitive Radio Technologies, 2007 Comments on Timing • When decisions are made also matters and different radios will likely make decisions at different time • Tj – when radio j makes its adaptations – Generally assumed to be an infinite set – Assumed to occur at discrete time • Consistent with DSP implementation • T=T1T2Tn • tT Decision timing classes • Synchronous – All at once • Round-robin – One at a time in order – Used in a lot of analysis • Random – One at a time in no order • Asynchronous – Random subset at a time – Least overhead for a network 8/67 Cognitive Radio Technologies, 2007 Variety of game models • Normal Form Game <N,A,{ui}> – Synchronous play – T is a singleton – Perfect knowledge of action space, other players’ goals (called utility functions) • Repeated Game <N,A,{ui},{di}> – Repeated synchronous play of a normal form game – T may be finite or infinite – Perfect knowledge of action space, other players’ goals (called utility functions) – Players may consider actions in future stages and current stages • Strategies (modified di) • Asynchronous myopic repeated game <N,A,{ui},{di},T> – Repeated play of a normal form game under various timings – Radios react to most recent stage, decision rule is “intelligent” • Many others in the literature and in the dissertation 9/67 Cognitive Radio Technologies, 2007 Cognitive radios are naturally modeled as players in a game Infer from Context Utility function Arguments Infer from Radio Model Establish Priority Normal Immediate Observe Outcome Space Outside World Utility Function Orient Autonomous Goal Plan Normal Urgent Learn New States Decide States Act \ Decision Rules Allocate Resources Initiate Processes Action Negotiate Cognitive Radio Technologies, 2007 Sets 10/67 Adapted From Mitola, “Cognitive Radio for Flexible Mobile Multimedia Communications ”, IEEE Mobile Multimedia Conference, 1999, pp 3-10. Interaction is naturally modeled as a game Radio 1 Radio 2 Actions Decision Rules u1 Actions Decision Rules Action Space Informed by Communications Theory u1 ˆ1 f :AO Outcome Space ˆ1, ˆ2 u2 ˆ2 u2 11/67 Cognitive Radio Technologies, 2007 Some differences between game models and cognitive radio network model • Assuming numerous iterations, normal form game only has a single stage. – Useful for compactly capturing modeling components at a single stage – Normal form game properties will be exploited in the analysis of other games • Repeated games are explicitly used as the basis for cognitive radio algorithm design (e.g., Srivastava, MacKenzie) – Not however, focus of work – Not the most commonly encountered implementation Player Cognitive Radio Knowledge Knows A Can learn O (may know or learn A) f : A O Invertible Constant Known Not invertible (noise) May change over time (though relatively fixed for short periods) Has to learn Preferences Ordinal Cardinal (goals) Cognitive Radio Technologies, 2007 12/67 Cognitive Radios’ Dilemma • Two radios have two signals to choose between {n,w} and {N,W} • n and N do not overlap • Higher throughput from operating as a high power wideband signal when other is narrowband 13/67 Cognitive Radio Technologies, 2007 Potential Problems with Networked Cognitive Radios Distributed • • • • • Centralized Infinite recursions Instability (chaos) Vicious cycles Adaptation collisions Equitable distribution of resources • Byzantine failure • Information distribution • • • • Signaling Overhead Complexity Responsiveness Single point of failure 14/67 Cognitive Radio Technologies, 2007 Price of Anarchy (Factor) Performance of Centralized Algorithm Solution Performance of Distributed Algorithm Solution 1 • Centralized solution always at least as good as distributed solution – Like ASIC is always at least as good as DSP • Ignores costs of implementing algorithms – Sometimes centralized is infeasible (e.g., routing the Internet) – Distributed can sometimes (but not generally) be more costly than centralized Cognitive Radio Technologies, 2007 9.6 7 15/67 Implications • Best of All Possible Worlds – Low complexity distributed algorithms with low anarchy factors • Reality implies mix of methods – Hodgepodge of mixed solutions • Policy – bounds the price of anarchy • Utility adjustments – align distributed solution with centralized solution • Market methods – sometimes distributed, sometimes centralized • Punishment – sometimes centralized, sometimes distributed, sometimes both • Radio environment maps –”centralized” information for distributed decision processes – Fully distributed • Potential game design – really, the panglossian solution, but only applies to particular problems 16/67 Cognitive Radio Technologies, 2007 The Role of Policy How does policy impact network performance? 17 Policy • Concept: Constrain the available actions so the worst cases of distributed decision making can be avoided • Not a new concept – – Policy has been used since there’s been an FCC • What’s new is assuming decision makers are the radios instead of the people controlling the radios 18/67 Cognitive Radio Technologies, 2007 Policy applied to radios instead of humans mask • Need a language to convey policy – Learn what it is – Expand upon policy later frequency Policies • How do radios interpret policy – Policy engine? • Need an enforcement mechanism – Might need to tie in to humans • Need a source for policy – Who sets it? – Who resolves disputes? • Logical extreme can be quite complex, but logical extreme may not be necessary. Cognitive Radio Technologies, 2007 19/67 Example Policies from WNAN • No harmful interference to non-WNaN systems – • Interference Limitation: Maintain ≤ 3dB of SNR at a Protected Receiver. – – • Perhaps not practical (then again, only a “principle”) More practical, though perhaps not measurable Possible to estimate with built in environment models Abandon Time: Abandon a Frequency ≤ 500 ms – – – Easily measured Depending on precise policy, easily implemented too Probably should be augmented with detection 20/67 Cognitive Radio Technologies, 2007 802.22 Example Policies • Detection – Digital TV: -116 dBm over a 6 MHz channel – Analog TV: -94 dBm at the peak of the NTSC (National Television System Committee) picture carrier – Wireless microphone: -107 dBm in a 200 kHz bandwidth. • Transmitted Signal – 4 W Effective Isotropic Radiated Power (EIRP) – Specific spectral masks – Channel vacation times 21/67 C. Cordeiro, L. Challapali, D. Birru, S. Shankar, “IEEE 802.22: The First Worldwide Wireless Standard based on Cognitive Radios,” Cognitive Radio Technologies, 2007 IEEE DySPAN2005, Nov 8-11, 2005 Baltimore, MD. Designing Well-Behaved Cognitive Radio Networks Repeated Games, Potential Games, Markets 22 Repeated Games • Same game is repeated Stage 1 – Indefinitely – Finitely • Players consider discounted payoffs across multiple stages Stage 2 – Stage k ui a k k ui a k – Expected value over all future stages Stage k ui a u a k k k 0 k i Cognitive Radio Technologies, 2007 23/67 Impact of Strategies • Rather than merely reacting to the state of the network, radios can choose their actions to influence the actions of other radios • Threaten to act in a way that minimizes another radio’s performance unless it implements the desired actions • Common strategies – Tit-for-tat – Grim trigger – Generous tit-for-tat • Play can be forced to any “feasible” payoff vector with proper selection of punishment strategy. 24/67 Cognitive Radio Technologies, 2007 Impact of Communication on Strategies • Players agree to play in a certain manner • Threats can force play to almost any state – Breaks down for finite number of stages Nada C N nada 0,0 -5,5 -100,0 c 5,-5 -1,1 -100,-1 n 0,-100 -1,-100 -100,-100 Cognitive Radio Technologies, 2007 25/67 Improvement from Punishment • Throughput/unit power gains be enforcing a common received power level at a base station • Punishment by jamming • Without benefit to deviating, players can operate at lower power level and achieve same throughput A. MacKenzie and S. Wicker, “Game Theory in Communications:26/67 Motivation, Explanation, and Application to Power Control,” Globecom2001, Cognitive Radio Technologies, 2007 pp. 821-825. Instability in Punishment • Issues arise when radios aren’t directly observing actions and are punishing with their actions without announcing punishment • Eventually, a deviation will be falsely detected, punished and without signaling, this leads to a cascade of problems V. Srivastava, L. DaSilva, “Equilibria for Node Participation in Ad Hoc Networks – An Imperfect Monitoring Approach,” ICC 06, June 2006, vol 8, pp. 3850-3855 27/67 Cognitive Radio Technologies, 2007 Comments on Punishment • Works best with a common controller to announce • Problems in fully distributed system – Need to elect a controller – Otherwise competing punishments, without knowing other players’ utilities can spiral out of control • Problems when actions cannot be directly observed – Leads to Byzantine problem • No single best strategy exists – Strategy flexibility is important – Significant problems with jammers (they nominally receive higher utility when “punished” • Generally better to implement centralized controller – Operating point has to be announced anyways 28/67 Cognitive Radio Technologies, 2007 Cost Adjustments • Concept: Centralized unit dynamically adjusts costs in radios’ objective functions to ensure radios operate on desired point ui a ui a ci a • Example: Add -12 to use of wideband waveform 29/67 Cognitive Radio Technologies, 2007 Comments on Cost Adjustments • Permits more flexibility than policy – If a radio really needs to deviate, then it can • Easy to turn off and on as a policy tool – Example: protected user shows up in a channel, cost to use that channel goes up – Example: prioritized user requests channel, other users’ cost to use prioritized user’s channel goes up (down if when done) 30/67 Cognitive Radio Technologies, 2007 Global Altruism: distributed, but more costly • Concept: All radios distributed all relevant information to all other radios and then each independently computes jointly optimal solution – Proposed for spreading code allocation in Popescu04, Sung03 • • • • C = cost of computation I = cost of information transfer from node to node n = number of nodes Distributed – nC + n(n-1)I/2 • Centralized (election) – C + 2(n-1)I • Price of anarchy = 1 • May differ if I is asymmetric 31/67 Cognitive Radio Technologies, 2007 Improving Global Altruism • Global altruism is clearly inferior to a centralized solution for a single problem. • However, suppose radios reported information to and used information from a common database – n(n-1)I/2 => 2nI • And suppose different radios are concerned with different problems with costs C1,…,Cn • Centralized – Resources = 2(n-1)I + sum(C1,…,Cn) – Time = 2(n-1)I + sum(C1,…,Cn) • Distributed – Resources = 2nI + sum(C1,…,Cn) – Time = 2I + max (C1,…,Cn) 32/67 Cognitive Radio Technologies, 2007 Example Application: • Overlay network of secondary users (SU) free to adapt power, transmit time, and channel • Without REM: – Decisions solely based on link SINR • With REM – Radios effectively know everything Upshot: A little gain for the secondary users; big gain for primary users 33/67 From: Y. Zhao, J. Gaeddert, Cognitive Radio Technologies, 2007 K. Bae, J. Reed, “Radio Environment Map Enabled SituationAware Cognitive Radio Learning Algorithms,” SDR Forum Technical Conference 2006. Comments on Radio Environment Map • Local altruism also possible – Less information transfer • Like policy, effectively needs a common language • Nominally could be centralized or distributed database 34/67 Cognitive Radio Technologies, 2007 Potential Games • Existence of a function (called the potential function, V), that reflects the change in utility seen by a unilaterally deviating player. • Cognitive radio interpretation: () – Every time a cognitive radio unilaterally adapts in a way that furthers its own goal, some realvalued function increases. 35/67 time Cognitive Radio Technologies, 2007 Exact Potential Game Forms • Many exact potential games can be recognized by the form of the utility function 36/67 Cognitive Radio Technologies, 2007 Implications of Monotonicity • Monotonicity implies – Existence of steady-states (maximizers of V) – Convergence to maximizers of V for numerous combinations of decision timings decision rules – all self-interested adaptations • Does not mean that that we get good performance – Only if V is a function we want to maximize 37/67 Cognitive Radio Technologies, 2007 Interference Reducing Networks • Concept – Cognitive radio network is a potential game with a potential function that is negation of observed network interference • Definition I i iN • Implementation: () – A network of cognitive radios where each adaptation decreases the sum of each radio’s observed interference is an IRN time – Design DFS algorithms such that network is a potential game 38/67 with -V Cognitive Radio Technologies, 2007 Bilateral Symmetric Interference • Two cognitive radios, j,kN, exhibit bilateral symmetric interference if g jk p j j , k g kj pk k , j j j , k k • k – waveform of radio k • pk - the transmission power of radio k’s waveform • gkj - link gain from the transmission source of radio k’s signal to the point where radio j measures its interference, • k , j - the fraction of radio k’s signal that radio j cannot exclude via processing (perhaps via filtering, despreading, or MUD techniques). What’s good for the goose, is good for the gander… Source: http://radio.weblogs.com/0120124/Graphics/geese2.jpg Cognitive Radio Technologies, 2007 39/67 Bilateral Symmetric Interference Implies an Interference Reducing Network • Cognitive Radio Goal: ui I i g ji p j i , j jN \ i • By bilateral symmetric interference g ki pk k , i gik pi i , k bki k , i bik i , k • Rewrite goal ui bik i , k kN \ i • Therefore a BSI game (Si =0) i 1 V g ki pk k , i iN k 1 • Interference Function 2V • Therefore profitable unilateral deviations increase V and decrease () – an IRN 40/67 Cognitive Radio Technologies, 2007 An IRN 802.11 DFS Algorithm • Suppose each access node measures the received signal power and frequency of the RTS/CTS (or BSSID) messages sent by observable access nodes in the network. • Assumed out-of-channel interference is negligible and RTS/CTS transmitted at same Start power Listen on Channel LC RTS/CTS energy detected? y n Note address of access node, a Pick channel to listen on, LC ui f I i f g ki pk f i , f k Update interference table k N \ i 1 fi , f k 0 fi f k fi f k n g jk p j f j , f k g kj pk f k , f j Measure power of access node in message, p Cognitive Radio Technologies, 2007 Time for decision? y Use 802.11h to signal change in OC to clients Apply decision criteria for new operating channel, OC 41/67 Statistics Reduction in Net Interference 70 60 • Reduction in Net Interference (dB) 30 cognitive access nodes in European UNII bands • Choose channel with lowest interference • Random timing • n=3 • Random initial channels • Randomly distributed positions over 1 km2 Asynchronous Round-robin Legacy Devices 50 40 30 20 10 0 0 10 20 30 40 50 60 70 Number of Access Nodes 80 90 100 Reduction in Net Interference 42/67 Cognitive Radio Technologies, 2007 Ad-hoc Network • Possible to adjust previous algorithm to not favor access nodes over clients • Suitable for ad-hoc networks 43/67 Cognitive Radio Technologies, 2007 Comments on Potential Games • All networks for which there is not a better response interaction loop is a potential game • Before implementing fully distributed GA, SA, or most CBR decision rules, important to show that goals and action satisfy potential game model • Sum of exact potential games is itself an exact potential game – Permits (with a little work) scaling up of algorithms that adjust single parameters to multiple parameters • Possible to combine with other techniques – Policy restricts action space, but subset of action space remains a potential game (see J. Neel, J. Reed, “Performance of Distributed Dynamic Frequency Selection Schemes for Interference Reducing Networks,” Milcom 2006) – As a self-interested additive cost function is also a potential game, easy to combine with additive cost approaches (see J. Neel, J. Reed, R. Gilles, “The Role of Game Theory in the Analysis of Software Radio Networks,” SDR Forum02) • More on potential games: – Chapter 5 in Dissertation of J. Neel, Available at http://scholar.lib.vt.edu/theses/available/etd-12082006-141855/ Cognitive Radio Technologies, 2007 44/67 Token Economies • Pairs of cognitive radios exchange tokens for services rendered or bandwidth rented • Example: – Primary users leasing spectrum to secondary users • D. Grandblaise, K. Moessner, G. Vivier and R. Tafazolli, “Credit Token based Rental Protocol for Dynamic Channel Allocation,” CrownCom06. – Node participation in peer-to-peer networks • T. Moreton, “Trading in Trust, Tokens, and Stamps,” Workshop on the Economics of Peer-to-Peer Systems, Berkeley, CA June 2003. • Why it works – it’s a potential game when there’s no externality to the trade 45/67 Cognitive Radio Technologies, 2007 Comments on Network Options • Approaches can be combined – Policy + potential – Punishment + cost adjustment – Cost adjustment + token economies • Mix of centralized and distributed • Potential game approach has lowest complexity, but cannot be extended to every problem • Token economies requires strong property rights to ensure • Punishment can also be implemented at a choke point in the network 46/67 Cognitive Radio Technologies, 2007 Commercial Cognitive Radio Standards 802.11h,y, 802.16h, 802.22 47 802.11j – Policy Based Radio 2.4 GHz • Explicitly opened up Japanese spectrum for 5 GHz operation • Part of larger effort to force equipment to operate based on geographic region, i.e., the local policy Lower Upper U.S. 2.402 2.48 Europe 2.402 2.48 Japan 2.473 2.495 Spain 2.447 2.473 France 2.448 2.482 5 GHz US UNII Low 5.15 – 5.25 (4) 50 mW UNII Middle 5.25 – 5.35 (4) 250 mW UNII Upper 5.725-5.825 (4) 1 W 5.47 – 5.725 GHz released in Nov 2003 Europe 5.15-5.35 200 mW 5.47-5.725 1 W Japan 4.9-5.091 48/67 5.15-5.25 (10 mW/MHz) unlicensed Cognitive Radio Technologies, 2007 802.11e – Almost Cognitive • Enhances QoS for Voice over Wireless IP (aka Voice over WiFi ) and streaming multimedia • Changes – Enhanced Distributed Coordination Function (EDCF) • Shorter random backoffs for higher priority traffic – Hybrid coordination function (orientation) • • • Defines traffic classes In contention free periods, access point controls medium access (observation) Stations report to access info on queue size. (Distributed sensing) 49/67 Cognitive Radio Technologies, 2007 802.11h – Unintentionally Cognitive • Dynamic Frequency Selection (DFS) – Avoid radars • – • Listens and discontinues use of a channel if a radar is present Uniform channel utilization Transmit Power Control (TPC) – – – – Interference reduction Range control Power consumption Savings Bounded by local regulatory conditions Cognitive Radio Technologies, 2007 50/67 802.11h: A simple cognitive radio Observe – – Must estimate channel characteristics (TPC) Must measure spectrum (DFS) Orientation Orient a) Radar present? b) In band with satellite?? c) Bad channel? d) Other WLANs? Observe Decision – – – Implement decision Learn – Learn Change frequency Change power Nothing Action Decide Act Outside World Not in standard, but most implementations should learn the environment to address intermittent signals 51/67 Cognitive Radio Technologies, 2007 IEEE 802.22 • Wireless Regional Area Networks (WRAN) – Aimed at bringing broadband access in rural and remote areas – Takes advantage of better propagation characteristics at VHF and low-UHF – Takes advantage of unused TV channels that exist in these sparsely populated areas • 802.22 is to define: – Physical layer specifications – Policies and procedures for operation in the VHF/UHF TV Bands between 54 MHz and 862 MHz – Cognitive Wireless RAN Medium Access Control 52/67 Cognitive Radio Technologies, 2007 802.22 Status and Objectives Objectives Status • Specify PHY and MAC • 10 proposals merged for fixed point-tomultipoint wireless into 1 draft proposal at regional area networks March Plenary (March operating in the VHF/UHF TV broadcast 5-10, Denver CO) bands between 54 MHz and 862 MHz. • Still working on • Strict non-interference bringing to ballot with incumbent licensed services. • Aimed at bringing broadband access in rural and remote areas 53/67 PAR: http://www.ieee802.org/22/802-22_PAR.pdf Cognitive Radio Technologies, 2007 802.22 Deployment Scenario • Devices – Base Station (BS) – Customer Premise Equipment (CPE) • Master/Slave relation – BS is master – CPE slave • Max Transmit CPE 4W 54/67 Cognitive Radio Technologies, 2007 Figure from: IEEE 802.22-06/0005r1 Proposed PHY Features of 802.22 • • • • Data Rates 5 Mbps – 70 Mbps Point-to-multipoint TDD/FDD DFS, TPC Adaptive Modulation – QPSK, 16, 64-QAM, Spread QPSK • • • • • OFDMA on uplink and downlink Use multiple contiguous TV channels when available Fractional channels (adapting around microphones) Space Time Block Codes Beam Forming – No feedback for TDD (assumes channel reciprocity) • 802.16-like ranging 55/67 Cognitive Radio Technologies, 2007 Possible MAC Features of 802.22 • 802.16 MAC plus the following – Multiple channel support – Coexistence • Incumbents • BS synchronization • Dynamic resource sharing – Clustering support – Signal detection/classification routines • Security based on 802.16e security 56/67 Cognitive Radio Technologies, 2007 Cognitive Aspects of 802.22 • Observation – – – – Signal strength and feature detection Aided by distributed sensing (CPEs return data to BS) Digital TV: -116 dBm over a 6 MHz channel Analog TV: -94 dBm at the peak of the NTSC (National Television System Committee) picture carrier – Wireless microphone: -107 dBm in a 200 kHz bandwidth. – Possibly aided by spectrum usage tables • Orientation – Infer type of signals that are present • Decision – Frequencies, modulations, power levels, antenna choice (omni and directional) • Policies – 4 W Effective Isotropic Radiated Power (EIRP) – Spectral masks, channel vacation times 57/67 C. Cordeiro, L. Challapali, D. Birru, S. Shankar, “IEEE 802.22: The First Worldwide Wireless Standard based on Cognitive Radios,” Cognitive Radio Technologies, 2007 IEEE DySPAN2005, Nov 8-11, 2005 Baltimore, MD. Sensing Aspects of 802.22 • Region based sensing CPE Number = 400, IT Number = 4 100 – Remote aided sensing 90 • Algorithm: 80 Grid Index Y – Partition cell into disjoint regions – For each region assign a remote (Customer Premise Equipment) • Example considered squares with 500 m sides 70 60 50 40 30 20 10 0 0 10 20 – CPE feeds back what it finds • Number of incumbents • Occupied bands Cognitive Radio Technologies, 2007 30 40 50 60 Grid Index X 70 80 90 100 Source: IEEE 802.22-06/0048r0 58/67 802.16h • Draft to ballot Oct 06, 67% approve, resolving comments) • Improved Coexistence Mechanisms for LicenseExempt Operation Basically, a cognitive radio standard Incorporates many of the hot topics in cognitive radio • • – – – – • Token based negotiation Interference avoidance Network collaboration RRM databases Coexistence with non 802.16h systems – Regular quiet times for other systems to transmit From: M. Goldhamer, “Main concepts of IEEE P802.16h / D1,” Document Number: IEEE C802.16h-06/121r1, November 13-16, 2006. 59/67 Cognitive Radio Technologies, 2007 General Cognitive Radio Policies in 802.16h • Must detect and avoid radar and other higher priority systems • All BS synchronized to a GPS clock • All BS maintain a radio environment map (not their name) • BS form an interference community to resolve interference differences • All BS attempt to find unoccupied channels first before negotiating for free spectrum – Separation in frequency, then separation in time 60/67 Cognitive Radio Technologies, 2007 DFS in 802.16h • Adds a generic algorithm for performing Dynamic Frequency Selection in license exempt bands • Moves systems onto unoccupied channels based on observations Generic DFS Operation Figure h1 61/67 Cognitive Radio Technologies, 2007 (fuzziness in original) Adaptive Channel Selection • Used when BS turns on • First – attempt to find a vacant channel – Passive scan – Candidate Channel Determination – Messaging with Neighbors • Second – attempt to coordinate for an exclusive channel • If unable to find an empty channel, then BS attempts to join the interference community on the channel it detected the least interference Figure h37: IEEE 802.16h-06/010 Draft IEEE Standard for Local and metropolitan area networks Part 16: Air Interface for Fixed Broadband 62/67 Wireless Access Systems Amendment for Improved Coexistence Cognitive Radio Technologies, 2007 Mechanisms for License-Exempt Operation, 2006-03-29 Collaboration • BS can request interfering systems to back off transmit power • Master BS can assign transmit timings – Intended to support up to 3 systems (Goldhammer) • Slave BS in an interference community can “bid” for interference free times via tokens. • Master BS can advertise spectrum for “rent” to other Master BS • Collaboration supported via Base Station Identification Servers, messages, and RRM databases • Interferer identification by finding power, angle of arrival, and spectral density of OFDM/OFDMA preambles • Every BS maintains a database or RRM information which can be queried by other BS – This can also be hosted remotely – Bid by tokens 63/67 Cognitive Radio Technologies, 2007 802.16h • • • Improved Coexistence Mechanisms for License-Exempt Operation Explicitly, a cognitive radio standard Incorporates many of the hot topics in cognitive radio – Token based negotiation – Interference avoidance – Network collaboration – RRM databases • Coexistence with non 802.16h systems – Regular quiet times for other systems to transmit From: M. Goldhamer, “Main concepts of IEEE P802.16h / D1,” Document Number: IEEE C802.16h-06/121r1, November 13-16, 2006. 64/67 Cognitive Radio Technologies, 2007 802.11y • Ports 802.11a to 3.65 GHz – 3.7 GHz (US Only) – – • • FCC opened up band in July 2005 Ready 2008 Intended to provide rural broadband access Incumbents – Band previously reserved for fixed satellite service (FSS) and radar installations – including offshore – Must protect 3650 MHz (radar) – Not permitted within 80km of inband government radar – Specialized requirements near Mexico/Canada and other incumbent users • Leverages other amendments – Adds 5,10 MHz channelization (802.11j) – DFS for signaling for radar avoidance (802.11h) • • Working to improve channel announcement signaling Database of existing devices – Access nodes register at http://wireless.fcc.gov/uls – Must check for existing devices at same site Cognitive Radio Technologies, Source: 2007 IEEE 65/67 802.11-06/0YYYr0 802.11s • Modify 802.11 MAC to create dynamic self-configuring network of access points (AP) called and Extended Service Set (ESS) Mesh • Status – Standard out in 2008 – Numerous mesh products available now – Involvement from Mitre, NRL IP or Ethernet • Features – Automatic topology learning, dynamic path selection – Single administrator for 802.11i (authentication) – Support higher layer connections – Allow alternate path selection metrics – Extend network merely by introducing access point and configuring SSID Cognitive Radio Technologies, 2007 66/67 Networking Summary • Many different solutions – Inferring context to select appropriate solution is important • Centralized solutions always present the option of the optimal solution, but may not find the solution in a useful amount of time or may be overly complex • Distributed solutions (generally) find solutions faster and with less complexity but may be suboptimal • Techniques for designing cognitive networks rapidly migrating into commercial standards – REMs – 802.11y, 802.16h – Token economy – 802.22 – Policy – 802.16h, 802.11, 802.22 67/67 Cognitive Radio Technologies, 2007