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Trends of Communications Technologies Trends of Communications Technologies Myung Jong Lee Dept. of Electrical Engineering Cilee@ccny.cuny.edu KOCSEA Symposium 2009
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2 Outline Evolution of Communications Technologies Recent Entropy Boosters Industry activities: cases in IEEE 802.15
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3 NBT? Extrapolation Past historical samples Energy conservation law: 1 st law of thermodynamics Law of entropy: 2 nd law of thermodynamics
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4 Entropy as a measure (1) Entropy In thermodynamics: Definition: S=q/T (joules/degree) –Tendency of spontaneous energy becoming diffused and spread out Natural progress or phenomena in the direction of increased entropy –Wind blows, ice melts, mountain lowers and valley rises, –Berlin wall torn down, equal rights for women, etc
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5 Entropy as a measure (2) In a dictionary Degree of freedom or degree of randomness or chaos, degradation In Information Theory: P i : the probability of event I Maximum Entropy when P i ‘ s are equal. Uniform distribution –(socio-political views) elite group (monarchy) democracy (all people) –Possession of information: “ 知彼知己 百戰百勝 ” Internet, ubiquitous networks: information age!
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6 Entropy as a measure (3) In short, Leveling Force is the core of the entropy law! Democratization, equal right ’ s movement, empowering individuals, fostering egalitarian society even for animal, plants, and environment (utopia?) etc.
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7 Entropy Drivers Decentralization, distribution Flexibility, future proof Personalization, user-centric Horizontal market Blurred distinction between computer and communications Cross cutting disciplines Etc, etc.
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8 Quntum Jumps in Entropy Centralized system to distributed system Circuit Switching to Packet Switching Wired to Wireless Infrastructure to Infrastructureless Toward Ubiquitous Networks Recent Entropy boosters In Communications
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9 1. Centralized to distributed Single large computer: single terminal to remote multiterminal Multiple mini computers Many personal computers Ubiquitous computing or networking Provide computing resources wherever demands exist. Grid computing, nano computing, biocomputing, etc This evolution demands efficient communication and management
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10 2. Circuit to Packet Circuit switching serves well for voice service for over 100 years Dedicated services to shared services Again, demands for flexibility, multimedia (voice, video, data), personalization lead to packet switching Packet switched Internet -> VOIP No technology without problems! Problems are mainly due to increased degree of randomness Diverse QoS’s for multimedia, Congestion, etc
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11 3. Wired to Wireless People as well as machine long to be untethered Evolution of wireless communications 1 st generation: analog AMPS 2 nd generation: digital (voice+data) IS-95, GSM, CDPD for data 3 rd generation: digital (voice+data+low rate video) IMT-2000 (3GPP, 3GPP2), Cdma 2000, GSM (wider bandwidth) WBMA (IEEE 802.16, 20), WLAN (IEEE802.11), WPAN (IEEE 802.15, ZigBee), WBAN (IEEE 802.15 IG) 4 th generation: Network convergence multimedia (HDTV), IMT-Advanced (ITU-R) Unifying PHY, MAC with SDR?
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13 4. Infrastructure to infrastructureless Wireless Communication infrastructure Base station or Access point based WWAN “ last mile ” wireless WLAN (WiFi) “ last 100m ” wireless WPAN “ last 10m ” wireless WBAN “ last 2m ” wireless Or, Macrocell, Microcell, Nanocell, Femtocell Infrastructureless or Wireless Ad hoc networks Peer-to-peer mesh communications without BS or AP No “ last x ” wireless Mobile Ad hoc networks (MANET), Wireless Mesh networks, WSN, WBAN
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14 Ad Hoc Networks Infrastructureless Wireless nodes possibly with mobility Possibly multiple hops between network nodes Router or relay node as well as end-node Multihop occurs as data rate gets higher. IEEE 802.11b (100m) 802.11a (<<100m) IEEE 802.15.3c (mmwave) Multihp, directional antenna IEEE 802.11ac, ad
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15 Applications for ad hoc networks Emergency networks Search-and-rescue, firefighting, policing Civilian environments Gaming, meeting room, stadium WPAN, WBAN Cell phone, PDA, earphone, wrist watch Vehicle to Vehicle networks Military Wireless mesh networks Wireless Sensor networks Etc
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16 5. Ubiquitous Networking Key capability to maximally satisfy personalized requirements- user-centric “awareness” technology Device-to-Device communications At the center of U Network lies the wireless sensor/control networks
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17 Courtesy: David Nagel 80’s Microprocessor 90’s Internet This decade—”Sensors” Gary Boone of the Accenture Technologies Laboratory asserted that "browsing reality" will prove to be the killer application for wireless sensor networks, Wireless Sensor Networks
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18 Wireless Sensor Networks Multihop ad hoc networks, but relatively static Resource constraints: energy, processing, memory Potentially numerous (inexpensive) Wireless channels: intermittent and bandwidth-limited Miniaturization
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19 WIRELESS SENSOR NETWORKS Courtesy: David Nagel
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20 Automation and control: home Factory, warehouse Energy saving (NYC apartment complex project) Monitoring Safety, security Health (BAN) Environments (agriculture, building, aqueous, etc) Situational awareness and precision asset location (PAL) military actions Ssearch and rescue (breadcrumb comm, use of mice?) autonomous manifesting Inventory tracking Entertainment learning games interactive toys Applications
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What a home! Courtesy: Zigbee
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22 Some Research Issues Key is to integrate communication, processing, and sensors in a miniaturized platform to provide ubiquitous sensing and control environment. General Energy, Energy harvesting Crosslayer Optimization (QoS, scalability, reliability, efficiency) Self Organization, Self healing Connection to widearea networks: Gateway (conversion or convergence)—IEEE 802.15.5, IETF 6lowpan, ROLL Security data fusion, mining Miniaturization (antenna, etc)
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23 Research Issues (2) At Protocol Layers PHY (adaptive modulation, voltage scaling, antenna, CR) Energy Efficient MAC (synchronous, asynchronous, asymmetry approach, wakeup radio, multichannel/CR MAC, Virtual MIMO, cooperation) Link control (hybrid of ARQ/FEC, power control) Network (addressing, routing (unicast, multicast, broadcast, geocast), beacon scheduling, topology control, frequency agility, CR, cooperation, network coding) Transport (wireless multihop) Applications (data fusion, unifying data format IEEE1451)
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24 Energy Saving Example
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Energy Saving for WSN For IEEE 802.15.5 WPAN Mesh Power saving algorithms are needed for IEEE 802.15.5 WPAN Mesh for wireless sensor/control networks Using IEEE 802.15.4 device One of the advantage of using IEEE 802.15.5 mesh for WSN (sleeping router)
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Majority of WSNs are low-data-rate The release of IEEE 802.15.4 (2003, 2006) - Many variants: 15.4a, 15.4c, 15.4d, 15.4f (RFID), 15.4e (MAC enhancement), 15.4g (SUN) - Smart Grid, Home area networks, Industrial applications -RF4CE -Seems coming of its age Why Using IEEE 802.15.4 device?
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Bandwidth and data rate An Overview of IEEE 802.15.4 (1) 0110... 1126... 868 MHz902 – 928 MHz2.4 – 2.4835 GHz 20 Kb/s40 Kb/s250 Kb/s 2 MHz5 MHz 868/915 MHz PHY2.4 GHz PHY Channel: Frequency: Data rate:
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Beacon Mode and Superframe Structure An Overview of IEEE 802.15.4 (2)
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Mesh layer solution based on IEEE 802.15.4-2006 Supporting long battery life Two AA batteries, 1year Flexible active time End-to-end latency constraint Considering receiver energy consumption Tree relation Easy implementation Design Consideration
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Battery Life Two AA batteries 2000 mA-hr Energy consumption of cc2420 Tx; 17.4 mA Rx; 19.7 mA When a device turns on the transceiver 4.2 days When the device keeps 5% active time 84 days (under 3 months) Minimizing active ratio is the key!
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Mesh Layer Solution Why Algorithms at Mesh Layer? MAC access limited in many transceivers, -MAC information not accessible -Cannot add MAC control frames -Only access via standard primitives At mesh layer, flexible and platform independent Timing problem Can not guarantee response time Ex. The time from calling MCPS-DATA.request to starting backoff
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Representative Algorithms 6 Generic Power Saving Algorithms applicable to a wide range of MAC protocols With beacon mode Determining parameters: Beacon interval and superframe duration -Non-beacon Tracking (NBT) -Beacon Tracking (BT) With non-beacon mode Determining parameters: Wakeup interval and wakeup duration - Long Preamble Emulation (LPE); BMAC -Long Preamble Emulation with Ack (LPEA); XMAC -Non-beacon Tracking Emulation (NTE) -Global Synchronization (GS); SMAC
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Algorithms with Beacon Mode Reliability, Beacon collision Upper layer control also required
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Synchronous Algorithm with Non-Beacon SMAC Time control precision Difficult to synchronize all devices
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LPE LPEA Asynchronous with Non-beacon Mode
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Average active ratio with the beacon mode Three Transmitters and one receiver
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Average active ratios with the non-beacon mode
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Hop latencies of the algorithms
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Beacon vs. Non-beacon Mode Beacon mode Suitable for the networks with Long beacon interval & small number of neighbors Hard time beacon transmission beacon collision Unreliable NBT; beacon collision BT; Sync tree problem Upper layer support for Active time scheduling, minimizing active time, broadcasting frames Non-beacon mode Requires all operations at the mesh layer Difficulty in timing control Flexible !, can make better solutions for large scale networks
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For Large WSN Environment with LPEA The Key to control the energy consumption is the wakeup interval Global Optimization with Unicast and broadcast Minimize Energy consumption vs Maximizing Network life time with wake-up interval Homogeneous WI Non-homogeneous WI Heuristics
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For Network Environment with LPEA 50 Node Network
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For Network Environment with LPEA
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43 Optimization Problem for unicast Minimize energy consumption Maximize Network Lifetime Active Ratio
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44 Performance Comparison
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45 Performance Comparison
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46 Quntum Jumps in Entropy Centralized system to distributed system Circuit Switching to Packet Switching Wired to Wireless Infrastructure to Infrastructureless Toward Ubiquitous Networks Recent Entropy boosters In Communications
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47 Dynamic Spectrum Technology-leveling disparity in spectrum use Leveling disparity Cognitive Radio MIMO Leveling the spatial & frequency disparity Array gain, SNR gain, enhanced data rate, etc Cooperative Communications (virtual MIMO) Leveling spatial and frequency disparity WBAN Personalization, decentralization, leveling spatial and frequency disparity FiWi lowering the wall between Fiber and Wireless Ex: RoF (Radio over Fiber) Recent Entropy Boosters
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48 Bandwidth—name of the game Avenues Bandwidth and power efficiency (Bits/Hz/Joule)--64QAM and Turbo coding get near Shannon limit. –fill the hole in bandwidth Dynamic spectrum; spectrum sharing…fill the gap New spectrum: very costly, therefore, exploring tera hertz band (electronics limitation) –IEEE 802.15 Interest group for THz. –dispersion to unexplored territory Spatial reuse: cellular concept. (lowering transmit power – boosting channel/hz
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49 Dynamic Spectrum FCC 2004 Policy change New spectrum policy to mitigate the scarcity of spectrum resource Unlicensed operation for TV bands (white space) Ch. 5-13, Ch.21-51 (except ch.37) (76-698 Mhz) Ch. 14-21 in rural area Opportunistic Spectrum Sharing : Space and Time Primary (vertical) sharing—finding and using white space Secondary (horizontal) sharing –dissimilar networks then sharing spectrum efficiently Industrial Standards Development IEEE 802.22 (Wireless Regional Area Network: WRAN) IEEE 802.18 (Coexistence) IEEE P1900 ECMA
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50 16% duty cycle, 30Mhz-3 Ghz, 24Hrs Actually even lower ( <10%) Spectrum Usage NYC Sept 1, 2004 copyright kiran.challapali@philips.com
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51 Cognitive Radio To protect licensed service operator Essential component of SDR To aware of spectrum usage in vicinity Time and space Cooperative sensing, etc Intelligent decision on sensing results. Current research focus: Fast and accurate spectrum sensing (energy & feature) Spectrum management Radio technologies from IEEE 802.22-04- 0003r0
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52 Copyright: pkolodzy@stevens-tech.edu Inerference Avoidance
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53 Scope To specify the air interface (PHY and MAC) Fixed point-to-multipoint wireless regional area networks operating in the VHF/UHF TV broadcast bands between 500MHz and 862 MHz. Purpose Alternatives to wireline broadband access to diverse geographic areas (rural areas, etc), Use of TV bands. IEEE 802.22 WRAN
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54 IEEE 802.22 from IEEE 802.22-04- 0003r0
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55 Cooperative communication Node close together can cooperate each other: cooperatively receive, form a multiple-antenna receiver cooperatively transmit, form a multiple-antenna transmitter Virtual MIMO It may not be practical for sensor networks to adopt the real MIMO (size, power), but cooperation between sensor nodes can achieve a virtual MIMO.
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56 Basic Relay Model Two general approaches for Relay Decode-Forward Amplify-Forward Relay scenario: Rayleigh fading channels + AWGN noise Half-Duplex constraint Channel State Information (CSI)
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57 Issues Gains vs. Overhead How much gains from cooperation? Will the gain outweigh overhead incurred by it? Cooperative partner selection, CSI information sharing Cooperative coding design (space-time coding) Power control Real network environment Will cooperation cause more collisions in real large networks? How often will cooperation happen in a practical network? Performance gain at the relay node at the price of its own thr oughput ? Will cooperation improve performance of overall networks?
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58 WBAN Natural extension WRAN WMAN WLAN WPAN WBAN Nominal range of 2 m New regulatory body: FDA in addition to FCC Recently Standard activity IEEE 802.15.6 Wearable and Implanted Single PHY or Multiple PHY Frequency BANDs ISM Band: 868/915MHz, 2.4GHz, 5.8GHz UWB band: 150-650MHz, Low band (3.24-4.74GHz), High band (5.94- 10.23GHz) Medical bands –MICS (medical implant communication service) (402-405MHz) –WMTS (wireless medical telemetry service) ( 608-614 MHz, 1395-1400MHz and 1427-1429.5MHz) –MEDS (medical data service) (401-402MHz and 405-406MHz) –New Band? Intrabody
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July 2006 Body Area Networks Usage Scenarios Body senor network Fitness monitoring Wearable audio/video Mobile device centric Remote control & I/O devices Courtesy: Stefan Drude, Philips
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July 2006 Courtesy: Stefan Drude, Philips Body Sensor Network Medical application Vital patient data Wireless sensors Link with bedside monitor Count on 10 – 20 sensors Five similar networks in range Minimum setup interaction Potentially wide application Total traffic / patient < 10 kbps
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61 Medical and Entertainment www.newscientists.com
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2015-08-27 Gastrointestinal Camera www.givenimaging.com 5
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63 IEEE 802.15.6 Technical Issues Operates on, inside, or in the vicinity of the body. Limited range (<.01 – 2 meters) The channel model will include human body effects. (absorption, health effect s) Extremely low consumption power (.1 to 1 mW) for each device Capable of energy scavenging / battery-less operation Support scalable Data Rate: 0.01 – 1,000 kbps (opt 10Mbps) Support different classes of QoS for high reliability, asymmetric traffic, power constrained. Needs optimized, low complexity MAC and Networking layer High number of simultaneously operating piconets required. Application specific, security/privacy required. Small form factor for the whole radio, antenna, power supply system Locating radios ( ” find me ” ) mode.
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65 IEEE 802.15 (WPAN) Wireless Personal Area Networks (WPAN) with nominal range of 10- 30m Branched from IEEE 802.11 WG 10 years ago Completed: 802.15.1: Bluetooth v.1.0: 1Mbps 802.15.2: Coexistence between 802.11 802.15.3a: Very high rate UWB PHY for commercial applications (disbanded) 802.15.3b: MAC for high rate applications 802.15.3c: PHY 500Mbps for commercial applications at 60GHz 802.15.4, 4b: low power, low rate (256Kbps)--lower two layers for ZigBee 802.15.4a: UWB for ranging and midrate upto 25 Mbps 802.15.5: WPAN Mesh based on 15.4b—2.5 layer approach 802.15.c, 15.d: 15.4 PHY for China and Japan
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66 IEEE 802.15 (WPAN) On going 802.15.4e: MAC enhancement for inudustrial applications 802.15.4g: SUN for smart grid 802.15.6: WBAN 802.15.7: Visual Light Communications 802.15.4f: RFID Interest Group: Terahertz group More details at IEEE 802.15 WG home page!
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67 In summary, Entropy Law may be able to explain and predict, in perspective, the IT technology trend !
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68 Advanced Wireless Research Lab (CUNY) Basic Research Standard Activities Testbed & Prototype
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Slide 69 Myung. J. Lee CUNY
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