Panel Pervasive Communications: All the Time, Everywhere

Panel Pervasive Communications: All the Time, Everywhere Rene L. Cruz UCSD Networking Joseph A. Bannister ISI and USC Networking Daniel J. Blumenthal UCSB Optical Networking Pamela Cosman UCSD Speech, Image, Audio and Video Coding Babak Daneshrad UCLA MIMO Wireless Urbashi Mitra USC Wireless Jeyhan Karaoguz Broadcom Wireless Avneesh Agrawal Qualcomm Cellular Wireless Al Servati Conexant Digital Home

State and Future of Networking Rene L. Cruz Professor UC San Diego Department of Electrical and Computer Engineering

Important Factors reliance on information networks is increasing performance requirements of access networks are increasing: access is bottleneck (cost) low cost, energy efficient wireless link technology (short,medium, and long range) expansion of un-licensed frequency spectrum willingness to pay is very limited

Opportunities and Challenges in Networking Access Networks: Cost Reliability and Performance are Important - Robustness to failures and security breaches Automated Network Control - Carriers - Ad-hoc networks Cooperation in a Competitive Environment - bit pipe provider versus service provider - peer to peer networking

The Future of Networking Joseph Bannister University of Southern California Information Sciences Institute 23 May 2005 Joseph A. Bannister Division Director ISI Computer Networks Division Assistant Director ChevronTexaco CiSoft Research Associate Professor EE-Systems

Four of Networkings Main Challenges Quality of Service Multicast Operations Mobility

Quality of Service Unfulfilled promise of packet switched data networking Nearly 30 years of research and development Reservations, queueing, congestion management ATM, BISDN, RSVP, IntServ, DiffServ, GMPLS Issues: QoS in an expanding infrastructure, extreme link heterogeneity, flexibly designed applications

Multicast Essential for true broadcast Lots of Internet work IETF, PIM, IGMP Currently superseded by peer-to-peer streaming or downloaded content Do customers prefer broadcast or on-demand content? Other uses of multicast: management, coordination, time distribution Anycast in DNS

Operations Includes security, dependability, network management Harvest the advances of AI Critical need as networks grow – sys admin gap Time Complexity Population Network complexity is growing rapidly 1980–2002 Internet annual growth rate was 100% Number of sys admins is growing moderately 1980–2002 sci & eng workforce annual growth rate was 5%

Mobility Ubiquitous connectivity Wireless or wired networks Mobile IP not really a success story Cellular mobility is a success story Voice Data Video – next hurdle

IV. Pervasive Communications: All the Time, Everywhere Optical Networking Daniel J. Blumenthal University of California Santa Barbara, CA California: Prosperity Through Technology 2005 Industry Research Symposium May 23 & 24, 2005

Power and Size Matters Optiputer Mean Performance

Fiber/Microprocessor Bandwidth Bottlenecks Fiber Capacity Increase Outstrips Electronic Switching Capacity Increase Microprocessors will Dissipate Increasing Power with Todays Technology IP Traffic will Continue to Drive Capacity Growth x 2 03 TDM W Aggregate Link Capacity (Gbps) Per Fiber Capacity Continues to Increase Greenfield Optical Switched Transport Networks: A Cost Analysis, C.R. Lima, M.Allen and B.Faer, NFOEC, 2001.

Todays Infrastructure: The Electronics/Optics Boundary Current infrastructure depends heavily on electronics and optics, where the former has strength in processing and the later in transmission WDM Mux/Demux EO/OETDM Muxes/DeMuxes WDM Fiber Access Switch/Router OpticalElectrical Router

Recent Progress in Optical Networking Has increased the functionality and role of optics in the routing and switching at the wavelength circuit level Transmission WDM/Fiber Grooming WDM Fiber Optical Switch ROADM TDM Switch/ Router OETunable EO TDM Multiplexing WDM Mux/ Demux WDM Mux/ Demux WDM Mux/ Demux WDM Mux/ Demux TDM Switch/ Router OETunable EO TDM Multiplexing Transmission WDM/Fiber Grooming Optical Electrical

DARPA Supported Optical Network Related Programs at UCSB CSWDM: 4 Year, 3.5M Integrated Optical Wavelength Converters and Routers for Robust Wavelength- Agile Analog/ Digital Optical Networks DoD-N: 4 Year 15.8M LASOR: A Label Switched Optical Router M. Masanovic, V. Lal, J. Summers, H. -F Chou, E. Skogen, J. S. Barton M. Sysak, D. J. Blumenthal, J. E. Bowers, L. A. Coldren, N. Dagli, E. Hu UCSB: M. Masanovic, V. Lal, J. Summers, H. Poulsen, D. Wolfson, Z. Hu, E. Burmeister, S. Bjorlin, H. Park, J. Chen, A. Tauke-Pedretti, M. Dummer, J. Barton, L. Johansson, M. Davanco, B. Koch, R. Rajaduray, R. Doshi, W. Zhao, D. J. Blumenthal, J. E. Bowers, L. A. Coldren, E. Hu Agility Communications: C. Coldren, G. Fish Calient Networks: O. Jerphagnon, R. Helkey, S. Yuan Cisco Systems: G. Epps, D. Civello, P. Donner JDS Uniphase: D. Al-Salameh Stanford University: Y. Ganjali, N. McKeown, T. Roughgarden, A. Goel

ISP 100Tbps Router 1.28/2.56 Tbps Linecard Todays Technology 32/64 40G Inputs 32/64 40G Outputs ORAM OH Read ERP Line WC/ Regen LASOR Research Vision Routing Protocols for Networks with Small Optical Buffers Integrated Photonic Packet Forwarding Engines Integrated Optical Random Access Memory 40G Optically Labeled Packets Fast Tunable Regenerative All- Optical Wavelength Converters Reconfigurable Optical Backplane Integrated Photonic Optical Header Read- Erase Dense Photonic Integration Optical Packet Forwarding Engine

The integration of optics and electronics at the level of LSI electronics is essential for the long term growth, strategic planning and cost reduction path required for the future of optical networks. Integration Microelectronics Computing Discrete 1950s IC 1960s LSI 1970s VLSI 1980s ULSI 1990s-2000s GSI ??? Microelectronics Computing Discrete 1950s IC 1960s LSI 1970s VLSI 1980s ULSI 1990s-2000s GSI ??? Optics + Electronics High Speed Networks Discrete 1970s-1980s Analog PIC 1980s-1990s Hybrid IC 2000s LSI ??? Optics + Electronics High Speed Networks Discrete 1970s-1980s Analog PIC 1980s-1990s Hybrid IC 2000s LSI ??? RF + Electronics Mobile Discrete 1970s-1980s Hybrid 1980s-1990s Hybrid IC 1990s Silicon 2000s RF + Electronics Mobile Discrete 1970s-1980s Hybrid 1980s-1990s Hybrid IC 1990s Silicon 2000s

InP Monolithic Photonic Integration Hybrid 10 Gbps OQW Mach-Zehnder Modulator WC Tunable Laser Mach-Zehnder Modulator Transmitter out in out 10 Gbps Tunable All- Optical Wavelength Converter 10 Gbps Tunable All- Optical Wavelength Converter + Optical Filter 40Gbps Folded Tunable All- Optical Wavelength Converter in out in out in out in Masanovic, Barton, Sysak, Lal, Summers, Dummer, Raring, Skogen, Blumenthal, Bowers, Coldren UCSB (DoDN) UCSB (CSWDM)

Impact of Optics on Network Architectures Core Metro Enterprise/LAN Transmission Switching and Routing Regeneration Wavelength Conversion Transmission Add/Drop Multiplexing Grooming Regeneration Wavelength Conversion Access Regeneration Add/Drop Multiplexing Wavelength Conversion Switching and Routing

Speech, Audio, Image, and Video Coding Professor, Electrical and Computer Engineering, UCSD Co-Director, Center for Wireless Communications, UCSD Pamela Cosman

Progress of Speech & Audio Coding Extending current systems to handle wideband speech at about 8kbps rate Music, general audio Robustness to delay, packet loss Very low rate coding (100s of bps) Fusion of speech compression and speech recognition Research Focuses: Graph from:

Images: JPEG vs. JPEG % reduction in file size compared to JPEG Lossless JPEG2000 has big improvement Application areas: Medical images (incl. 3D) Scientific images / space Archiving (digital libraries) High-quality digital video editing, digital cinema (Motion-JPEG2000 can outperform MPEG-4) Slow uptake because Legacy JPEG material Does 25-35% improvement warrant widespread replacement? At high rates, JPEG & JPEG2000 have similar performance digital cameras can do without Abundance of bandwidth: 2Mbps download, 130k or 100k image doesnt matter Submarine patents

Progress of Video Compression Bit Rate PSNR (dB) CoderMPEG-4 ASP H.263 HLP MPEG-2 H.264 AVC 39%49%64% MPEG-4 ASP -17%43% H.263 HLP - -31% Bit rate savings over MPEG2

New Technologies & Applications Applications Searching & Indexing, Content-based retrieval, Games, Augmented Reality Compression for sensor and surveillance networks (infrastructure monitoring, traffic conditions, security…) Seamless mobility over heterogeneous networks Disaster response New Technologies Object-based coding: fusion of compression & computer vision Network Coding Joint audio/video coding: exploit correlation More realistic motion models Scalable video & image: adapt to different formats & channels for both images and video…

MPEG4 vs. Scalable Video Coding Features: spatial scalability, temporal scalability, SNR scalability, complexity scalability, … Encoder Low qualitySmall sizeHigh quality Bit-stream Pre-decoder Bit-stream Single-encoding / multi-decoding Very fast pre-decoder Only one bit-stream in server

Wireless Integrated Systems Lab. Multi Antenna (MIMO) Processing and the Second Wireless Revolution Babak Daneshrad University of California, Los Angeles

Wireless Integrated Systems Lab. The Trend Progress in wireless communications requires support for progressively higher data rates under progressively higher levels of mobility. To achieve this, systems must exploit space, the last frontier in the signaling space ! Three forms of spatial (antenna) processing –Phased array beamforming Used in cellular base stations –Diversity processing Used in WLAN access points –MIMO Emerging WLAN n standard Emerging e standard

Wireless Integrated Systems Lab. Multi Input Multi Output (MIMO) Wireless Comms. MODULATOR MIMO Receiver MIMO Receiver x(t) y(t) z(t) r 1 (t) = a 11 x(t)+a 12 y(t)+a 13 z(t) r 3 (t) = a 31 x(t)+a 32 y(t)+a 33 z(t) x(n) y(n) z(n) x(n) y(n) z(n) Different data sent on different transmit antennas All transmissions occur at the same time and in the same frequency band The signal from each transmitter is received at ALL receive antennas (this is not interference) Channel impulse response is a matrix –NxM matrix; where N is the number of TX and M is the number of RX antennas; N>M

Wireless Integrated Systems Lab. Theoretical MIMO Capacity 10x to 20x capacity increase with same total TX power 23 dB (200x) reduction in the required power when bandwidth efficiency is kept constant MIMO Config. 95 % Capacity at 20 dB SNR Required SNR to achieve capacity of 1 bit/sec/Hz 1x12.6 bits/sec/Hz12.8 dB 2x28.0 bits/sec/Hz1.2 dB 4x419.0 bits/sec/Hz-4.9 dB 8x840.8 bits/sec/Hz-9.3 dB

Wireless Integrated Systems Lab. 2x2 MIMO vs a & b

Wireless Integrated Systems Lab. MIMO Economics Spectrum is expensive in licensed bands Spectrum is scarce in unlicensed bands MIMO techniques increase data throughput without increasing bandwidth Signal is expanded in space –Systems can operate at lower carrier frequencies No need for exotic & expensive semiconductor technologies Better signal penetration through walls and around corners –Expense: more sophisticated signal processing

Wireless Integrated Systems Lab. Multi Antenna Processings Here to Stay By 2010 nearly all wireless standards will have elements of MIMO in them n (next generation WLAN) will standardize on MIMO –MIMO enables: video distribution, Gbps enterprise networking –Ratification expected in 1H e (mobile flavor of WiMax) has optional MIMO modes –MIMO enables: building penetration, range extension –Ratification expected in G cellular systems looking to incorporate MIMO modes –MIMO enables: broadband in limited cellular bands –Ratification ? Other wireless systems will deploy some form of multi antenna processing

35 Wireless Research for the Future Urbashi Mitra Professor Co-Director, Communication Sciences Institute Department of Electrical Engineering University of Southern California California: Prosperity through Technology 2005 Industry Research Symposium

36 The Need for SYNERGY open systems interconnect (OSI) stack modified from InetDaemon.com The network IS the channel – A. Sabharwal, Rice University cross-layer designs (again!) wireless sensor networks

37 A New (?) SYNERGY Hardware low complexity UWB receivers Hardware joint design of hardware and algorithms Fano decoder in VLSI P. Beerel & K.Chugg USC Quantized UWB receiver S. Franz & U. Mitra, USC

38 Experimental Wireless? Other disciplines –Physics (experimental and theoretical) Usual province of industry –Where do trained faculty come from? Academic training needed –RF circuits and wireless communication theory –Challenge of providing in a two year MS How can industry/academia collaborate on training new wireless engineers?

39 Academic-Industry Relationships The heyday of Bell Labs –Claude Shannon Where are the new Bell Labs? –Who has the largest market share? Applied Research –Defense model 6.1, 6.2, 6.3 etc. How can industry invest? –Gifts –Support centers –One-by-one agreements –Is there a NEW model? intellectual property }

40 Role of Government Agencies Funding waning for wireless/communications –monotonically decreasing at NSF Move towards a few large-sized programs –Vanishing single investigator grants Impact on industry?

41 What is the Channel? sensor networks ultrawideband Signal Power (dB) Cellular Ambient RF Multipath Effects UHF TV underwater communications coding for fading/MIMO channels

42 Biological Communications? Understand how nature communicates –Inform our communication system design Grow communication receivers –Use biological building blocks to construct classical receivers

43 Problems designing cell-to-cell communication R. Weiss et al, Princeton University capacity of neural communication M. Gastpar, Berkeley B. Rimoldi, EPFL error-correction for DNA crystals Erik Winfree, CalTech

Wireless Challenges: A Billion User Experimental Test Bed Jeyhan Karaoguz Broadcom Corporation

The Current Semiconductor Revolution: Communications In Everything

The Next Communications Challenge: Convergence of Multimedia Content over Home and Mobile Networks Mobile World Home WorldContent Provider Broadband Service Provider Cellular Service Provider

The Path To Convergence in the Broadband World is Pretty Scary Media Servers Media Service Provider Broadband Network Cable DSL 3GPP CDMA Network 3GPP GSM/GPRS Network DVB-HWiMAX Wireless over Unused TV Channels Satellite Audio/Media Sharing Voice SMS MMS HOME Multimedia/Video Smart Phone Telecom Carrier CO WiFi Hotspot

Future Levels of Integration in Mobile Devices Complexity – 1000 DMIPS CPU – 10M polygon/sec 3D graphics – 100M pixel/sec MPEG4 codec – 10 Mbps 3G WWAN – 100Mbps WLAN – 1000Mbps UWB WPAN – Digital Video Broadcasting >500 MHz 32-bit Processor w/FPU Multi-threaded 3D Graphics W/Dual ¼ Mpixel LCD Displays CD-Quality MP3 Encode/Decode Full-Frame MPEG4 Encode/Decode Advanced Power Management WWAN BB/MAC WLAN BB/MAC WPAN BB/MAC Integrated RF DRAM InterfaceFLASH Interface Dual Camera Interface Mobile Communications Super Chip of the Future Power Dissipation is the Limiting Factor

Research Challenges Multi-Modal RF Coexistence MIMO Signal processing for improved range/quality/capacity/features Voice and Audio Quality Inter-Networking Security – Watermarking – DRM – Biometrics User Experience Power Management

50 Qualcomm May 2005 My Vision for Cellular Avneesh Agrawal Qualcomm

51 Qualcomm May 2005 Challenge/Opportunity The key challenge/opportunity for cellular is the widespread adoption of mobile data services. The case for data over cellular –Ubiquity (Anytime/Anywhere) –Location specific content –Higher penetration than wireline internet Only internet experience for many people Challenges –Limited UI –Cost

52 Qualcomm May 2005 Wallet MP3 Player Game Console FM Radio PDA Voice Pager PC Bar Scanner CamcorderWalkie-Talkie Television Newspaper Rolodex Glucometer GPS Device Photo Album Camera Cell-phone: The one device that everyone carries

53 Qualcomm May 2005 Some perspective Over 125 3G operators Over 200M 3G subscribers Over 610 3G mobile devices Over 55 mobile device vendors Projected ~ 1B 3G users in 2009 (~50% of total cellular market) 3G = CDMA2000 (1x, EV-DO) and WCDMA (Rel99, HSDPA, HSUPA) Worldwide cellular subscribers ~1.5B Projected > 2B in 2009 We have just begun to tap into the wireless data market.

54 Qualcomm May 2005 Multicast – a more efficient mechanism for distributing content For multicast services, cost/bit is largely determined by users at cell- edge –Spectral efficiency at edge of cellular systems could be as low as.1 bps/Hz. Cell radius cannot be very large (typical < 1-2 km) –Limited by Uplink link budget For multicast data, same information can be transmitted simultaneously. –No cell edge. Spectral efficiency ~1-2 bps/Hz No uplink => can use few high powered large towers. –Radius ~30-40 km Hence cost/bit for multicast data can be significantly reduced by using specialized multicast networks. News / Live TV /Sports Traffic report / Weather Stock Ticker A surprising large amount of content can be delivered efficiently using multicast MediaFlo

55 Qualcomm May 2005 What is 4G ? Dont know ! My conjecture: –4G should cause significant reduction in cost/bit (>5x) over 3G? The wireless industry will spend > $100B going from 2G to 3G Any transition away from 3G will be expensive and should be well worth the pain. Need to separate hype from reality. Next Generation Services will involve hybrid networks –WAN/LAN/Multicast –Use the most cost effective mechanism for delivering data.

56 Qualcomm May 2005 Active Areas of Research CDMA Multi-user Detection –Advances in Silicon technology now allow us to implement interference cancellation and get closer to the theoretical limits. –Compare with orthogonal multiple access techniques such as OFDMA. MIMO for Wide Area Networks –How do we extract MIMO gains in a WAN that is characterized by correlated scattering and fairly poor C/I conditions? Smart Antennas Device innovation –Text input, low power displays, low power circuit design, battery technology, multiband radios, etc. Services –Mobile search, m-commerce, multi-player games, etc..

The Digital Home Everything On Demand Network UCI Research Symposium May 2005 Al Servati Director Marketing, Broadband Media Products

Page 58 Conexant ConfidentialUpdated 1/20/05 Broadband Digital Home Internet Video Telephony / VPN Game Worlds Music Dial-Up Satellite Cable DSL Broadband Wireless Ethernet HPNA Powerline Wireless PC Game System Internet Radio Analog/Digital Phones TV/Video Displays Terminals Media Gateway Data Gateway

Page 59 Conexant ConfidentialUpdated 1/20/05 Broadband Digital Home Technologies ADSL VDSL Cable Modem Wireless (2.5/3G) a/b/g BB/MAC RF Ethernet Bluetooth Powerline Analog Modem Video Codec MPEG-2 Codec Digital Tuner Demodulator SD MPEG-2 Codec LCD Control Audio Codec Advanced Video Codecs PC DTV DVD-R Audio STB Display Current Conexant Portfolio Capability Gap Media Applications Local Distribution DVD Navigator ADSL2/2+ Voice Codec Telephony Application VOP Network Processor Broadband Access xDSL CO Current GlobespanVirata Portfolio

Page 60 Conexant ConfidentialUpdated 1/20/05 Cable Operators Business Challenges Need to compete with Satellite, ISP, and Telco offerings Everything On Demand Video on Demand, IP-Video (HDTV/H.264) VoIP, Multimedia service, Home Security, other services ?? Need to drive open standards to lower CAPEX and OPEX A flexible network architecture, NGNA Communication technologies (Euro- / DOCSIS standards) Next Generation DOCSIS DOCSIS 3.0 Low-cost CPEs Highly Integrated SOCs (HD / H.264) Advanced content servers, standard middleware, home networking technologies

Page 61 Conexant ConfidentialUpdated 1/20/05 Current Cable Network Cable Modem CM + VoIP CM + RG Data Set Top Box Video HFC MPEG-2

Page 62 Conexant ConfidentialUpdated 1/20/05 DOCSIS Evolution: Better QoS / Higher BW TDMA PHY MAC Without QoS Applications Asymmetric Bandwidth Best Effort DOCSIS 1.0 DOCSIS 3.0 Applications Asymmetric Bandwidth Best Effort MAC Without QoS TDMA PHY DOCSIS 1.1 MAC QoS Enhancements Constant Bit Rate DOCSIS 2.0 Constant Bit Rate S-CDMA PHY Symmetric Bandwidth A-TDMA/ S-CDMA MAC Changes MAC Without QoS Applications Asymmetric Bandwidth Best Effort MAC QoS Enhancements TDMA PHY A-TDMA PHY

Page 63 Conexant ConfidentialUpdated 1/20/05 Everything On Demand Network HFC H.264 Content Thick Set-top Box Broadband Content Gateway Home Network Thin STB Cable operators and consumer electronics companies must form alliances To provide new content and services Cable operators focus on delivering applications /services Retain subscribers and increase revenue per subscriber

Page 64 Conexant ConfidentialUpdated 1/20/05 Next Generation STBs, DTVs, …. eSTB HD / H.264 Tuner TS eCM DOCSIS 3.0 Support for Video over IP via dedicated DOCSIS channels HD / H.264, up to 200 Mpbs downstream bandwidth CX2418x H.264 I/O Bus or PCICLKTS YCrCb CX2417x HD Decoder

Page 65 Conexant ConfidentialUpdated 1/20/05 Next Gen. STB with Home Networking eCM DOCSIS 3.0 eSTB HD / H.264 HDD Tuner TS RF IP-STB HD / H.264 Communication Processor HDD (NAS) Wireless VoIPWired IP

Page 66 Conexant ConfidentialUpdated 1/20/05 The Future: Multi-Pipe DOCSIS DOCSIS X.x Cable Modem DOCSIS X.x CMTS Multi-Upstreams Max Rate: 30Mbps x N 1 2 N 1 2 M Multi-Downstreams Max Rate: 40Mbps x M

Page 67 Conexant ConfidentialUpdated 1/20/05 Next Generation DOCSIS 3.0 DOCSIS VersionDOCSIS 1.0DOCSIS 1.1DOCSIS 2.0 DOCSIS 3.0 Services Broadband Internet Tiered Services VoIP Video Conferencing Commercial Services Entertainment Video XXXXXXX XXXXXXXXXX XXXXXXXXXXXX Consumer Devices Cable Modem VoIP Phone (MTA) Residential Gateway Video Phone Mobile Devices IP Set-top Box XXXXXXX XXXXXXXX XXXXXXXXXXXX Downstream Bandwidth Mbps/channel Upstream Bandwidth Mbps/channel DS Bond four 6MHz channels. With 256QAM = 160 Mbps, with 1024QAM = 200Mbps. US Bond multiple Channels

Page 68 Conexant ConfidentialUpdated 1/20/05 Hard-wired or DSP Satellite and Cable Operators will use Hard-wired solutions Performance, Cost, Integration roadmap IP/DSL-STB mostly will use integrated Hard-wired solutions Designed primarily for satellite and cable operators Large STB IC vendors will drive the cost and functionality of HD/H.264 STB SoCs Responding to satellite and cable STB needs Broad portfolio of complementary products and IP

Rene L. Cruz UCSD Networking Joseph A. Bannister ISI and USC Networking Daniel J. Blumenthal UCSB Optical Networking Pamela Cosman UCSD Speech, Image, Audio and Video Coding Babak Daneshrad UCLA MIMO Wireless Urbashi Mitra USC Wireless Jeyhan Karaoguz Broadcom Wireless Avneesh Agrawal Qualcomm Cellular Wireless Al Servati Conexant Digital Home