Professor Andrea Goldsmith EE 359: Wireless Communications Professor Andrea Goldsmith

Outline Course Basics Course Syllabus The Wireless Vision Technical Challenges Current Wireless Systems Spectrum Regulation and Standards Emerging Wireless Systems

Course Information* People Instructor: Andrea Goldsmith, andrea@ee, Packard 371, OHs: MW after class and by appt. TAs: Mainak Chowdhury, mainakch@stanford.edu, and Milind Rao, milind@stanford.edu, Discussion Tues 4-5 pm (televised) or 5-6pm OHs: Tues after discussion (Mainak), Wed 5-6pm, Thur 9:30-10:30 (Milind), location TBA. Email OHs (ideally via Piazza): Thursday 2-4 pm. Piazza website: https://piazza.com/stanford/fall2014/ee359/home Class Administrator: Pat Oshiro, poshiro@stanford, Packard 365, 3-2681. Homework dropoff: Th by 5 pm. *See web or handout for more details

Course Information Nuts and Bolts Prerequisites: EE279 or equivalent (Digital Communications) Required Textbook: Wireless Communications (by me), CUP Available at bookstore (out of stock) or Amazon Extra credit for finding typos/mistakes/suggestions (2nd ed. soon!) Supplemental texts on 1 day reserve at Engineering Library. Class Homepage: www.stanford.edu/class/ee359 All handouts, announcements, homeworks, etc. posted to website “Lectures” link continuously updates topics, handouts, and reading Class Mailing List: ee359-aut1415-students@lists (automatic for on-campus registered students). Guest list ee359-aut1415-guest@lists for SCPD and auditors: send Mainak/Milind email to sign up. Sending mail to ee359-aut1415-staff@lists reaches me and TAs.

Course Information Policies Grading: Two Options No Project (3 units): HW – 30%, 2 Exams – 30%, 40% Project (4 units): HWs- 20%, Exams - 25%, 30%, Project - 25% HWs: assigned Thurs, due following Thurs 5pm (starts 9/25) Homeworks lose 33% credit per day late, lowest HW dropped Up to 3 students can collaborate and turn in one HW writeup Collaboration means all collaborators work out all problems together Unpermitted collaboration or aid (e.g. solns for the book or from prior years) is an honor code violation and will be dealt with strictly. Exams: Midterm week of 11/3. (It will be scheduled outside class time; the duration is 2 hours.) Final on 12/8 from 8:30-11:30 am. Exams must be taken at scheduled time, unless a course conflicts

Course Information Projects The term project (for students electing to do a project) is a research project related to any topic in wireless Two people may collaborate if you convince me the sum of the parts is greater than each individually A 1 page proposal is due 10/24 at 5 pm. 5-10 hours of work typical for proposal Project website must be created and proposal posted there The project is due by 5 pm on 12/6 (on website) 20-40 hours of work after proposal is typical for a project Suggested topics in project handout Anything related to wireless or application of wireless techniques ok.

Course Syllabus Overview of Wireless Communications Path Loss, Shadowing, and Fading Models Capacity of Wireless Channels Digital Modulation and its Performance Adaptive Modulation Diversity MIMO Systems Multicarrier Modulation Spread Spectrum Intro to Wireless Networks (EE360)

No lectures Wed 9/24, Mon 10/20, Wed 11/12 Date Topic Required Reading   Introduction 1 9/22 Overview of Wireless Communications Chapter 1 and Appendix D Wireless Channel Models 2*-3 9/26*,9/29 Path Loss and Shadowing Models Lec 2: Section 2.1 to 2.6 Lec 3: Section 2.7 to 2.10 4-5 10/1,10/6 Statistical Fading Models, Narrowband Fading Lec 4: Section 3.1 to 3.2.1 Lec 5: Section 3.1 to 3.2 6 10/8 Wideband Fading Models Section 3.2 to 3.3 Impact of Fading and ISI on Wireless Performance 7 10/13 Capacity of Wireless Channels Chapter 4 8,9*,10 10/15,10/22, 10/24* Digital Modulation and its Performance Lec 8: Chapter 5 Lec 9-10: Chapter 6 Flat-Fading Countermeasures 11 10/27 Diversity Chapter 7 12 10/29 Adaptive Modulation Section 9.1 to 9.2 MT Week of 11/3 Midterm (outside class time) Chapters 2 to 7 13 11/3 Practical Considerations in Adaptive Modulation Section 9.3 14,15,16* 11/5,11/10, 11/17 Multiple Input/Output Systems (MIMO) Chapter 10 & Appendix C ISI Countermeasures 17 11/19 Equalization, Multicarrier Systems Chapter 12.1-12.3 18 11/21* Multicarrier Modulation and OFDM Chapter 12.4-12.6 Multiuser Systems 19 12/1 Spread Spectrum and CDMA Chapter 13 20 12/3 Overview of multiuser systems & networks Course summary Sections 14.1 to 14.4, 15.1 to 15.2, 16.1 to 16.3 Final 12/8 8:30-11:30 am No lectures Wed 9/24, Mon 10/20, Wed 11/12

Class Rescheduling 9/24 (this Wed) moved to 9/26 (this Fri), 9:30-10:45, 102 Thornton (w/donuts) 10/20 (Mon) rescheduled to Fri 10/24, tentatively 9:30-10:45am, 102 Thornton (w/donuts) 11/12 (Wed) rescheduled to Fri 11/21, tentatively 9:30-10:45am, 102 Thornton (w/donuts) May have optional advanced topics lecture the last week of classes (evening or lunch, w/ pizza)

Wireless History Ancient Systems: Smoke Signals, Carrier Pigeons, … Radio invented in the 1880s by Marconi Many sophisticated military radio systems were developed during and after WW2 Cellular has enjoyed exponential growth since 1988, with almost 5 billion users worldwide today Ignited the wireless revolution Voice, data, and multimedia ubiquitous Use in third world countries growing rapidly Wifi also enjoying tremendous success and growth Wide area networks (e.g. Wimax) and short-range systems other than Bluetooth (e.g. UWB) less successful

Future Wireless Networks Ubiquitous Communication Among People and Devices Next-generation Cellular Wireless Internet Access Wireless Multimedia Sensor Networks Smart Homes/Spaces Automated Highways In-Body Networks All this and more …

Challenges Network Challenges Device Challenges Scarce/bifurcated spectrum Demanding/diverse applications Heterogeneous networks High-performance requirements Reliability and coverage Device Challenges Size, Power, Cost Multiple Antennas in Silicon Multiradio Integration Coexistance Cellular Apps Processor BT Media GPS WLAN Wimax DVB-H FM/XM

Software-Defined (SD) Radio: Is this the solution to the device challenges? BT A/D FM/XM Cellular GPS A/D DVB-H DSP Apps Processor A/D WLAN Media Processor Wimax A/D Wideband antennas and A/Ds span BW of desired signals DSP programmed to process desired signal: no specialized HW Today, this is not cost, size, or power efficient Compressed sensing may be a solution for sparse signals

Current Wireless Systems Cellular Systems Wireless LANs WiGig and mmWave Communications Cognitive Radios Satellite Systems Zigbee radios

Driving Constraint in Wireless System Design: Scarce Spectrum $$$ Licensed Bands Scarce & Expensive

Spectral Reuse Due to its scarcity, spectrum is reused BS In licensed bands and unlicensed bands Wifi, BT, UWB,… Cellular Reuse introduces interference

Cellular Systems: Reuse channels to maximize capacity Geographic region divided into cells Frequency/timeslots/codes reused at spatially-separated locations. Co-channel interference between same color cells (reuse 1 common now). Base stations/MTSOs coordinate handoff and control functions Shrinking cell size increases capacity, as well as networking burden BASE STATION MTSO

Future Cellular Phones Burden for this performance is on the backbone network Everything wireless in one device BS Phone System San Francisco Paris Nth-Gen Cellular Internet LTE backbone is the Internet Much better performance and reliability than today - Gbps rates, low latency, 99% coverage indoors and out

4G/LTE Cellular Much higher data rates than 3G (50-100 Mbps) 3G systems has 384 Kbps peak rates Greater spectral efficiency (bits/s/Hz) More bandwidth, adaptive OFDM-MIMO, reduced interference Flexible use of up to 100 MHz of spectrum 20 MHz spectrum allocation common Low packet latency (<5ms). Reduced cost-per-bit All IP network

Careful what you wish for… Exponential Mobile Data Growth Leading to massive spectrum deficit Source: FCC Source: Unstrung Pyramid Research 2010 Growth in mobile data, massive spectrum deficit and stagnant revenues require technical and political breakthroughs for ongoing success of cellular

Number of Connected Objects Expected to Reach 50bn by 2020 On the Horizon: “The Internet of Things” Number of Connected Objects Expected to Reach 50bn by 2020

Are we at the Shannon limit of the Physical Layer? We don’t know the Shannon capacity of most wireless channels Time-varying channels with no/imperfect CSI Channels and networks with feedback Channels with delay/energy/HW constraints. Channels with interference or relays Cellular systems Ad-hoc/peer-to-peer networks Multicast/common information networks

Rethinking “Cells” in Cellular How should cellular systems be designed? Coop MIMO Small Cell Relay Will gains in practice be big or incremental; in capacity or coverage? DAS Traditional cellular design “interference-limited” MIMO/multiuser detection can remove interference Cooperating BSs form a MIMO array: what is a cell? Relays change cell shape and boundaries Distributed antennas move BS towards cell boundary Small cells create a cell within a cell Mobile cooperation via relays, virtual MIMO, network coding.

Are small cells the solution to increase cellular system capacity? Yes, with reuse one and adaptive techniques (Alouini/Goldsmith 1999) A=.25D2p Area Spectral Efficiency S/I increases with reuse distance (increases link capacity). Tradeoff between reuse distance and link spectral efficiency (bps/Hz). Area Spectral Efficiency: Ae=SRi/(.25D2p) bps/Hz/Km2.

10x CAPACITY Improvement The Future Cellular Network: Hierarchical Architecture Today’s architecture 3M Macrocells serving 5 billion users Anticipated 1M small cells per year 10x Lower COST/Mbps (?) 10x CAPACITY Improvement Near 100% COVERAGE MACRO: solving initial coverage issue, existing network PICO: solving street, enterprise & home coverage/capacity issue Macrocell Picocell Femtocell Future systems require Self-Organization (SON) and WiFi Offload

SON Premise and Architecture Mobile Gateway Or Cloud Node Installation Initial Measurements Self Optimization Self Healing Self Configuration Measurement SON Server SoN Server IP Network X2 X2 SW Agent X2 X2 SON is part of 3GPP/LTE standard Small cells not widely deployed today Small cell BS Macrocell BS

Green” Cellular Networks Pico/Femto How should cellular systems be redesigned for minimum energy? Coop MIMO Relay DAS Research indicates that significant savings is possible Minimize energy at both the mobile and base station via New Infrastuctures: cell size, BS placement, DAS, Picos, relays New Protocols: Cell Zooming, Coop MIMO, RRM, Scheduling, Sleeping, Relaying Low-Power (Green) Radios: Radio Architectures, Modulation, coding, MIMO

Wifi Networks Multimedia Everywhere, Without Wires Wifi is today’s small cell 802.11ac Streaming video Gbps data rates High reliability Coverage inside and out Wireless HDTV and Gaming

Wireless Local Area Networks (WLANs) 1011 01011011 0101 Internet Access Point WLANs connect “local” computers (100m range) Breaks data into packets Channel access shared (random access + backoff) Backbone Internet provides best-effort service Poor performance in some apps (e.g. video)

Wireless LAN Standards 802.11b (Old – 1990s) Standard for 2.4GHz ISM band (80 MHz) Direct sequence spread spectrum (DSSS) Speeds of 11 Mbps, approx. 500 ft range 802.11a/g (Middle Age– mid-late 1990s) Standard for 5GHz band (300 MHz)/also 2.4GHz OFDM in 20 MHz with adaptive rate/codes Speeds of 54 Mbps, approx. 100-200 ft range 802.11n/ac (Current) Standard in 2.4 GHz and 5 GHz band Adaptive OFDM /MIMO in 20/40/80/160 MHz Antennas: 2-4, up to 8 Speeds up to 600Mbps/10 Gbps, approx. 200 ft range Other advances in packetization, antenna use, multiuser MIMO Many WLAN cards have (a/b/g/n)

Why does WiFi performance suck? Carrier Sense Multiple Access: if another WiFi signal detected, random backoff Collision Detection: if collision detected, resend The WiFi standard lacks good mechanisms to mitigate interference, especially in dense AP deployments Multiple access protocol (CSMA/CD) from 1970s Static channel assignment, power levels, and carrier sensing thresholds In such deployments WiFi systems exhibit poor spectrum reuse and significant contention among APs and clients Result is low throughput and a poor user experience

Why not use SoN for WiFi? - Channel Selection - Power Control - etc. SoN Controller SoN-for-WiFi: dynamic self-organization network software to manage of WiFi APs. Allows for capacity/coverage/interference mitigation tradeoffs. Also provides network analytics and planning.

In fact, why not use SoN for all wireless networks? TV White Space & Cognitive Radio Vehicle networks mmWave networks

Software-Defined Wireless Network (SDWN) Architecture Video App layer Security Vehicular Networks M2M Health Freq. Allocation Power Control Self Healing ICIC QoS Opt. CS Threshold SW layer UNIFIED CONTROL PLANE HW Layer WiFi Cellular mmWave Cognitive Radio

WiGig and mmWave WiGig mmWave Standard operating in 60 GHz band Data rates of 7-25 Gbps Bandwidth of around 10 GHz (unregulated) Range of around 10m (can be extended) Uses/extends 802.11 MAC Layer Applications include PC peripherals and displays for HDTVs, monitors & projectors mmWave Couples 60GHz with massive MIMO and better MAC Promises long-range communication w/Gbps data rates Hardware, propagation and system design challenges Much research on this topic today

Satellite Systems Cover very large areas Different orbit heights GEOs (39000 Km) versus LEOs (2000 Km) Optimized for one-way transmission Radio (XM, Sirius) and movie (SatTV, DVB/S) broadcasts Most two-way systems went bankrupt Global Positioning System (GPS) ubiquitous Satellite signals used to pinpoint location Popular in cell phones, PDAs, and navigation devices

IEEE 802.15.4/ZigBee Radios Low-Rate WPAN Data rates of 20, 40, 250 Kbps Support for large mesh networking or star clusters Support for low latency devices CSMA-CA channel access Very low power consumption Frequency of operation in ISM bands Focus is primarily on low power sensor networks

Spectrum Regulation Spectrum a scarce public resource, hence allocated Spectral allocation in US controlled by FCC (commercial) or OSM (defense) FCC auctions spectral blocks for set applications. Some spectrum set aside for universal use Worldwide spectrum controlled by ITU-R Regulation is a necessary evil. Innovations in regulation being considered worldwide in multiple cognitive radio paradigms

Standards Interacting systems require standardization Companies want their systems adopted as standard Alternatively try for de-facto standards Standards determined by TIA/CTIA in US IEEE standards often adopted Process fraught with inefficiencies and conflicts Worldwide standards determined by ITU-T In Europe, ETSI is equivalent of IEEE Standards for current systems are summarized in Appendix D.

Emerging Systems* Cognitive radio networks Ad hoc/mesh wireless networks Sensor networks Distributed control networks The smart grid Biomedical networks *Can have a bonus lecture on this topic late in the quarter if there is interest

Cognitive Radios CRRx NCRRx NCRTx CRTx NCR IP CR MIMO Cognitive Underlay Cognitive Overlay Cognitive radios support new users in existing crowded spectrum without degrading licensed users Utilize advanced communication and DSP techniques Coupled with novel spectrum allocation policies Multiple paradigms (MIMO) Underlay (interference below a threshold) Interweave finds/uses unused time/freq/space slots Overlay (overhears/relays primary message while cancelling interference it causes to cognitive receiver)

Compressed Sensing in Communications Compressed sensing ideas have found widespread application in signal processing and other areas Basic premise: exploit sparsity to approximate high-dimensional system/signal in a few dimensions. We ask: how can sparsity be exploited to reduce the complexity of communication system design Sparse signals: e.g. white-space detection Sparse samples: e.g. sub-Nyquist sampling Sparse users: e.g. reduced-dimension multiuser detection Sparse state space: e.g reduced-dimension network control

Ad-Hoc Networks Peer-to-peer communications Routing can be multihop. No backbone infrastructure or centralized control Routing can be multihop. Topology is dynamic. Fully connected with different link SINRs Open questions Fundamental capacity region Resource allocation (power, rate, spectrum, etc.) Routing -No backbone: nodes must self-configure into a network. -In principle all nodes can communicate with all other nodes, but multihop routing can reduce the interference associated with direct transmission. -Topology dynamic since nodes move around and link characteristics change. -Applications: appliances and entertainment units in the home, community networks that bypass the Internet. Military networks for robust flexible easily-deployed network (every soldier is a node).

Wireless Sensor Networks Data Collection and Distributed Control Smart homes/buildings Smart structures Search and rescue Homeland security Event detection Battlefield surveillance Energy (transmit and processing) is the driving constraint Data flows to centralized location (joint compression) Low per-node rates but tens to thousands of nodes Intelligence is in the network rather than in the devices

Distributed Control over Wireless Automated Vehicles - Cars - Airplanes/UAVs - Insect flyers Interdisciplinary design approach Control requires fast, accurate, and reliable feedback. Wireless networks introduce delay and loss Need reliable networks and robust controllers Mostly open problems : Many design challenges

The Smart Grid: Fusion of Sensing, Control, Communications Open problems: - Optimize sensor placement in the grid - New designs for energy routing and distribution - Develop control strategies to robustify the grid - Look at electric cars for storage and path planning carbonmetrics.eu

Applications in Health, Biomedicine and Neuroscience Neuro/Bioscience EKG signal reception/modeling Brain information theory Nerve network (re)configuration Implants to monitor/generate signals In-brain sensor networks SP/Comm applied to bioscience Body-Area Networks Doctor-on-a-chip Wireless Network Recovery from Nerve Damage

Main Points The wireless vision encompasses many exciting systems and applications Technical challenges transcend across all layers of the system design. Existing and emerging systems provide excellent quality for certain applications but poor interoperability. Innovative wireless design needed for mmWave systems, massive MIMO, SDWN, and Internet of Things connectivity Standards and spectral allocation heavily impact the evolution of wireless technology