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From Marconi to Wireless Internet: The Wireless (R)evolution Prof. Vijay K. Bhargava Professor and Head, Dept. of Electrical and Computer Engineering The.

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Presentation on theme: "From Marconi to Wireless Internet: The Wireless (R)evolution Prof. Vijay K. Bhargava Professor and Head, Dept. of Electrical and Computer Engineering The."— Presentation transcript:

1 From Marconi to Wireless Internet: The Wireless (R)evolution Prof. Vijay K. Bhargava Professor and Head, Dept. of Electrical and Computer Engineering The University of British Columbia Vancouver, Canada Email: Website:

2 2 Presentation Outline 1. Historical Overview 2. The Three Generations 3. Beyond 3G/Wireless Internet 4. Enabling Techniques (Innovations from IT Society) 5. Malaise Afflicting the Wireless Industry 6. Possible Recovery Scenario 7. Conclusions

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4 4 Maxwell Hertz Popov Fessenden

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7 7 Signal Hill, December 12, 2001

8 8 The Three Generations and Beyond (Overview) First Generation : Analog Cellular (Mainly Speech) Second Generation : Digital Cellular (Digital Speech and messaging) 2.5G, 2.75G, … Third Generation : IMT2000 (Integrated Audio and Video)

9 9 Beyond 3G The true Wireless Internet Internet connectivity anytime anywhere Wireless and mobile extensions to the Internet Wireless – Wireline BB Transparency

10 10 Claude Elwood Shannon Father of Information Theory Electrical engineer, mathematician, and native son of Gaylord. His creation of information theory, the mathematical theory of communication, in the 1940s and 1950s inspired the revolutionary advances in digital communications and information storage that have shaped the modern world. This statue was donated by the Information Theory Society of the Institute of Electrical and Electronics Engineers, whose members follow gratefully in his footsteps. Dedicated October 6, 2000 Eugene Daub, Sculptor

11 11 Enabling Techniques (Innovations from IT Society) Reed Solomon Codes Viterbi Algorithm Public Key Crytosystem Compression Algorithm, Huffman, Lempel-Ziv, Algebraic Coding Modem Design with Coded Modulation, Ungerböeck Turbo Decoding approaches Shannons capacity limit by less than 0.5dB Theory of CDMA and Multiuser Transmission Space-Time Coding for Mobiles

12 12 Cryptography Secret Key System Public Key System

13 13 Digital Signature

14 14 Source Coding for Voice and Video Variants of Predictive Coding For voice CELP, VCELP, RPE-LTP and other Variants H.261 and H.263 Standards support low bit rate (30-64 kbps) Video for mobile communication MPEG-4 (with Reed-Solomon Codes)

15 15 Turbo Codes Originally Turbo code encoder was built using a parallel concatenation of two (or more) relatively simple recursive systematic convolutional (RSC) codes with large interleaving Although the component codes are weak, the output turbo codeword is very powerful due to the Interleaver gain which produces a random-like codeword dkdk RSC1 RSC2 Interleaver dkdk d 1,k d 2,k Turbo Code Encoder

16 16 After m iterations Decoder 1 Decoder 2 rkrk r 1,k r 2,k Turbo code Decoder d Turbo Codes (Iterative Decoding) Soft Input/Soft Output MAP Decoder Use extrinsic information produced from past decoder as á priori information Gradually improvement of knowledge on transmitted information through iterations

17 17 Turbo Codes Turbo codes will be used in high data rate services in the next generation CDMA systems above 32 kbps There are already existing standards for ½ and 1/3 coding rate turbo code for 3GPP systems The same iterative decoding principle can be applied in various different areas Turbo equalization Turbo multiuser detection (for coded CDMA signals) Turbo decoding with estimation of parameters of an unknown time-varying channel

18 18 Multiuser Detection (MUD) Signals from all users are considered useful instead of only interference to each other MUD provides important performance gains over the conventional single-user receiver Performance of single-user conventional receivers are limited in fading channel due to the near-far effect which necessitates use of strict power control In certain cases multiuser receivers can even benefit from the diversity in powers of the received users and have better performances than in the case of equal received powers of users

19 19 Multiuser Detection (MUD) In the single user approach, each detector focuses on extracting the data of a single user Other users are considered as interference Simple h(t) 1 st Rake Receiver K th Rake Receiver Rx Multiuser Detector b1b1 bKbK oscillator In the multi-user detection approach, the common detector uses available information from all users to detect each user Complex oscillator Rx h(t) 1 st Rake Receiver K th Rake Receiver Detector b1b1 bKbK

20 20 Multiuser Detection (MUD) Benefits of using multiuser detection More efficient spectrum utilization (in some situations we can expect ten fold increase in spectrum efficiency) Reduced precision requirement for power control More efficient power utilization Main difficulties in implementing multiuser detection Existence of the other-cell multiple-access interference (MAI) Difficulty in implementing multiuser detection on the downlink (cost, size, weight are of much larger concern for mobile terminals)

21 21 Multiuser Detection (MUD) Some of the MUD algorithms are Maximum Likelihood (Optimal) Decoding (complexity increases exponentially with the number of users) Linear detectors (similar to the linear equalization techniques) decor relating detector MMSE detector MMSE detector can be implemented as an adaptive filter to reduce complexity Blind adaptive implementation of the MMSE detector Decision Feedback Detectors where past decisions are used to improve the current ones Conventional Decision Feedback or Successive Interference Cancellation Parallel Interference Cancellation Optimum Decision Feedback Receiver (has the spectral efficiency equal to the optimum detector)

22 22 Multiuser Detection (MUD) Implementation examples of multistage parallel interference cancellation multiuser detection: DSP implementation [Buehrer, Woerner, 1999] VLSI implementation [Aazhang et al., 2000] The parallel interference cancellation is prefered due to its performance complexity tradeoff However, MUD research is still in a phase that would not justify to make it a mandatory feature for 3G WCDMA standards Most probably, its practical implementation and standardization is going to be defered for 4G systems

23 23 Space-Time Codes Capacity of a multi-antenna systems far exceeds that of single-antenna system Multiple transmit/receive antennas provide diversity in the space domain (space diversity) Channel coding designed for wireless communication systems with multiple transmit/receive antennas provide both space and time diversity Space-time codes Two categories of space-time coding 1) space-time trellis codes 2) space-time block codes Decoding of space-time codes requires channel estimation

24 24 Space-Time Codes Information source Space-time encoder Receiver s(k ) c 1 (k) c N (k) r 1 (k) r N (k) s(k) Space-time coding system 0 1 2 3 4 5 6 7 00,01,02,03,04,05,06,07 50,51,52,53,54,55,56,57 20,21,22,23,24,25,26,27 70,71,72,73,74,75,76,77 40,41,42,43,44,45,46,47 10,11,12,13,14,15,16,17 60,61,62,63,64,65,66,67 30,31,32,33,34,35,36,37 Input: 0 1 5 7 6 4 Tx 1: 0 0 5 1 3 6 Tx 2: 0 1 5 7 6 4 0 1 2 3 4 5 6 7 Space-time trellis codes (8-PSK) with two transmit antennas Space-time block codes with two transmit antennas (Alamoutis scheme) Constellation Mapper s(k ) [c 1 c 2 ]

25 25 Space-Time Codes Bandwidth and power efficient – a codeword is transmitted simultaneously from different antennas with the same total transmit power Channel information is not necessary at the transmitter Differential scheme is available when channel information is not known at the receiver Can be concatenated with other codes such as Reed- Solomon, TCM, turbo code Can be applied in broadband channel – CDMA, OFDM Adopted in standards – IS-136, W-CDMA, CDMA2000 Tested in WLAN 802.11a. Increase in link layer throughput and improving TCP performance

26 26 The Malaise Afflicting The Communications Industry * A convergence of five key factors 1. Greed 2. Corporate Crime 3. Misguided Regulations 4. Too Much Debt 5. A Broken Business Model Why did we, the engineers, allow business manipulators and bureaucrats to drive the show ? *Peter A. Bernstein, IEEE Spectrum, January 2003

27 27 Possible Recovery Scenario Nothing lasts forever This too shall pass Survival of the fattest! Broadband: Alive and Well Mobile, and Loving it If Each is Good, Both are Better If You Build it, Killer Apps will Come *Steven M.Cherry, IEEE Spectrum, January 2003

28 28 Conclusions We have presented a historical overview of Wireless Communication Innovations from IT Society have been discussed Reliable high-speed mobile Internet Access will lead to innovative product and services It is dangerous to put limits on Wireless Communications

29 29 ISBN: 1-4020-7251-1 © 2003

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