New and Emerging Wireless Technologies Beyond 3G

1. New and Emerging Wireless Technologies Beyond 3G Sam Samuel Lucent Technologies Swindon UK

2. TOC • Economics and Vision • Background to the Problem • Future and Emerging Technologies • MIMO • OFDM • Beam forming – IA and Antenna Array • Interference cancellation • Network Time Scheduling • IEEE Approaches • Summary

3. $10 $1 $0.1 1 10 100 1000 10000 Wireless Experience Curve: 1985 to 1996 CEO’s Note: DRAM and airtime both reduced ~10x from 1985-1995 Real Estate Agents 1985 Replace Calling Cards 1986 1987 Cost per Minute 1988 1989 1990 1991 1992 Intercom 1993 Elasticity ~ 3 1994 1995 1996 Def of Elasticity: %change in X/% change in y Source: G.Blonder, AT&T Labs, 1977 Cumulative Minutes (B) Note: Cost excludes marketing and sales expense and are in 1996 dollars • Next generation systems must be spectrally efficient across the network (bandwidth where needed). • Equipment providers will provide the “compilers” for application creation. • Partnering will be the norm.

4. Economics and Visions

5. Ambient Control Space 2.5 G 3G Corporate 4G WLAN Fixed Information Anywhere Vision:Example project – EU 6FP Ambient Networks • Ambient Networks: • Common Control Services • Dynamic Network Composition Services Services Ambient Connectivity Community Personal Home Vehicular PAN CAN VAN HAN

6. Background to the problem Motivation

7. Preceived delay spread The wireless channel • Scattering causes local signal fading • Delay spread dependent on environment (small for indoor, large for macrocell)

8. Pr Pr f t delay spread Channel Normal-modes • Classic static multipath channel is linear. • Normal modes are simple sinusoids. OFDM then is optimal in this sense. • Information is broken into small frequency bands with flat fading. Great for MIMO type applications. • Active research areas within Bell Labs: • OFDM, chirped pulses, MC-CDMA, OFDM-CDMA for legacy and practical implementation

9. ideal multiple access noise floor bit rate bit rate goes to zero at infinite bandwidth and fixed power bandwidth Increasing the Data Rate in CDMA Original signal Multipath channel Rake Receiver Rx signal time diversity UMTS

10. 1600 1200 Packet Size 800 400 0 5 10 15 20 25 Latency sec 5 10 20 25 Live Wireless Transaction Measurements • Traffic characteristics: • Initial download of HTTP skeleton resulted in GET of large objects. Many 1500 packets retrieved. • Period 9 - 20 consumed by DNS accesses to resolve www.xxx.com addresses to IP addresses. • End of transaction resulted in many small object retrievals. Large uplink payloads for smaller downlink payloads. • Latency chart illustrates queuing within system as generated load piles up in uplink and downlink directions. • This traffic profile is typical of Web accesses. • Netscape Browser access to www.adobe.com: • blue dots are downlink packets, red dots are uplink packets. • average downlink Kbps to 1 second peak = 4.3:1 • average uplink Kbps to 1 second peak = 4.7:1 • MRU was 1500 bytes • TCP Window Size was 8,192 bytes We cannot ignore delay – TTI Issues We cannot ignore uplink – Symmetry Issues

11. General Throughput Equation • To optimize data performance we should combine rate and power control • OFDM is convenient for water filling • Keep number of sub-carriers manageable for uplink channel information

12. Future and Emerging Technologies

13. MIMO

14. Space: The Last Frontier • Convergence of ubiquitous wireless access and broadband internet creates insatiable demand for high bit rate wireless access • System capacity is interference limited - cannot be increased by increasing transmitted power • The spectrum has become a scarce and very expensive resource • For Cellular systems reducing cell size is not viable • Increasing spectral efficiency with multiple transmit and multiple receive antennas opens a new dimension, space, offering exceedingly high bit rates without increasing transmitted power bandwidth allocation

15. C. Shannon • Bell Labs Technical Journal, 1950 Bandwidth Efficiency Limits

16. ... Rx M Efficiency Limits with a Single Array • Adding a single array does provide diversity against fading, but it does not change the (slow growth) logarithmic nature of the bandwidth efficiency limit

17. s2 ... ... sM Rx M number of antennas in the smaller of the transmit and receive arrays Lifting the Limits with Dual Arrays s1

18. Predicted outage capacities 150 100 50 SPECTRAL EFFICIENCY vs. NUMBER ANTENNAS AT 1% OUTAGE 24dB 12dB 18 dB SPECTRAL EFFICIENCY (bps/Hz) 6 dB 1N Optimum Combining at 24 dB 0 dB 8 0 10 20 30 40 50 60 NUMBER OF UNCORRELATED ANTENNAS (M=N)

19. Receiver Chip (2.1mmx1.9mm) MIMO Capacity Increases C/W=log2(det(I+rHHH)) ~N*log2(1+SNR) Capacity grows as the number of antennas! • Increases the spectral efficiency • Compact antenna arrays • Low-cost receivers

20. Tx Rx User data is encoded, modulated and transmitted simultaneously over multiple antennas  High Data Rates High levels of interference at the mobile requires sophisticated yet efficient signal processing. MIMO MIMO: Increase data rates by exploiting multiple antennas at both Tx and Rx. Channel

21. The Wireless Channel in MIMO Processing • Multiple antenna techniques rely on the • characteristics of the spatial signature: • Diversity techniques rely on the assumption thatdistinct spatial signatures correspond to different pairs of transmit-receive antennas. • Intelligent antenna techniques rely on the efficient adaptation of the array pattern according to the spatial distribution of the desirable user and interferers.

22. Open-Loop Transmit Diversity • Time-Switched Transmit Diversity (TSTD) x1 Data Mobile time x1 , x2 x2 time • Space-Time Block Code Transmit Diversity (STC) x1 x2 Space-Time Block Code Data Mobile time x1 , x2 –x2* x1* time

23. MIMO Research Trends Advanced MIMO receivers can be costly on the downlink due to limitations in mobile form-factor and complexity. • High-performance, low-complexity detection algorithms for MIMO. Algorithms based on joint-detection or serial/parallel interference cancellation techniques following space-time equalization. • High-performance, low-complexity receiver architectures for MIMO based on multiple iterations between a low-complexity detector and a error-correcting decoder. • Transmitter encoding for High-Order Modulations in MIMO, allowing reduced complexity at the receiver. • Dynamic packet scheduling across multiple antennas.

24. Laptop Propagation Modeling & Measurements Indoor propagation measurements consistently show high BLAST gains. Recent outdoor measurements demonstrate similar results. Mobile Measurements theory omni ant. BLAST/1x1 capacity 120 ft antenna in laptop time (sec) • narrowband channel capacity in mobile suburban 80% of theory • narrowband channel capacity of laptop in van is 65% of theory • Capacity improvements are real

25. OFDM

26. 1/NT sin(wt) IFFT N Block cos(wt) f Orthogonal Frequency Division Duplexing • Breaks high-speed data into low-rate parallel streams • Longer symbol period reduces ISI & ICI for spread OFDM • fn=fc+nDf, where for orthogonality DfTs=1 • Simple DFT implementation

27. Beam Forming – Intelligent Antenna

28. Performance Enhancements • Transmit Diversity achieves: • Improved call quality on the downlink by combating multipath fading. • Reduced BTS transmit power, thereby reducing downlink inter-cell interference. • Intelligent Antennas achieve: • Higher antenna gain - by maximising received energy or transmitting more effective power. • Reduction of Interference by maximising Signal – to - Interference Ratio

29. Omnidirectional Cell Site Three Sector Cell Site Intelligent Antenna Cell Site Intelligent Antennas • An antenna-array transceiver system. • Combined with a base station architecture and signal processing techniques designed to dynamically select or form the “optimum” beam pattern per user.

30. Conventional Receiver Adaptive Antenna Mobile 1: Direct Ray Mobile 1: Direct Ray Mobile 1 Mobile 1: Reflected Ray Mobile 1: Reflected Ray Mobile 2 Interferer Interferer Mobile 1: Reflected Ray Mobile 1: Reflected Ray Mobile 2: Direct Ray Mobile 2: Direct Ray Adaptively “weight” and combine multiple antenna signals to optimise performance. Antenna spatial gain patterns are fixed. Adaptive Antenna Principle

31. Closed-Loop Transmit Diversity w1 Mobile Data w2 Feedback on Uplink Closed-loop TxAA Quantised Weights • Weights are computed by the mobile as a function of the downlink channel estimates to maximise the received signal energy. • Weights are then quantised in amplitude/phase and sent back on the uplink control channel.

32. Multi-Antenna Solutions Signal fades in time and space. Include both space and time diversity Pathloss (dB) dB antenna separation time

33. Base and terminal Smart Antenna Prototypes

34. Basestation Antenna Configurations • two beam lobes • polarization and spacial diversity configurations • 2-6 dB improvement • high gain for low-speed users • 4-fold diversity on the uplink polarization beams • 16 element tower top electronics • 9o beamwidth with -35 dB side lobes • Space-division multiple access

35. H E Polarization Antennas at Mobile Three omni-antennas co-located at feed point Key feature to obtain MIMO gains: • achieving the separation between Antennas on the end device Ceramic Antenna, Tripole Antenna Without scattering polarization perpendicular to k-vector Tripole antenna

36. Interference Cancellation

37. Serving NodeB (1-Antenna Tx) Interfering NodeB (1-Antenna Tx) Inter-cell Interference K2Codes K1Codes Multi-Antenna UE Interference Mitigation (1):Cellular Downlink Intra- and inter-cell interference mitigation algorithms at the mobile. • Iterative detectors based on space-time filtering. Filter weights trained via transmitted pilots of the desired signal using Least squares and semi-blind (e.g. constant modulus) optimisation criteria.

38. Interference Mitigation (2):WLAN Inter-system Interference due to co-existing technologies in unlicensed bands. • Space-time filtering at the receiver in conjunction with enhanced MAC algorithms to cope with inter-system interference.

39. Interference Mitigation Advances K=4, M=2, Nt=20, Nd=80, SIR=0dB, 500 trials 0 10 Known parameters LR with outliers selection LS Conventional solutions LSB SB (delta=0.1) Proposed semi-blind solution -1 10 MSE Finite data ML benchmark Optimal solution: Full a priori info -2 10 10 11 12 13 14 15 16 17 18 19 20 SNR, dB Techniques advancing to point where they approaching theoretical limits

40. Network Time Scheduling

41. link loss Short Delay vs. Long Delay Services Tx power link loss Delay constraints force user to power control through fades delay jitter Tx power Schedule transmission around fades. Transmit at full power maximum rate. Higher latency.

42. high latency low latency Data scheduling Partition low and high latency services in power

43. Coordinated Cell Scheduling • High priority packets are sent with neighbors quiet. • Coordination is local between nearest neighbour • MESH Network • 802.16a • Other relay techniques • being proposed in 4G • research • Considered a key • Future Emerging • Technology by EU possible 3X improvement

44. IEEE Approaches

45. Impact of 802.20, 802.16 , 802.11 IEEE approach is largely OFDM based • Even IEEE 802.15.3 is OFDM based Actively adding mobility to the standards: • 802.16e and 802.20 • 802.11 considering management plane that would allow mobility Differences: • 802.20 – wide scale mobility (vehicular) • frequency band 500Mhz to 3.5GHz • 802.16e – pedestrian • Based on 802.16a frequency band 2GHz to 6 GHz Appears there is an overlap between two

46. Efficiency Targets for 802.20 Source IEEE 802.20

47. A A Second-Generation Wireless LANs • InterNet/IntraNet • Ethernet-Compatible Speeds • Multiple RF Bands to operate Third-Generation Wireless Communications • TDMA • EDGE • Wideband CDMA 802.11: Indoor Wireless LAN Migration IEEE 802.11 Fourth-Generation of Wireless Communications First Generation Wireless LANs • Peer/Peer and Client/Server • Small User Population • Isolated "Cells" and User Groups • Non-Contiguous Coverage • Indoor Operation • Limited Mobility • Mostly Asynchronous Traffic • Slower than Ethernet • Larger User Population • Managed Services • Full Roaming/Handoff Capability • Contiguous Coverage in Dense Areas • Wider Area Coverage for Community LANs • Mobility (Follow-Me Service) • Mix of Async and Isochronous Traffic • Higher System Utilization • Enhanced Security Merge of 3G and 4G services (WLAN & WAN) Source ATT proposal to IEEE 802.11

48. 802.11: Device Management Process of Managed 802.11 devices in the Standards (Small steps to make good progress) Inter-Access Port Protocol Inter-Communications between APs (Now a Standard) Radio Resource Measurements Ability to obtain MAC and PHY measurements by Upper Layers (Now a Task Group) Enable external entities to manage Devices (APs and Clients) (Proposed Next Logical Step) Remote Managed Device Source ATT proposal to IEEE 802.11

49. IEEE impact on 4G Mobility: Higher layer approach to mobility: • MIP and enhancements e.g. Dynamic Home Agents • Considering proposals to Link layer mobility • That all 802.xx standards adhere to MAC and VLAN bridging Conclusion: Aim is for improved spectral efficiency Incorporating ideas of: • PAN - 802.15.x • VAN – 802.20, 802.16e • HAN – 802.11(a-g) • CAN – 802.16a Potential High Impact on 4G

50. Summary