Joint PHY-MAC Designs and Smart Antennas for Wireless Ad-Hoc Networks

1. Joint PHY-MAC Designs and Smart Antennas for Wireless Ad-Hoc Networks CS 838 - Mobile and Wireless Networking (Fall 2006)

2. Review of IEEE 802.11a/b/g PHY/MAC PHY • Modulation: Orthogonal Frequency Division Multiplexing (OFDM) (11a/11g) or Direct Sequence Spread Spectrum (DS-SS) (11b/11g) • Antenna Technology: Single omni-directional antenna • 2 antenna Access Points (APs) ? • APs with directional antennas ? MAC • Physical Carrier Sensing: Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) • Virtual Carrier Sensing:Request-to-Send/Clear-to-Send (RTS/CTS) handshake (Hidden node avoidance)

3. Review of Hidden Node Problem Pure CSMA/CA Carrier Sense? Clear

4. 802.11 Solution of Hidden Node Problem CSMA/CA with RTS/CTS Virtual Carrier Sense? Busy RTS CTS

5. Some Limitations of 802.11 PHY/MAC PHY • Throughput (bits/sec): Antenna technology limits spatial re-use Physical Carrier Sensing Virtual Carrier Sensing

6. Some Limitations of 802.11 PHY/MAC (contd.) MAC • Throughput: RTS/CTS handshake further limits the spatial re-use in the network • Fairness (and Throughput):RTS/CTS fails to completely take care of the hidden node problem, resulting in dropped packets for one transmission more than the other • Interference range is typically more than the successful reception range of CTS • Fairness: 802.11 MAC can unfairly favor one transmission over the other as a function of the distance between the nodes X CTS

7. 802.11 Simulated Performance [TPHN04] Linear Topology: 2 3 1 0 200 m 200 m D Throughput reduction (and unfairness) due to spatial proximity Hidden node effect

8. [TPHN04] Proposed Solution PHY • Single transmit/multiple receive antennas with OFDM modulation MAC • Mitigating Interference using Multiple Antennas MAC (MIMA-MAC) • Built on top of 802.11 MAC with antenna awareness • N nodes in spatial proximity would be allowed to transmit simultaneously in a network of nodes with N receive antennas • PHY expected to cancel the interference of (N-1) unintended flows using advanced signal processing techniques

9. [TPHN04] Simulation Results Topology: Simulation Technique • PHY Simulation: MATLAB (with channel bandwidth of 2 MHz and data rate of 1 Mbps) • MAC Simulation: ns-2 (fed with look-up tables mapping channel realizations to corresponding BER’s obtained from MATLAB) Other Parameters • Input SNR: 12dB; Path-loss exponent: 4; Packet reception threshold BER: 10-5; Carrier sensing threshold BER: 10-1

10. [TPHN04] Simulation Results (contd.) Throughput Performance for Multiple Receive Antennas MIMA-MAC vs Conventional 802.11 MAC

11. [TPHN04] Simulation Results (contd.) Fairness Performance for Multiple Receive Antennas MIMA-MAC vs Conventional 802.11 MAC

12. Smart Antennas for Wireless Ad-Hoc Networks Switched Beam Antennas • Pre-determined set of weights applied to different antenna elements to form a fixed number of high-directionality beams • A K element array can form up to K beams • The directionality gain of each beam at the transmitter and the receiver is given by (assuming LOS/low angular spread) • Assuming that the transmitter and the receiver know each other’s direction, the total transmission gain (SNR gain) is bounded by

13. Smart Antennas for Wireless Ad-Hoc Networks Fully Adaptive Arrays • Fully adaptive set of weights applied to different antenna elements to adaptively change the radiation pattern • A K element array has K degrees-of-freedom (DOFs), and can adaptively null (K-1) uncorrelated interferers • Even in the presence of significant multipath scattering, the total transmission gain (SNR gain) of an adaptive array can be given by • Very high multipath scattering and low signal correlation can some- times limit the gain to

14. Smart Antennas for Wireless Ad-Hoc Networks MIMO Links • Digital adaptive arrays capable of operating in two modes: Spatial Multiplexing and Diversity • A rich set of multipath scattering between the transmitter and the receiver transforms a K element MIMO link into K independent links • In multiplexing mode, this can result in K fold increase in the data rate of the MIMO link • In diversity mode, this can result in a reduction in the variance of the received SNR. At high SNR, this results in

15. Smart Antennas can be leveraged for … 1) Higher Data Rate • For a given modulation scheme, the bit-error-rate (BER) on a link is determined by the link SNR • Switched Beam/Adaptive Array: Gain in SNR (G)  Perform adaptive modulation to increase bits transmitted per symbol and keep BER the same • MIMO Link: Operate the link in the spatial multiplexing mode

16. Smart Antennas can be leveraged for … 2) Increased Transmission Range • The transmission range of a link is related to the link SNR by • Switched Beam/Adaptive Array: Gain in SNR (G)  Obtain a range extension factor given by • MIMO Link: Operate the link in the diversity mode. Not a straight forward relationship between the diversity order and the range extension, so resort to MATLAB simulations (diversity mode only reduces SNR variance)

17. Smart Antennas can be leveraged for … 3) Increased Link Reliability • For a fixed data rate (modulation scheme), the bit-error-rate (BER) on a link is determined by the link SNR • Switched Beam/Adaptive Array: Gain in SNR (G)  For the same data rata, obtain a reduction in the BER by a factor of • MIMO Link: Operate the link in the diversity mode. For the same data rate, this can result in a reduction in the BER by a factor of

18. Smart Antennas can be leveraged for … 4) Reduced Transmit Power • Switched Beam/Adaptive Array: Gain in SNR (G)  For the same BER, obtain a reduction in the transmit power by a factor of • MIMO Link: Operate the link in the diversity mode. For the same BER, this can result in a reduction in the transmit power given by

19. [SLS06] Simulation Model Antenna Model • Switched Beam Array: Pre-determined, fixed beam pattern • Adaptive Array/MIMO Link: Dynamically tunable beam pattern Channel Model • PHY: BER obtained fromMATLAB simulations by assuming a fast Rayleigh fading collision channel model (per location, antenna technology and strategy), with data rate of 2 Mbps, transmit power of 20 dBm, SINR of 10 dB and fade margin of 0-10 dB • Link: Packet loss probability obtained from ns-2 (fed with look-up tables of PHY simulations), with packet size of 1000 bytes

20. [SLS06] Simulation Model (contd.) Network and Traffic Model • 100 nodes over a rectangular grid of 400x400 m to 1000x1000 m • Number of simultaneous flows in the network varied from 1 to 50 • Multipath scattering varied from LOS to 180 degrees (rich scatter) • Number of antenna elements per node varied from 1 to 12 • Initial transmission range of each node set to 100 m Metrics • Throughput (T): Bits per second, normalized by the number of flows • Throughput/Energy (TE): Bits per unit of Joule consumed (consisting of communication circuit power Pc, transmit power Pt and computational power)

21. [SLS06] Simulation Model (contd.) Protocols and Algorithm • Goal: Obtain fundamental tradeoffs in the operation of different antenna technologies • Requires: Suppressing the inefficiencies of other factors • Solution: Centralized algorithm for finding routes, scheduling slotted transmissions, ensuring fairness, taking care of interferences etc. • Routing Strategy: Djikstra’s algorithm Caveat • Simulation results are not indicative of how things might perform in a distributed setting

22. [SLS06] Strategy Comparison: T Metric Switched Beam Adaptive Array MIMO Links Setup • High density network, load of 50 flows, fading loss of 5%, scattering angle of 90 degrees

23. [SLS06] Strategy Comparison: T Metric (contd.) Exceptions • Under low node density and small number of flows, range works better (better connectivity) 4 Antenna elements per node

24. [SLS06] Strategy Comparison: TE Metric Switched Beam Adaptive Array MIMO Links Setup • High density network, load of 50 flows, fading loss of 5%, scattering angle of 90 degrees and Pt >> Pc

25. [SLS06] Strategy Comparison: Inferences Moderate-High Network Densities Low Network Densities

26. [SLS06] Antenna Technology Comparison Parameters of Interest • Network node density • Number of antenna elements • Number of network flows • Scattering angle • Fading loss Components Impacting T and TE Metrics • Number of independent contention regions  density • Number of active links/contention region flows and density • Number of resources/contention region  elements and scattering

27. [SLS06] Technology Comparison: T Metric(Scattering and Elements under Rate Strategy) Rich Scattering: Low Scattering: Rich scattering does not degrade MIMO links’ rate performance

28. [SLS06] Technology Comparison: T Metric(Scattering and Fading under Rate Strategy) Fading impacts all rate strategies alike!

29. [SLS06] Technology Comparison: T Metric(Flows and Elements under Rate Strategy) Low Load: High Load: No logarithmic effect for MIMO at low load

30. [SLS06] Technology Comparison: T Metric(Flows and Density under Rate/Range Strategy) Low Load & High Density: Low Load & Moderate Density: Low Load & Low Density:

31. [SLS06] Technology Comparison: TE Metric(Pt >> Pc: Power/Range Strategy) Low Scattering & Large Elements: Other Network Conditions:

32. [SLS06] Technology Comparison: TE Metric(Pt ~< Pc: Rate/Range Strategy) Majority of Network Conditions: