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

Review of IEEE a/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)

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

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

Some Limitations of PHY/MAC PHY Throughput (bits/sec): Antenna technology limits spatial re-use Physical Carrier SensingVirtual Carrier Sensing

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: MAC can unfairly favor one transmission over the other as a function of the distance between the nodes Some Limitations of PHY/MAC (contd.) CTS X

Simulated Performance [TPHN04] Linear Topology: m D Hidden node effect Throughput reduction (and unfairness) due to spatial proximity

[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 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

[TPHN04] Simulation Results 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) Topology: Other Parameters Input SNR: 12dB; Path-loss exponent: 4; Packet reception threshold BER: ; Carrier sensing threshold BER: 10 -1

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

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

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

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

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

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

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)

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

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

[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 from MATLAB 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

[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 P c, transmit power P t and computational power)

[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

[SLS06] Strategy Comparison: T Metric Switched BeamAdaptive ArrayMIMO Links Setup High density network, load of 50 flows, fading loss of 5%, scattering angle of 90 degrees

[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

[SLS06] Strategy Comparison: TE Metric Switched BeamAdaptive ArrayMIMO Links Setup High density network, load of 50 flows, fading loss of 5%, scattering angle of 90 degrees and P t >> P c

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

[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

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

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

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

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

[SLS06] Technology Comparison: TE Metric ( P t >> P c : Power/Range Strategy) Other Network Conditions:Low Scattering & Large Elements:

[SLS06] Technology Comparison: TE Metric ( P t ~< P c : Rate/Range Strategy) Majority of Network Conditions: