MIMO: Challenges and Opportunities Lili Qiu UT Austin New Directions for Mobile System Design Mini-Workshop

Motivation Benefits of MIMO – Large capacity increase – High reliability Challenges in achieving MIMO gain – Power efficiency – Distributed MIMO in WLANs – Distributed MIMO in multihop networks

Model-Driven Energy-Aware MIMO Rate Adaptation [MobiHoc’13] Why simple rule doesn’t work? – Highest throughput ≠ lowest energy – One antenna ≠ lowest energy – The min energy rate depends on channel condition and energy profile of WiFi device

Why Model-Driven? Probing may take a long time and may not find the optimal rate by the time channel changes – Probing space is large especially w/ MIMO Model-driven – Estimate power consumption for each rate – Directly select the one w/ lowest power

Measurement-Driven Energy Model E tx = a ETT + b E rv = c ETT + d where a, b, c, d depend on the WiFi card IntelAtheros a 0.24 n tx MIMO n tx b n tx n tx c 0.30 n rv n rv d n rv n rv

Model Validation Intel WiFi transmitter Intel WiFi receiver Error is within 5%.

Model Validation (Cont.) Atheros WiFi transmitter Atheros WiFi receiver Error is within 5%.

Energy Aware Rate Adaptation Measure CSI Compute post-processed CSI Compute ETT Compute energy using model Select rate with min energy It reduces energy by 15-40%.

Multi-point to Multi-point MIMO in WLANs [INFOCOM’13] AP 1AP 2AP n … Client … n concurrent uplink or downlink streams

Downlink: Zero-Forcing Precoding APs precode the signal so that the receiver can decode it with one antenna Each client separately gets its intended signal Client AP 1 AP 2

Uplink: Joint Decoding APs share their received signals and jointly decode Client AP 1AP 2 Share the received signals over the Ethernet

Our Contributions Demonstrate the feasibility and effectiveness of multi-point to multi- point MIMO on USRP and SORA – Downlink: phase and time synchronization – Uplink: time synchronization Design multi-point to multi-point MIMO-aware MAC

MAC Design Medium Access Support ACKs Rate adaptation Dealing with losses and collisions Scheduling transmissions Limiting Ethernet overhead Obtaining channel estimation

MAC Design Medium Access Support ACKs Rate adaptation Dealing with losses and collisions Scheduling transmissions Limiting Ethernet overhead Obtaining channel estimation

Medium Access compatible MAC design – CSMA/CA – A winning AP/client triggers the selected APs/clients to join its transmission – Trigger frame has NAV set till the end of data transmission

Supporting ACKs ACKs enjoy the same spatial multiplex in the reverse direction Downlink – Clients multiplex ACK to APs and APs jointly decode Uplink – APs multiplex ACK to clients via precoding

Rate Adaptation (downlink) Challenges – Receiver receives a combination of signals from all of the transmitting APs – Per link SNR based rate adaptation does not work

Rate Adaptation (downlink) Error vector magnitude (EVM) based SNR – Distance between the received symbol and the closest constellation point

Evaluation Implementation using USRP and SORA Performance evaluation – Phase alignment – Downlink throughput – Uplink throughput – Rate adaptation (downlink)

Downlink Phase Misalignment Median phase misalignment is radian and reduces SNR by 0.4 dB.

Downlink Throughput Downlink throughput almost linearly increases with # antennas across different APs or clients.

Uplink Throughput Uplink throughput almost linearly increases with # antennas across different APs or clients.

Rate adaptation (downlink) Achieves close to 96% throughput of best fixed rate.

Distributed MIMO in Multihop Wireless Networks How to relay signals while achieving spatial multiplexing?

Distributed MIMO in Single-hop Wireless Networks APs share received signals over Ethernet to jointly decode Clients Ethernet

Distributed MIMO in Multihop Wireless Networks Receivers can’t share received signals for free! How can they relay signals without decoding them while still allowing the destination to decode?

Distributed MIMO in Multihop Wireless Networks How to relay while achieving spatial multiplexing? How to select distributed MIMO routes? How to design a practical routing protocol?

Thank you!

Challenge of downlink Each AP generate signal based on its own clock Signals from two APs have different phase rotation Client AP 1 AP 2 29 / 40

Handling phase difference The reason of different phase rotation: different center frequency offset (CFO) by using separate clock How to synchronize it? 1.Measurement of CFO at the receiver side 2.Feedback to the transmitter 3.Compensation at the transmitter 30 / 40

Handling phase difference CFO measurement and feedback Client AP 1AP 2 LTS 1 31 / 40

Handling phase difference CFO measurement and feedback Client AP 1AP 2 LTS 2 32 / 40

Handling phase difference CFO measurement and feedback Client AP 1AP 2 FEEDBACK 33 / 40

Handling phase difference CFO measurement and feedback Client AP 1AP 2 34 / 40

Handling phase difference Phase rotation compensation Client AP 1AP 2 35 / 40

Handling phase difference Phase rotation compensation Client AP 1AP 2 36 / 40

Multi-point to Multi-point MIMO in WLANs [INFOCOM’13] Motivation – MIMO promises a capacity increase n, ac, … – But usually limited by # antennas at a client – Multi-point to multi-point MIMO achieves a higher capacity and overcomes the limitations