mimo: challenges and opportunities lili qiu ut austin new directions for mobile system design...
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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 deviceTRANSCRIPT
MIMO: Challenges and Opportunities
Lili QiuUT 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
• Etx = a ETT + b• Erv = c ETT + dwhere a, b, c, d depend on the WiFi card Intel Atheros
a 0.24 ntx + 0.425 MIMO + 1.02
0.38 ntx + 0.108
b 0.045 ntx + 0.108 0.040 ntx + 0.062c 0.30 nrv + 0.61 0.142 nrv + 0.3d 0.064 nrv + 0.167 0.048 nrv + 0.106
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 1 AP 2 AP n…
ClientClient Client … 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
[𝑥1𝑥2]=𝐻− 1[𝑝1𝑝2]
[𝑦1𝑦2]=𝐻 [𝑥1𝑥2]=𝐻𝐻−1[𝑝1𝑝2]=[𝑝1𝑝2]Client Client
AP 1 AP 2
𝒙𝟏 𝒙𝟐
h11 h21 h12h22
𝒚𝟏=𝒑𝟏𝒚𝟐=𝒑𝟐
Uplink: Joint Decoding• APs share their received signals
and jointly decode
Client Client
AP 1 AP 2
𝑝1❑ 𝑝2❑
Share the received signals over the Ethernet
h11 h21h12h22
[𝑦1𝑦2]=[h11 h12h21 h22 ][𝑝1𝑝2]
[𝑝1𝑝2]=𝐻−1[𝑦 1𝑦 2]=𝐻−1𝐻 [𝑝1𝑝2]
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• 802.11 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
0.000.02
0.040.06
0.080.10
0.120.14
0.160.18
00.20.40.60.8
1
Phase misalignment (radian angle)
CDF
Median phase misalignment is 0.078 radianand reduces SNR by 0.4 dB.
Downlink Throughput
Downlink throughput almost linearly increases with # antennas across different APs or clients.
116QAM
216QAM
3QPSK
4QPSK
5BPSK
0
1
2
3individual2x2 downlink3x3 downlink
Location ID
Thro
ughp
ut (M
bps)
Uplink Throughput
116QAM
2QPSK
3QPSK
4 5BPSK
0
10
20
30 individual2x2 uplink3x3 uplink
Location ID
Thro
ughp
ut (M
bps)
Uplink throughput almost linearly increases with # antennas across different APs or clients.
Rate adaptation (downlink)
0 24 48 72 96 1201441681922162402642880
1
2Best fixed ESNR
Packet Trace Index (x 20)
Thro
ughp
ut (M
bps)
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 decodeClients
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 Client
AP 1 AP 2
𝒆 𝒋∆𝟏 𝒆 𝒋∆𝟐 [𝑥1𝑥2]=[𝒆 𝒋 ∆𝟏 00 𝒆 𝒋 ∆𝟐 ]𝐻− 1[𝑝1𝑝2]
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 side2. Feedback to the transmitter3. Compensation at the transmitter
𝑒 𝑗 ∆1(𝑡 )=𝑒 𝑗2𝜋 𝑓 𝑐❑1 𝑐𝑡
30 / 40
Handling phase differenceCFO measurement and feedback
• AP 1 sends LTS (long training sequence) to clients
• Client measures CFO (carrier frequency offset) based on it
Client Client
AP 1 AP 2
LTS 1
31 / 40
Handling phase differenceCFO measurement and feedback
• AP 1 sends LTS (long training sequence) to clients
• Client measures CFO (carrier frequency offset) based on it
• AP 2 sends LTS to clients• Client measures CFO based on it
Client Client
AP 1 AP 2
LTS 2
32 / 40
Handling phase differenceCFO measurement and feedback
• AP 1 sends LTS (long training sequence) to clients
• Client measures CFO (carrier frequency offset) based on it
• AP 2 sends LTS to clients• Client measures CFO based on it• Client feedbacks them to APs
Client Client
AP 1 AP 2
FEEDBACK
33 / 40
Handling phase differenceCFO measurement and feedback
• AP1 sends precoded signal with phase rotation
Client Client
AP 1 AP 2𝑥1′ (𝑡 )
34 / 40
Handling phase differencePhase rotation compensation
• AP1 sends precoded signal with phase rotation
• AP2 sends phase rotation compensated precoded signal
=Client Client
AP 1 AP 2𝑥1′ (𝑡 ) 𝑥2′ (𝑡 )
35 / 40
Handling phase differencePhase rotation compensation
• Clients receive the signals with unified phase rotation
• Each client separately compensates during its CFO compensation process
Client Client
AP 1 AP 2
𝑝1𝒆 𝒋∆𝟏
𝑝2𝒆 𝒋∆𝟏
36 / 40
Multi-point to Multi-point MIMO in WLANs [INFOCOM’13]
• Motivation–MIMO promises a capacity increase• 802.11n, 802.11ac, …
– But usually limited by # antennas at a client
–Multi-point to multi-point MIMO achieves a higher capacity and overcomes the limitations