Wireless Networks Should Spread Spectrum On Demand

1
Wireless Networks Should Spread Spectrum On Demand

• Ramki Gummadi (MIT)?
• Joint work with Hari Balakrishnan

2
The problem Bursty traffic

• Demand variability observable even at short (30
  s) time scales
• From OSDI 2006 traces
• Five APs, three orthogonal channels
• Spatio-temporal demand variations common

3
Today Static spectrum allocation

• Partitioned into non-interfering channels
• Avoid CSMA hidden and exposed terminals
• Avoid back-offs

X
4
Insight Spectrum tracks demand

• Spectrum tracking demand achieves higher SINR
  than shifting demand to where spectrum is

5
ODS On-Demand Spectrum

• Demand-based spectrum to nodes
• Uses spread-spectrum codes
• Allocates multiple codes to transmitters
• A single transmitter can use entire spectrum

6
Key challenge

• Avoid inter-AP coordination
• Different admin domains
• Demand-communication overhead

X
7
Mechanism Spread-spectrum codes
Data
Signal
Concurrent
Code
Alices code
Received signal
Bobs code
Copy of received signal
8
Roadmap

• ODS design
• Determine demands
• Allocate codes
• Ensure conflict-freedom
• Use multiple codes concurrently
• ODS evaluation

9
Determining demands

• An AP computes demands of its own clients
• Averaged over last 30 s
• Demand if queue length qi, bit-rate ri
  
• For uplink, a client tells its queue length to AP

10
Allocating codes

• Large (128) codebook c of random codes
• Same at each AP
• AP allocates transmitter
  codes
• Minimizes mean transmission time. (Fairness?)?

11
Code assignment

• Each AP assigns codes to transmitters from the
  codebook randomly
• No coordination among APs

. .
. .
12
Code selection

• Each transmitter selects up to k (11, say) codes
  from its allocation randomly
• With 2 tx, 1 code, no-conflict probability
• With n transmitters, 1 code,
• If n tx, k codes, conflict-free code number
• Optimum code number as

The optimum conflict-free code number under
random selection within factor e of centralized
13
Random code selection performance
Random selection policy can be both efficient
and robust

• High throughput at low contention
• Non-zero throughput even with 128 interferers

14
Finding conflict-free codes

• Transmitter uses feedback from receiver
• Assign success probability p 0,1 per code
• Toggle p based on receiver feedback
• p0 at tx whose hashed id closest to code

. .
. .
id010
id100
code101
15
Using codes concurrently

• Divide packet into sub-packets
• Use one code per sub-packet
• Transmit all coded sub-packets concurrently
• Packet header tells receiver which codes are used
• Codes in conflict easy to identify at receiver

Packet
16
Recap Avoid inter-AP coordination

• Two key mechanisms
• Random code selection
• Efficient and robust
• Feedback-based conflict detection
• Decentralized

17
Roadmap

• ODS design
• Determine demands
• Allocate codes
• Ensure conflict-freedom
• Use multiple codes concurrently
• ODS evaluation

18
Challenge Data reduction
De-spreading
Synchronization

• USRP/GNURadio USB throughput-limited
• Two steps needed for data reduction
• De-spreading and synchronization
• FPGA de-spreads, followed by synchronization
• Transmitter design similar

19
Preliminary evaluation
ODS, two bonded 2 Mbps links
No ODS, two bonded 2 Mbps links
ODS improves link throughput by 75
20
Related work

• Plain CDMA
• Inefficient spectrum usage with bursty traffic
• Sub-optimal
• Load-aware spectrum distribution (MSR)?
• Uses channel-widths instead of codes
• Inter-AP coordination (10-minute updates)?

X
CDMA
21
Contributions

• Exploit bursty demands to improve spectrum usage
• Demand-based code allocation
• Challenge Avoid inter-AP coordination
• Random code selection
• Feedback-based conflict detection
• Future work Better implementation, evaluation
• Need high-throughput, low-latency radios