scaling the throughput of wireless mesh networks via physical carrier sensing and two-radio multi-...
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Scaling the Throughput of Wireless Mesh Networks via Physical Carrier
Sensing and Two-Radio Multi-Channel Architecture
Jing Zhu*, Sumit Roy*, Xingang Guo**, and W. Steven Conner**
*Department of Electrical EngineeringU of Washington, Seattle, WA
**Communications Technology LabIntel Corporation, Hillsboro, OR
Outline of Presentation
• Mesh Networks: Introduction, Architecture
• Enhancing Aggregate (Network) Throughput 1. Enhance spatial reuse via optimal physical carrier sensing 2. Multiple Orthogonal Channels (frequency reuse) Channel Allocation with clustering
• Multi-Radio, Multi-channel Architecture Towards a soft-radio architecture for high-performance MESH
Mesh Networks: Salient Features Scalability for coverage
Single hop Multi-hop (mesh) Heterogeneous Nodes, Hierarchy
Mobile Clients, APs, SoftAPs (router) Multiple PHY technologies
WiFi, WiMAX, UWB, …
Challenge for MAC in Mesh- Current MAC Protocols (e.g. 802.11) are not optimized for Mesh
low efficiency, poor fairness, …
Key Solution Approach: Spatial Reuse + Channel Reuse
1. As # clients (laptops) increase, more APs are needed in the same area.
2. Available # orthogonal channels is very limited (3 or 8 in 11b/a) increased multiple acccess interference.
Example1: AP-MT Mesh–Enterprise
Link Capacity
PHY Optimization: MIMO, Adaptive Coded Modulation, etc.
Frequency Plan: 3 (11b), 7 (11a), ? (11n)Topology Control
MAC Optimization
How to scale a MESH?
Network Throughput
=
Frequency (Channel) Reuse
Spatial Reuse
X X
Our Focus
Outline
CSMA/CA – the core of 802.11 MAC Spatial Reuse and Physical Carrier Sensing
Implementation of PCS in OPNET: Simulation of Spatial Reuse
Enhance Physical Carrier Sensing SchemeOptimal PCS threshold through tuning: PCS adaptation
Channel Reuse: Two-Radio Multi-Channel Clustering Architecture
Next-gen: Adaptive MAC Framework for Mesh
CSMA/CA – basic 802.11 MAC
Carrier Sensing Multiple Access / Collision Avoidance
Physical Carrier Sensing (PCS) for Interference AvoidanceBinary Exponential Back-off (BEB) for Collision Avoidance (Optional) RTS/CTS Handshaking
Advantages: Asynchronous, Distributed, Simple
Disadvantages:Low Spatial Reuse (due to Non-optimized PCS)No QoS Support (due to pure contention-based
access)
Spatial Reuse Multiple communications using the same channel/freq happen
simultaneously at different locations w/o interfering each other Received SINR Model:
Physical Carrier Sensing A station samples the energy in the medium and initiates
transmission only if the reading is below a threshold threshold optimization
0.00E+00
1.00E+06
2.00E+06
3.00E+06
4.00E+06
5.00E+06
6.00E+06
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
SNIR (dB)
On
e-H
op
Ca
pa
cit
y (
bp
s)
1 Mbps
2 Mbps
5.5 Mbps
11 Mbps
Hidden node Problem Revisited
R
I1
I2 …
Any node outside of transmission range of Tx and Rx could be a hidden node, which cannot be prevented by using RTS/CTS!
A1
B1
B2
RxTx
Hidden Node: A node that cannot hear the current transmission but will cause the failure of the transmission if it transmits.
Hidden Nodes in a MESH
Multiple (group) of hidden nodes in a mesh Accumulation of interferences Impossible to identify due to the unknown number of
contributors.
Instead of preventing all hidden nodes, the goal of the interference avoidance/mitigation is pro-actively avoiding the worst-case interference
Sensed energy during PCS is a good indicator of interference level on the coming transmission.
The lower the sensing threshold, the higher the received SNIR on average
Has a great impact on the performance
PHY improvement does NOT necessarily mean proportional improvement at MAC
Optimal PCS threshold varies with data rates and topology
How to set the optimal carrier sensing threshold dynamically?
-30 -25 -20 -15 -10 -5 0
30k40k50k60k70k80k90k
100k110k120k130k140k150k160k170k180k190k200k
=2, n=90, Ptx=0dbm, P
N = - 200dbm, d = 12.5 m, R =13 m
1 Mbps 2 Mbps 5.5 Mbps 11 Mbps
E2E
Thr
ough
put (
bps)
pcs_t
(db)
...d
0 1 2 n
Effect of PCS threshold on Network Throughput
Analytical estimate of end2end t’put: Observations:
Near optimal results can be achieved by simply tuning the carrier sensing threshold without using RTS/CTS
(simulation is for 90-node Chain)
kW /
[1] Xingang Guo, Sumit Roy, W. Steven Conner, "Spatial Reuse in Wireless Ad-hoc Networks," IEEE VTC 2003, Orlando, FL, October, 2003.
Comparison with analytical estimates
Optimal PCS Threshold
Assumptions:Co-location of receiver and transmitterHomogenous links (same reception power) Ignore background noiseSaturation traffic load
Result: Optimal PCS Threshold ≈ 1/S0, where S0 is the SINR
threshold for sustaining the maximum link throughputS0 = 11dB, 14dB, 18dB, and 21dB for 802.11b 1Mbps,
2Mbps, 5.5Mbps, and 11Mbps, respectively.
-29.0 -27.0 -25.0 -23.0 -21.0 -19.0 -17.0 -15.0 -13.0 -11.0 -9.0 -7.0 -5.00.0
500.0k
1.0M
1.5M
2.0M
2.5M
3.0M
3.5M
4.0M
=2.5
=3
=2
data rate =1Mbps, n=10x10, Random Traffic, PN=-200dbm
Tot
al O
ne-H
op T
hrou
ghpu
t
pcs_t
(db) -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -101.0M
1.5M
2.0M
2.5M
3.0M
3.5M
4.0M
4.5M
5.0M
5.5M
6.0M
=2.5
=3
=2
data rate =2Mbps, n=10x10, Random Traffic, PN=-200dbm
Tot
al O
ne-H
op T
hrou
ghpu
t
pcs_t
(db)
-20 -19 -18 -17 -16 -15 -14 -13 -120.0
2.0M
4.0M
6.0M
8.0M
10.0M
=2.5
=3
=2
data rate =5.5Mbps, n=100, Random Traffic, PN=-200dbm
Tot
al O
ne-H
op T
hrou
ghpu
t
pcs_t
(db)
-25 -24 -23 -22 -21 -20 -19 -18 -17 -16 -150.0
2.0M
4.0M
6.0M
8.0M
10.0M
12.0M
=2.5
=3
=2
data rate =11Mbps, n=100, Random Traffic, PN=-200dbm
Tot
al O
ne-H
op T
hrou
ghpu
t
pcs_t
(db)
10x10 Grid with Local Only Traffic and Homogenous Links
Comparison of 1/S0 with the Simulation Optimal PCS threshold
1/S0(dB)
Simulations match the theoretical estimates !
Enterprise Network: AP-MT Mesh
3 Channels16 / 30 / 72/ 110 APs
per channel11Mbps, So = 21dB154 m x 154 m OfficePath Loss Exponent =3
Scale the Capacity of Enterprise AP Network
10 20 30 40 50 60 70 80 90 100 110 1200.0
5.0M
10.0M
15.0M
20.0M
25.0M
30.0M
35.0M
Without Spatial Reuse
Optimal PCS Today's PCS
Netw
ork
Cap
acit
y (
bp
s)
# AP
1. Network capacity is proportional to # of APs2. The optimal PCS achieves best per-AP capacity
28%40%
60%
73%
Summary: Spatial-Reuse for a single-channel MESH
Spatial-Reuse – the key to improve the aggregate throughput of a single-channel mesh links sufficiently separated can transmit simultaneously
without interfering each other
Limitations: Not effective for a small scale network, i.e. the required
minimum separation distance could be high. For example, >7 hops in a regular chain network with
802.11b 1Mbps and path loss exponent = 2. Further Scaling the Throughput with Multiple Channels!
Scaling the Throughput with Multiple Channels
Takes advantage of multiple channels (even multiple bands) 8 orthogonal channels in 802.11 a 3 orthogonal channels in 802.11 b UWB, 802.11, and 802.16
Channel Bonding (wider channel BW) is another alternative Increases peak link rate but does not translate to proportional
MAC throughput increase Lack of backward compatibility: proprietary solution
Multi-channel Approaches – Our Choice No change on channel BW Use all available channels through the network Key issues: channel allocation
Feasible Multi-Channel Architectures One-Radio Multi-Channel Approaches*
Efficient, but will require new MAC (hence not backwards compatible) Still cannot do full-duplex transmission (e.g.difficult to conduct channel sensing consistently
due to channel switching) Control overhead – per-packet channel swtiching
Multi Radio: One Channel per NIC(Network Interface Card) ** Simple to implement
Each NIC channel is fixed (i.e. comes hard-coded from manufacturer) no negotiation required for channel selection
Fully compatible with legacy But costly, will not scale (number of NICs = number of channels)
Our Approach: Two Radio Multi-Channel Scale, i.e. number of NICs fixed at 2 Backwards compatible Assumptions: ad-hoc scenario, irregular but not random topology, homogenous traffic No
need to frequently update the channel allocation!
*:Jiandong LI, Zygmunt J. Haas, and Min Sheng; ``Capacity Evaluation of Multi-Channel Multi-Hop Ad Hoc Networks ''; IEEE International Conference on Personal Wireless Communications, ICPWC 2002. **: A. Adya, P. Bahl, J. Padhye, A. Wolman, and L. Zhu, A Multi-Radio Unification Protocol for IEEE 802.11 WirelessNetworks, Microsoft Research, Technical Report MSR-TR-2003-44, July, 2003.
Two-Radio Based Network Cluster
• Channel Allocation with Clustering • Each cluster is identified a common channel – i.e. all inter-cluster
communications using the default (primary) radio• Intra-cluster communications on different channels using the secondary
radio• Interference Mitigation
• Interference among co-channel clusters is minimized through an efficient channel selection algorithm – MIX (min. interference channel select).
• Interference within the cluster is prevented by Physical Carrier Sensing.• Legacy compatible: legacy APs connect to mesh via default radio.
Channel 1
Channel 2
Channel 3 DefaultMAC/PHY
SecondaryMAC/PHY
MAC Extension
IP
Framework Semi-distributed clustering channel
assignment + distributed MAC mechanisms (802.11 DCF) Semi-distributed: channel on
secondary radio is assigned by the local cluster-head within the cluster
Distributed: CSMA/CA MAC protocols
Default vs. Secondary Radio Both radios are for data
transmission The secondary radio has no
administrative functionality, such as association, authentication, etc.
The common channel on the default radio is determined a-priori.
Layer 3 (IP) routing between the nodes
Clustering(HCC)
Channel Selection (MIX)
I am Cluster Head.
Configure the 2nd PHY/MAC
Fin
d
Channel
Cluster Head is down.
Reset the 2nd PHY/MAC
Reset the 2nd PHY/MAC
Receive Channel Update Information From Cluster Head
Channel Information
Expired
Distributed Highest Connection Clustering (HCC) Algorithm*
A node is elected as a clusterhead if it is the most highly connected (has the highest number of neighbor nodes) node of all its ``uncovered" neighbor nodes (in case of a tie, lowest ID (e.g. MAC address) prevails).
A node which has not elected its clusterhead is an “uncovered” node, otherwise it is a “covered” node.
A node which has already elected another node as its clusterhead gives up its role as a clusterhead.
* M. Gerla and J.T.-C. Tsai, "Multicluster, mobile, multimedia radio network", ACM/Baltzer Journal of Wireless Networks. vol. 1, (no. 3), 1995, p. 255-265.
Clustering Procedure
Step 1: All nodes have their neighbor list ready (every node should know its neighbors, how many)
Step 2: All nodes broadcast their own neighboring information, i.e., the number of neighbors, to its neighborhood.
Step 3: A node that has got such information from all its neighbors can decide its status (clusterhead or slave)
MIX – Minimum Interference Channel Selection On-Air energy estimation per channel
t0: estimation starting time T: estimation period Ei(t): on-air energy at time t on channel i
k: Selected Channel
T
dttEE
Tt
t i
i
0
0
)(
}),...,2,1{|min(| niEEk ik
Forwarding Table (MAC Extension)
Neighbor MAC/PHY
192.168.0.2 Secondary
Neighbor MAC/PHY
192.168.0.2 Default
192.168.0.4 Secondary
Neighbor MAC/PHY
192.168.0.1 Secondary
192.168.0.3 Default
192.168.0.1
192.168.0.2
192.168.0.3
192.168.0.4
Neighbor MAC/PHY
192.168.0.3 SecondaryCluster 1
Cluster 2
An IP packet will be forwarded to default or Secondary MAC/PHY according to the forwarding table in the MAC Extension layer.
DefaultMAC/PHY
SecondaryMAC/PHY
MAC Extension
IP
Example – 10 x 10 Grid
Cluster-Head
Cluster-Slave
Transmission range = d
d: neighboring distance
2
ChannelStatus
6Number of UncoveredNeighboring Nodes
8Bits 2
00
01
10
Uncovered
Cluster Head
Cluster Member
Simulation Topology
Random, Local, and Saturate Traffic
10 x 10 Grid 802.11 b 1Mbps 3 orthogonal channels Path Loss Exponent = 3 Packet Size =1024
Bytes Dash Circle: Cluster Dark node: Cluster-Head
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Channel 1 Channel 2
B1 B2 B3 B4 B5 B6 B7 B8 B9 B10
A1 A2 A3 A4 A5 A6 A7 A8 A9 A10
C1 C2 C3 C4 C5 C6 C7 C8 C9 C10
Tracing One-Hop Aggregate Throughput
The new multi-channel and two radio architecture achieves 3X performance, compared to a traditional single-channel and single-radio mesh.
0 100 200 300 400 5000
1M
2M
3M
4M
5M
6M
7M
8M
9MData Rate = 1MbpsPacket Size = 1024 BytesPath Loss Exponent = 3
Traditional Single-Channel and Single-Radio Mesh
Clustering Multi-Channel and Two-Radio Architecture
Th
rou
gh
pu
t (b
ps)
Time (sec.)
Throughput Distribution
Location-dependent fairness problem : Links Ai experience worse interference environment than links Bi and Ci, leading to the oscillation of the throughput distribution.
Future Work: How Physical Carrier Sensing could mitigate the location dependent fairness problem?
0 100 200 300 400 500 600 700
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100000 C10C9C8
C7
C6
C5C4C3C2C1 B10
B9
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A1
On
e-H
op
Th
rou
gh
pu
t (b
ps)
Link
Clustering Multi-Channel and Two-Radio Mesh Traditional Single-Channel and Single-Radio Mesh
Performance Comparison in Random Topology
a) Tracing Aggregate Throughput b) Throughput Distribution
Performance gain of aggregate throughput is almost 3x (10Mbps vs. 3.5Mbps)
0 100 200 300 400 5000
1M
2M
3M
4M
5M
6M
7M
8M
9M
10M
Data Rate = 1MbpsPacket Size = 1024 BytesPath Loss Exponent = 3
Traditional Single-Channel and Single-Radio Mesh
Clustering Multi-Channel and Two-Radio Architecture
Thr
ough
put
(bp
s)
Time (sec.)
100 200 300 400
100
1000
10000
100000
On
e-H
op T
hro
ugh
put (
bps)
Link
Clustering Multi-Channel and Two-Radio Mesh Traditional Single-Channel and Single-Radio Mesh