future opportunistic frequency agile wireless …implementation of cognitive mac protocol warp is...
TRANSCRIPT
Future Opportunistic Frequency Agile Wireless Networks: Theory & Implementation Challenges
Kaveh Ghaboosi
Centre for Wireless Communications
University of Oulu
Outline
Part I: MAC Protocols in Mobile Ad Hoc Networks
Problems in wireless ad hoc networks:
Hidden terminal problem
Exposed terminal problem
Unreachability problem
Proposed Scheme: eMAC
Part II: MAC Protocols for Cognitive Radio Networks
Problems and open issues in multi-hop cognitive networks
Multi-channel hidden terminal problem
Multi-channel unreachability problem
Stochastic channel selection mechanism in cognitive networks
Part I:
MAC Protocols for Mobile Ad Hoc Networks
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Introduction
Two major types of wireless networks:
Infrastructure Wireless Local Area Networks (WLANs) With central entity, named as Access Point (AP).
Mobile Ad Hoc Networks (MANETs) Without central entity exists.
Problems in Wireless Ad Hoc Networks
Three major problems can be identified:
Hidden Terminal Problem Almost impossible to be addressed completely
Exposed Terminal Problem Easy to address
Unreachability Problem Possible, but indeed hard, to address.
- But, what are these problems?
Hidden Terminal Problem
In the same office, no more than one individual can aim for a girl.
Hidden Terminal Problem
A station which is unable to receive control/data frames of another station while can easily interfere to its data transmission is called a hidden terminal.
To reduce the impact of hidden terminal on the overall system performance, employing a four-way handshake technique known as RTS/CTS/DATA/ACK is recommended.
Exposed Terminal Problem
In the same office, multiple individuals may try to date with differentgirls, given that they do not interfere with each other.
Unreachability Problem
It is hard to date with a girl whom is being dominated by aninterfering entity, such as her demanding boss.
Unreachability Problem
When the destination is in the radio range of another transmitting station, most of the efforts on setting up communication with the destination will fail due to collision between transmitted control frames and undesired received control/data frames.
Unreachability problem becomes a bottleneck in data fragmentation scenarios.
Unreachability Problem: Type I
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Unreachability Problem: Type II
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Proposed Solution: eMAC
All stations are enforced to broadcast their one-hop neighbourhood information in the form of eMAC Tables.
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Proposed Solution: eMAC
Each station then knows everything about its double-hop neighbourhood; hence, we are only needed to solve the ICP broadcast storm.
We propose use of a p − persistent mechanism for ICP broadcasting in order to decreasethe probability of ICP collision.
Our proposed mechanism is totally topology aware, simple, and easy for implementation.
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Proposed Solution: eMAC
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Simulation Results
In our simulation study, 60 nodes are randomly placed in a 1000m × 300m area.
The source of each traffic flow randomly selects one station as the destination, which is with at least certain minimum hops away, i.e., 3 hops.
We assume that there are 20 traffic flows with the same CBR/UDP rate.
We use pre-computed shortest path with no routing overhead. All results are averaged over 50 random simulations.
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Simulation Results
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K. Ghaboosi, M. Latva-aho, Y. Xiao, and Q. Zhang, “eMAC – A Medium Access Control Protocol for the Next-Generation Ad Hoc Networks,” IEEE Trans. on Vehicular Technology, vol. 58, no. 8, October 2009, pp. 4476-4490
Part II:
MAC Protocols for Cognitive Radio Networks
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Cognitive Radio Concept &“Finnish Sauna”
We live in a building which has two saunas (resources).
We don’t sign up for the sauna to avoid paying the monthly fee (unlicensed).
To use the sauna, we first check (sense) one of the saunas. If it is free, we will invade; however, when a registeredneighbour (primary user) shows up, we quickly vacate the sauna.
We then check (sense) the next sauna (resource). If it is free, we will occupy it; otherwise, either we wait for any of the saunas to become free or we go outside and roll on the snow!!!
Cognitive Radios & Medium Access Control
Cognitive radio is known as a key solution to the spectrum scarcity in wireless access networks.
One of the primary goals of cognitive radio technology is to enable opportunistic spectrum access (OSA).
With respect to the above fundamental objective, MAC layer plays a key role in achieving efficient and reliable radio resource allocation.
Three major goals are attention-grabbing to be attained simultaneously: Distributed Channel Selection Distributed Load Balancing Multi-channel Contention Resolution
All the aforementioned aspects shall take into account coexistence with licensed primary users.
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Challenges & Open Issues
Multi-channel Hidden Terminal that happens when a device is operating on a channel and hence, is unable to listen to any other channels: Dual-transceiver architecture alleviates the impact of this
problem, but does not solve it completely. Few proposals in the literature try to solve this problem by
dividing time into an alternating sequence of control- and data exchange phases (e.g., MMAC and C-MAC) → Still low capacity due to control-phase saturation.
Multi-channel Unreachability that may happen on any channels, as well as due to either primary- or secondary users: No significant contribution in the literature.
But: What is multi-channel Unireachability problem? Is there any hope to re-use single-channel approaches in
multi-channel cognitive wireless networks?
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Multi-channel Unreachability Problem
It is even harder to date with multiple girls in different departmentswhom are dominated by their demanding bosses.
Stochastic Channel Selection Mechanism
Each data channel is tagged with a PU occupation probability pi with i = {1, 2, 3,…,m}.
Using probabilities pi a radio runs a probabilistic channel
selection mechanism to randomly choose one of the frequency opportunities.
It loads the designated counters of data channels with uniformly distributed integers taken from set {1, 2,…,W0}, where W0 is a pre-defined window size.
All counters within a station are driven by a common master clock. By each clock beat, the content of all counters is either decremented by one or remains unchanged.
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Stochastic Channel Selection Mechanism
Upon a clock beat the content of data channel i’s counter is decremented by one with probability 1− pi and remains unchanged with probability pi .
Data channel i will be chosen as the frequency opportunity
if its counter reaches zero before the counter of any other data channel. In such circumstances, counting down of other data channels’ counters is stopped and their contents remain unchanged until re-initiation of the probabilistic channel selection for the current frame transmission attempt becomes necessary.
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Stochastic Channel Selection Mechanism
Upon primary user appearance or another secondary user activity on the selected data channel while the backoff process on the common control channel is in progress, the cognitive station should resume the stochastic channel selection in order to randomly pick another data channel for the scheduled frame transmission.
In either of these cases, counting down of all data channels’ counters is continued from the point where it has been suspended upon conclusion of the previous channel selection attempt.
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Stochastic Channel Selection Mechanism
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Simulation Results
The average frame payload size is set to 1024 bytes.
Bit rate for each data channel is assumed to be 2 Mbps.
The transmission range of each station is approximately 250m and the capture threshold is set to 10 dB.
The beacon interval is set to 100 msec.
50 stations are randomly placed in a 1000 × 1000 m2 area.
There are 25 active traffic flows with the same CBR/UDP.
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Simulation Results
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Aggregate end-to-end throughput vs. total offered load: No primary user, 6 data channels.
Aggregate end-to-end throughput vs. total offered load: No primary user, 13 data channels.
Average frame end-to-end delay vs. total offered load: No primary user, 6 data channels.
Average frame end-to-end delay vs. total offered load: No primary user, 13 data channels.
Simulation Results
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Aggregate frame end-to-end throughput vs. total offered load: With primary user, 10 data channels.
Average frame end-to-end delay vs. total offered load: With primary user, 10 data channels.
K. Ghaboosi, A. B. MacKenzie, L. DaSilva, and M. Latva-aho, “Performance Analysis of Multi-channel Contention-basedMedium Access Control Protocols,” IEEE Trans. on Communications, Minor Revision
Implementation of Cognitive MAC Protocol
WARP is the platform on which our proposed cognitive MAC protocol is implemented.
We began the implementation by coding the so-called multi-channel cognitive backoff algorithm.
To handle multi-channel hidden terminal problem, a dual-transceiver architecture is required, however, we implemented the proposed scheme on a single-transceiver platform to observe the impact of lack of information regarding the neighbouring radios operation on other data communication channels.
The coding phase is almost completed and we are currently debugging the code while adding new features to the backoff counter/timers on the platform.
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Questions?
Thank You!