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TitlePerformance analysis of the WiNC2R platform
NameSatarkar, Sumit (author), Trappe, Wade (chair), Gruteser, Marco (internal member), Raychaudhuri, Dipankar (internal member), Miljanic, Zoran (outside member), Rutgers University, Graduate School - New Brunswick,
Degree Date2009-10
Date Created2009
SubjectElectrical and Computer Engineering,
Cognitive radio networks
DescriptionA Cognitive Radio (CR) is an intelligent transceiver device, able to support multiple technologies, dynamic re-configurability, ease of programming and collaboration with other CR devices to improve the communication efficiency. The two key requirements for an efficient CR implementation are flexibility in operation/programming and speed.
WiNC2R (Winlab Network Centric Cognitive Radio) achieves high speed of operation using its hardware platform and flexibility using its software-configurable architecture. The current WiNC2R architecture implements an 802.11a-like OFDM flow. We evaluate the WiNC2R hardware architecture to see the modularity in the architecture, separation of data and control flow and the performance in terms of latency and throughput. To test the system, the Xilinx Bus Functional Model environment, which is designed to test the IBM standard bus-architecture-based hardware systems, is used. We use a simple ALOHA protocol in the MAC layer to communicate between two WiNC2R nodes and evaluate the performance under the best-case scenario, where the performance is only hindered by the architecture itself rather than external conditions like channel state.
The results of our basic experiments showed that for a single OFDM 802.11a-like flow, the Unit Control Modules (UCM) were idle for almost 80% of the total processing time.
We then tested the WiNC2R system to study the effects of changing the frame size. It was seen that the latencies in the WiNC2R transmitter are frame-size dependent while those in the receiver mainly depend on the size of the data in the last chunk rather than the size of the whole frame. We suggest that chunk size should be 2 OFDM symbols, and chunking be moved to MAC layer for better performance. We give analytical estimates of resulting performance improvement. In the next experiment, we describe virtualization in the WiNC2R by adding more flows. We describe the steps to implement the additional flows and estimate maximum number of concurrent flows possible.
In the last analysis, we show the effect of operating clock frequency on the performance. We prove that at 250 MHz operating frequency and 2 OFDM symbols per chunk, the current WiNC2R implementation will be able to satisfy the SIFS criterion.
WiNC2R (Winlab Network Centric Cognitive Radio) achieves high speed of operation using its hardware platform and flexibility using its software-configurable architecture. The current WiNC2R architecture implements an 802.11a-like OFDM flow. We evaluate the WiNC2R hardware architecture to see the modularity in the architecture, separation of data and control flow and the performance in terms of latency and throughput. To test the system, the Xilinx Bus Functional Model environment, which is designed to test the IBM standard bus-architecture-based hardware systems, is used. We use a simple ALOHA protocol in the MAC layer to communicate between two WiNC2R nodes and evaluate the performance under the best-case scenario, where the performance is only hindered by the architecture itself rather than external conditions like channel state.
The results of our basic experiments showed that for a single OFDM 802.11a-like flow, the Unit Control Modules (UCM) were idle for almost 80% of the total processing time.
We then tested the WiNC2R system to study the effects of changing the frame size. It was seen that the latencies in the WiNC2R transmitter are frame-size dependent while those in the receiver mainly depend on the size of the data in the last chunk rather than the size of the whole frame. We suggest that chunk size should be 2 OFDM symbols, and chunking be moved to MAC layer for better performance. We give analytical estimates of resulting performance improvement. In the next experiment, we describe virtualization in the WiNC2R by adding more flows. We describe the steps to implement the additional flows and estimate maximum number of concurrent flows possible.
In the last analysis, we show the effect of operating clock frequency on the performance. We prove that at 250 MHz operating frequency and 2 OFDM symbols per chunk, the current WiNC2R implementation will be able to satisfy the SIFS criterion.
NoteM.S.
NoteIncludes bibliographical references (p. 72-73)
Noteby Sumit Satarkar
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051905
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work