2019
Tsitseklis, K.; Kakkavas, G.; Karyotis, V.; Papavassiliou, S.
A Realistic Evaluation of MRF-based Resource Allocation for SDR Cognitive Radio Networks Conference
vol. 2019-October, IEEE Computer Society, 2019, ISBN: 9781728110288, (cited By 0; Conference of 44th Annual IEEE Conference on Local Computer Networks, LCN 2019 ; Conference Date: 14 October 2019 Through 17 October 2019; Conference Code:157724).
Abstract | Links | BibTeX | Tags: Cognitive radio, Cognitive radio network; Cross-layer design; Distributed computations; Experimental evaluation; Parallel implementations; Research and development; Software defined radio technologies; Software-defined radios, Computer networks; Magnetorheological fluids; Markov processes; Open source software; Radio; Radio receivers; Radio systems; Resource allocation; Software radio; Structural frames; Testbeds
@conference{Tsitseklis2019185,
title = {A Realistic Evaluation of MRF-based Resource Allocation for SDR Cognitive Radio Networks},
author = {K. Tsitseklis and G. Kakkavas and V. Karyotis and S. Papavassiliou},
editor = {Oteafy S. Tan H.-P. Andersson K.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080939926&doi=10.1109%2fLCN44214.2019.8990725&partnerID=40&md5=5ece1109bea717561dba60bfdc872500},
doi = {10.1109/LCN44214.2019.8990725},
isbn = {9781728110288},
year = {2019},
date = {2019-01-01},
journal = {Proceedings - Conference on Local Computer Networks, LCN},
volume = {2019-October},
pages = {185-192},
publisher = {IEEE Computer Society},
abstract = {In this paper, we focus on the development and realistic evaluation of a resource allocation approach for cognitive radios implemented with Software Defined Radio (SDR) technology over two testbeds of the ORCA federation. Our cross-layer approach is based on a Markov Random Field (MRF) framework realizing a distributed computation among the secondary nodes of cognitive radios. This is the first implementation and real experimental evaluation of such a mechanism. New SDR functions for implementing various cognitive radio functionalities, such as spectrum sensing, distributed node synchronization, etc., were developed in GNU Radio from scratch. We demonstrated the feasibility of the MRF-based resource allocation approach and quantified various performance metrics of interest, such as allocation fairness and collision percentage. Through this development, several design principles of broader interest for SDR emerged (e.g., for spectrum sensing and collision detection design), while salient features of our framework requiring further research and development were discovered (e.g., need for parallel implementation). © 2019 IEEE.},
note = {cited By 0; Conference of 44th Annual IEEE Conference on Local Computer Networks, LCN 2019 ; Conference Date: 14 October 2019 Through 17 October 2019; Conference Code:157724},
keywords = {Cognitive radio, Cognitive radio network; Cross-layer design; Distributed computations; Experimental evaluation; Parallel implementations; Research and development; Software defined radio technologies; Software-defined radios, Computer networks; Magnetorheological fluids; Markov processes; Open source software; Radio; Radio receivers; Radio systems; Resource allocation; Software radio; Structural frames; Testbeds},
pubstate = {published},
tppubtype = {conference}
}
In this paper, we focus on the development and realistic evaluation of a resource allocation approach for cognitive radios implemented with Software Defined Radio (SDR) technology over two testbeds of the ORCA federation. Our cross-layer approach is based on a Markov Random Field (MRF) framework realizing a distributed computation among the secondary nodes of cognitive radios. This is the first implementation and real experimental evaluation of such a mechanism. New SDR functions for implementing various cognitive radio functionalities, such as spectrum sensing, distributed node synchronization, etc., were developed in GNU Radio from scratch. We demonstrated the feasibility of the MRF-based resource allocation approach and quantified various performance metrics of interest, such as allocation fairness and collision percentage. Through this development, several design principles of broader interest for SDR emerged (e.g., for spectrum sensing and collision detection design), while salient features of our framework requiring further research and development were discovered (e.g., need for parallel implementation). © 2019 IEEE.