TY - GEN
T1 - Dynamic spectrum estimation with minimal overhead via multiscale information exchange
AU - Michelusi, Nicolo
AU - Nokleby, Matthew
AU - Mitra, Urbashi
AU - Calderbank, Robert
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - In this paper, a multiscale approach to spectrum sensing in cognitive cellular networks is analyzed. Observing that wireless interference decays with distance, and that estimating the entire spectrum occupancy across the network entails substantial energy cost and communication overhead, a protocol for distributed spectrum estimation is defined by which secondary users maintain fine-grained estimates of the spectrum occupancy of nearby cells, but coarse-grained estimates of that of distant cells. This is accomplished by arranging the cellular network into a hierarchy of increasingly coarser macro-cells and having secondary users fuse local spectrum estimates up the hierarchy. The spectrum occupancy is modeled as a Markov process, and the system is optimized by defining a probabilistic framework for spectrum sensing and information exchange that balances improvements in spectrum estimation against energy costs. The performance of the multiscale scheme is evaluated numerically, showing that it offers substantial improvements in energy efficiency over local estimation. On the other hand, it is shown that schemes that attempt to estimate the state of the whole network perform poorly, due to the excessive cost of performing information exchange with far away cells, and to the fact that, knowing the spectrum occupancy of distant cells, which experience low interference levels, results in a small increase in reward.
AB - In this paper, a multiscale approach to spectrum sensing in cognitive cellular networks is analyzed. Observing that wireless interference decays with distance, and that estimating the entire spectrum occupancy across the network entails substantial energy cost and communication overhead, a protocol for distributed spectrum estimation is defined by which secondary users maintain fine-grained estimates of the spectrum occupancy of nearby cells, but coarse-grained estimates of that of distant cells. This is accomplished by arranging the cellular network into a hierarchy of increasingly coarser macro-cells and having secondary users fuse local spectrum estimates up the hierarchy. The spectrum occupancy is modeled as a Markov process, and the system is optimized by defining a probabilistic framework for spectrum sensing and information exchange that balances improvements in spectrum estimation against energy costs. The performance of the multiscale scheme is evaluated numerically, showing that it offers substantial improvements in energy efficiency over local estimation. On the other hand, it is shown that schemes that attempt to estimate the state of the whole network perform poorly, due to the excessive cost of performing information exchange with far away cells, and to the fact that, knowing the spectrum occupancy of distant cells, which experience low interference levels, results in a small increase in reward.
UR - http://www.scopus.com/inward/record.url?scp=84964817483&partnerID=8YFLogxK
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U2 - 10.1109/GLOCOM.2014.7417532
DO - 10.1109/GLOCOM.2014.7417532
M3 - Conference contribution
AN - SCOPUS:84964817483
T3 - 2015 IEEE Global Communications Conference, GLOBECOM 2015
BT - 2015 IEEE Global Communications Conference, GLOBECOM 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th IEEE Global Communications Conference, GLOBECOM 2015
Y2 - 6 December 2015 through 10 December 2015
ER -