TY - GEN
T1 - Data-Driven Service Provisioning over Shared Spectrums with Statistical QoS Guarantee
AU - Li, Xuanheng
AU - Ding, Haichuan
AU - Pan, Miao
AU - Wang, Jie
AU - Zhang, Haixia
AU - Fang, Yuguang
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2019/4/1
Y1 - 2019/4/1
N2 - With the rapid growth on data traffic, spectrum shortage becomes increasingly serious, leading to the paradigm shift in spectrum usage from an exclusive mode to a sharing mode. However, how to utilize shared spectrums effectively for service provisioning is not straightforward due to its uncertain availability, known as spectrum uncertainty. In this paper, we propose a new metric to evaluate the achievable rate of a link on a share band under a confidence level, called probabilistic link capacity, which offers us an effective way to guarantee the quality of service statistically when using the shared spectrum for service delivery. Different from most existing works where the distributional information is explicitly given based on certain structural assumption, we develop a data-driven distributionally robust approach by using the first and second order statistical information. To achieve the result, we formulate it into a tractable semidefinite programming problem based on the worst-case of conditional-value-at-risk. Finally, as a use case, we design a service-based spectrum-aware transmission scheme, so that different kinds of spectrums (licensed and shared) can be efficiently utilized to satisfy the diverse service requirements.
AB - With the rapid growth on data traffic, spectrum shortage becomes increasingly serious, leading to the paradigm shift in spectrum usage from an exclusive mode to a sharing mode. However, how to utilize shared spectrums effectively for service provisioning is not straightforward due to its uncertain availability, known as spectrum uncertainty. In this paper, we propose a new metric to evaluate the achievable rate of a link on a share band under a confidence level, called probabilistic link capacity, which offers us an effective way to guarantee the quality of service statistically when using the shared spectrum for service delivery. Different from most existing works where the distributional information is explicitly given based on certain structural assumption, we develop a data-driven distributionally robust approach by using the first and second order statistical information. To achieve the result, we formulate it into a tractable semidefinite programming problem based on the worst-case of conditional-value-at-risk. Finally, as a use case, we design a service-based spectrum-aware transmission scheme, so that different kinds of spectrums (licensed and shared) can be efficiently utilized to satisfy the diverse service requirements.
KW - data-driven
KW - distributionally robust optimization
KW - service provisioning
KW - Spectrum sharing
KW - spectrum uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85074787000&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85074787000&origin=recordpage
U2 - 10.1109/WCNC.2019.8885666
DO - 10.1109/WCNC.2019.8885666
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781538676462
VL - 2019-April
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
PB - IEEE
T2 - 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
Y2 - 15 April 2019 through 19 April 2019
ER -