TY - JOUR
T1 - Multiband spectrum sensing in cognitive radio networks with secondary user hardware limitation
T2 - Random and adaptive spectrum sensing strategies
AU - Xiong, Tianyi
AU - Yao, Yu Dong
AU - Ren, Yujue
AU - Li, Zan
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/5
Y1 - 2018/5
N2 - Hardware limitation at the secondary user (SU) terminal makes multiband (wideband) spectrum sensing more challenging. This paper considers spectrum sensing under SU hardware limitation, where the SU can only sense a small portion of the multiband spectrum for a given time period. This introduces a design issue of selecting channels to sense at a given time. A random spectrum sensing strategy (RSSS) is presented to select the subchannels to sense in a totally random fashion. Considering the Markov property of the state transition of a primary user (PU), an adaptive spectrum sensing strategy (ASSS) is then proposed to take advantage of the PU traffic patterns in determining the subchannels to sense. In the proposed ASSS, a novel decision rule is designed and two decision combinations are obtained. The ASSS decision rule adaptively selects a decision combination to determine the subchannels to sense for SU such that the selected subchannels are more likely to be available for the SU network. A metric called spectrum sensing capability (SSC) is defined to evaluate the performance of any spectrum sensing strategies. The SSC expressions for both RSSS and ASSS are derived. Numerical results show significant performance gain of ASSS as compared to RSSS.
AB - Hardware limitation at the secondary user (SU) terminal makes multiband (wideband) spectrum sensing more challenging. This paper considers spectrum sensing under SU hardware limitation, where the SU can only sense a small portion of the multiband spectrum for a given time period. This introduces a design issue of selecting channels to sense at a given time. A random spectrum sensing strategy (RSSS) is presented to select the subchannels to sense in a totally random fashion. Considering the Markov property of the state transition of a primary user (PU), an adaptive spectrum sensing strategy (ASSS) is then proposed to take advantage of the PU traffic patterns in determining the subchannels to sense. In the proposed ASSS, a novel decision rule is designed and two decision combinations are obtained. The ASSS decision rule adaptively selects a decision combination to determine the subchannels to sense for SU such that the selected subchannels are more likely to be available for the SU network. A metric called spectrum sensing capability (SSC) is defined to evaluate the performance of any spectrum sensing strategies. The SSC expressions for both RSSS and ASSS are derived. Numerical results show significant performance gain of ASSS as compared to RSSS.
KW - Adaptive spectrum sensing
KW - Markov model
KW - channel selection
KW - cognitive radio
KW - multiband spectrum sensing
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U2 - 10.1109/TWC.2018.2805729
DO - 10.1109/TWC.2018.2805729
M3 - Article
AN - SCOPUS:85042199513
SN - 1536-1276
VL - 17
SP - 3018
EP - 3029
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 5
ER -