TY - GEN
T1 - Multi-bit cooperative spectrum sensing strategy in closed form
AU - Fan, Xiaoyuan
AU - Duan, Dongliang
AU - Yang, Liuqing
PY - 2013
Y1 - 2013
N2 - Spectrum sensing is one of the most important tasks in cognitive radio system. In order to combat fading, cooperation among different sensing users is usually adopted. In our previous work [1], we quantified the performance gain of cooperative spectrum sensing by the notion of diversity. In addition, we have shown that even with local binary decisions, the cooperative spectrum sensing can achieve the maximum diversity by appropriately selecting local and fusion rules. However, there is a significant signal-to-noise ratio (SNR) loss compared with the soft information fusion scenario due to local binary quantization. Intuitively, increasing the number of bits of local quantization will improve the sensing performance. Most work in the literature on multi-bit cooperative sensing are mathematically intractable and can only be solved numerically with high complexity. In this paper, by jointly maximizing diversity and SNR gain, we provide a generalized multi-bit cooperative sensing strategy with the local and fusion decision rules in explicit closed form. Simulations show that even with small number of bits, our proposed cooperative sensing strategy can significantly improve the sensing performance.
AB - Spectrum sensing is one of the most important tasks in cognitive radio system. In order to combat fading, cooperation among different sensing users is usually adopted. In our previous work [1], we quantified the performance gain of cooperative spectrum sensing by the notion of diversity. In addition, we have shown that even with local binary decisions, the cooperative spectrum sensing can achieve the maximum diversity by appropriately selecting local and fusion rules. However, there is a significant signal-to-noise ratio (SNR) loss compared with the soft information fusion scenario due to local binary quantization. Intuitively, increasing the number of bits of local quantization will improve the sensing performance. Most work in the literature on multi-bit cooperative sensing are mathematically intractable and can only be solved numerically with high complexity. In this paper, by jointly maximizing diversity and SNR gain, we provide a generalized multi-bit cooperative sensing strategy with the local and fusion decision rules in explicit closed form. Simulations show that even with small number of bits, our proposed cooperative sensing strategy can significantly improve the sensing performance.
UR - http://www.scopus.com/inward/record.url?scp=84901257792&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84901257792&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2013.6810540
DO - 10.1109/ACSSC.2013.6810540
M3 - Conference contribution
AN - SCOPUS:84901257792
SN - 9781479923908
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1473
EP - 1477
BT - Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PB - IEEE Computer Society
T2 - 2013 47th Asilomar Conference on Signals, Systems and Computers
Y2 - 3 November 2013 through 6 November 2013
ER -