Continuous Power Allocation Strategies for Sensing-Based Multiband Spectrum Sharing

We propose continuous power allocation strategies for secondary users (SUs) based on sensing the primary user (PU) channels in a multiband cognitive radio (CR) network. Unlike the conventional sensing-based spectrum sharing, where there are two transmit power levels corresponding to whether the PU is sensed present or not, in the proposed strategy, the power levels are continuous functions of the sensing statistics, and optimized with respect to the achievable rate of the SU. The continuous power allocation function is parameterized by some channel parameters of the PU and SU, and we treat the cases of perfect and quantized channel state information (CSI) separately, where the former provides an upper bound on the achievable rate with full channel information; and the latter constitutes an efficient practical power allocation method for the SU with statistic/partial channel information. The power control process consists of two phases: in the first phase, the SU listens to the multiple bands licensed to the PU and obtains the sensing statistics, e.g., the received signal energies on these bands; in the second phase, the SU adjusts its transmit power levels on these bands based on the sensing results. Optimal power allocation schemes are derived to maximize the achievable rate at the SU under several possible combinations of the peak/average transmit power constraints at the SU and the peak/average interference power constraints at the PU. Simulation results demonstrate that the proposed strategies can significantly improve the achievable throughput of the SU compared to the conventional methods.

[1]  Arkadi Nemirovski,et al.  Lectures on modern convex optimization - analysis, algorithms, and engineering applications , 2001, MPS-SIAM series on optimization.

[2]  Lutz H.-J. Lampe,et al.  Distributed transmit power allocation for multihop cognitive-radio systems , 2009, IEEE Transactions on Wireless Communications.

[3]  Yuanan Liu,et al.  Power Allocation Over Fading Cognitive MIMO Channels: An Ergodic Capacity Perspective , 2012, IEEE Transactions on Vehicular Technology.

[4]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[5]  Arumugam Nallanathan,et al.  On the Throughput and Spectrum Sensing Enhancement of Opportunistic Spectrum Access Cognitive Radio Networks , 2012, IEEE Transactions on Wireless Communications.

[6]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[7]  Yiyang Pei,et al.  How much time is needed for wideband spectrum sensing? , 2009, IEEE Transactions on Wireless Communications.

[8]  Yonghong Zeng,et al.  Sensing-Throughput Tradeoff for Cognitive Radio Networks , 2008, IEEE Trans. Wirel. Commun..

[9]  Ying-Chang Liang,et al.  Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity , 2008, IEEE Transactions on Wireless Communications.

[10]  Geoffrey Ye Li,et al.  Probabilistic Resource Allocation for Opportunistic Spectrum Access , 2010, IEEE Transactions on Wireless Communications.

[11]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[12]  Vincent K. N. Lau,et al.  On the design of MIMO block-fading channels with feedback-link capacity constraint , 2004, IEEE Transactions on Communications.

[13]  Chintha Tellambura,et al.  Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity Under Fading Channels in Cognitive Radio Networks , 2010, IEEE Transactions on Signal Processing.

[14]  Hai Jiang,et al.  Joint Optimal Cooperative Sensing and Resource Allocation in Multichannel Cognitive Radio Networks , 2011, IEEE Transactions on Vehicular Technology.

[15]  Arumugam Nallanathan,et al.  Optimal Sensing Time and Power Allocation in Multiband Cognitive Radio Networks , 2010 .

[16]  Sonia Aïssa,et al.  Capacity and power allocation for spectrum-sharing communications in fading channels , 2009, IEEE Transactions on Wireless Communications.

[17]  Ying-Chang Liang,et al.  Sensing-Based Spectrum Sharing in Cognitive Radio Networks , 2008, IEEE Transactions on Vehicular Technology.

[18]  Geoffrey Ye Li,et al.  Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[19]  Gi-Hong Im,et al.  Joint Sensing Adaptation and Resource Allocation for Cognitive Radio with Imperfect Sensing , 2012, IEEE Transactions on Communications.