Ergodic capacity for fading channels in cognitive radio networks

In this paper, we consider a Cognitive Radio (CR) system where two type of users try to access to the primary spectrum : a primary user (PU) owning the spectrum license and a secondary user (SU) who does not own the spectrum license. However, the secondary communication is allowed to coexist with the primary communication as long as the interference caused by SU to PU is below a tolerable threshold. We study the optimization problem which maximizes the SU's achievable ergodic capacity under different types of power constraints and for different fading channel models. Our goal is to calculate the optimal power allocation strategies for these optimization problems. We show that modelling with Rayleigh fading for the channel between SU transmitter and PU receiver is an advantageous way to ameliorate the SU ergodic capacity. Furthermore, we consider four combinations of power constraints, since the interference power constraint and the transmit power constraint can be restricted by a peak or an average threshold. We also show that the SU ergodic capacity under average transmit power constraint and average interference power constraint outperforms the one with peak power constraints. In this case, we propose a novel decoupling method. Our method reduces the complexity of the initial problem and makes our initial problem easier to solve.

[1]  Danijela Cabric,et al.  Cognitive Radio Spectrum-Sharing Technology , 2007 .

[2]  Inbar Fijalkow,et al.  A unifying view on energy-efficiency metrics in cognitive radio channels , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

[3]  Raouia Masmoudi Power Allocation Problem for Fading Channels in Cognitive Radio Networks , 2018, 2018 15th International Multi-Conference on Systems, Signals & Devices (SSD).

[4]  Ying-Chang Liang,et al.  Optimal Power Allocation Strategies for Fading Cognitive Radio Channels with Primary User Outage Constraint , 2011, IEEE Journal on Selected Areas in Communications.

[5]  Yonghong Zeng,et al.  Sensing-Throughput Tradeoff for Cognitive Radio Networks , 2008, IEEE Transactions on Wireless Communications.

[6]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[7]  Norman C. Beaulieu,et al.  Energy-Efficient Optimal Power Allocation for Fading Cognitive Radio Channels: Ergodic Capacity, Outage Capacity, and Minimum-Rate Capacity , 2016, IEEE Transactions on Wireless Communications.

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

[9]  Rui Zhang,et al.  On peak versus average interference power constraints for protecting primary users in cognitive radio networks , 2008, IEEE Transactions on Wireless Communications.

[10]  Mohammed Hawa,et al.  Distributed opportunistic spectrum sharing in cognitive radio networks , 2017, Int. J. Commun. Syst..

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

[12]  Sonia Aïssa,et al.  Ergodic and Outage Capacities of Spectrum-Sharing Systems in Fading Channels , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[13]  Inbar Fijalkow,et al.  A closed-form solution to the power minimization problem over two orthogonal frequency bands under QoS and Cognitive Radio interference constraints , 2012, 2012 IEEE International Symposium on Dynamic Spectrum Access Networks.

[14]  Inbar Fijalkow,et al.  Efficient spectrum scheduling and power management for opportunistic users , 2016, EURASIP J. Wirel. Commun. Netw..

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

[16]  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.

[17]  Tho Le-Ngoc,et al.  QoS-based power allocation for cognitive radios with AMC and ARQ in Nakagami-m fading channels , 2016, Trans. Emerg. Telecommun. Technol..

[18]  Amir Ghasemi,et al.  Fundamental limits of spectrum-sharing in fading environments , 2007, IEEE Transactions on Wireless Communications.

[19]  Jon M. Peha,et al.  Approaches to spectrum sharing , 2005, IEEE Communications Magazine.