Power allocation policies with full and partial inter-system channel state information for cognitive radio networks

This paper investigates several power allocation policies in orthogonal frequency division multiplexing -based cognitive radio networks under the different availability of inter-system channel state information (CSI) and the different capability of licensed primary users (PUs). Specifically, we deal with two types of PUs having different capabilities: a dumb (peak interference-power tolerable) PU and a more sophisticated (average interference-power tolerable) PU. For such PU models, we first formulate two optimization problems that maximize the capacity of unlicensed secondary user (SU) while maintaining the quality of service of PU under the assumption that both intra- and inter-system CSI are fully available. However, due to loose cooperation between SU and PU, it may be difficult or even infeasible for SU to obtain the full inter-system CSI. Thus, under the partial inter-system CSI setting, we also formulate another two optimization problems by introducing interference-power outage constraints. We propose optimal and efficient suboptimal power allocation policies for these four problems. Extensive numerical results demonstrate that the spectral efficiency achieved by SU with partial inter-system CSI is less than half of what is achieved with full inter-system CSI within a reasonable range of outage probability (e.g., less than 10 %). Further, it is shown that the average interference-power tolerable PU can help to increase the saturated spectral efficiency of SU by about 20 and 50 % in both cases of full and partial inter-system CSI, respectively.

[1]  Leila Musavian,et al.  Fundamental capacity limits of cognitive radio in fading environments with imperfect channel information , 2009, IEEE Transactions on Communications.

[2]  Bang Chul Jung,et al.  Opportunistic Underlay Transmission in Multi-Carrier Cognitive Radio Systems , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[3]  Ying-Chang Liang,et al.  Joint Beamforming and Power Allocation for Multiple Access Channels in Cognitive Radio Networks , 2008, IEEE Journal on Selected Areas in Communications.

[4]  Daniel Pérez Palomar,et al.  Practical algorithms for a family of waterfilling solutions , 2005, IEEE Transactions on Signal Processing.

[5]  Theodore Antonakopoulos,et al.  Bit and Power Allocation in Constrained Multicarrier Systems: The Single-User Case , 2008, EURASIP J. Adv. Signal Process..

[6]  Yan Xin,et al.  Robust cognitive beamforming with partial channel state information , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.

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

[8]  John M. Cioffi,et al.  Understanding Digital Subscriber Line Technology , 1999 .

[9]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[10]  John M. Cioffi,et al.  Impact of imperfect channel knowledge on the performance of multicarrier systems , 1998, IEEE GLOBECOM 1998 (Cat. NO. 98CH36250).

[11]  Abhay Parekh,et al.  Spectrum sharing for unlicensed bands , 2005, IEEE Journal on Selected Areas in Communications.

[12]  B. Gnedenko,et al.  Limit Distributions for Sums of Independent Random Variables , 1955 .

[13]  Gordon L. Stuber,et al.  Uplink Resource Allocation in Cognitive Radio Networks with Imperfect Spectrum Sensing , 2010 .

[14]  Georgios B. Giannakis,et al.  Rate-maximizing power allocation in OFDM based on partial channel knowledge , 2003, IEEE Transactions on Wireless Communications.

[15]  Bang Chul Jung,et al.  Power Allocation for OFDM-Based Cognitive Radio Systems under Outage Constraints , 2010, 2010 IEEE International Conference on Communications.

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

[17]  Adam Wolisz,et al.  COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Frequency Hopping Communities for Efficient IEEE 802.22 Operation , 2007, IEEE Communications Magazine.

[18]  S. Srinivasa,et al.  The Throughput Potential of Cognitive Radio: A Theoretical Perspective , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[19]  Dusit Niyato,et al.  Competitive spectrum sharing in cognitive radio networks: a dynamic game approach , 2008, IEEE Transactions on Wireless Communications.

[20]  Yiwei Thomas Hou,et al.  Toward secure distributed spectrum sensing in cognitive radio networks , 2008, IEEE Communications Magazine.

[21]  Kwang-Cheng Chen,et al.  Radio Resource Allocation in OFDMA Cognitive Radio Systems , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[22]  Pin-Han Ho,et al.  An Efficient Power Allocation Algorithm for OFDM Based Underlay Cognitive Radio Networks , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[23]  Khaled Fazel,et al.  Multi-Carrier and Spread Spectrum Systems , 2003 .

[24]  Abbas Jamalipour,et al.  Mean-Variance Based QoS Management in Cognitive Radio , 2010, IEEE Transactions on Wireless Communications.

[25]  Hüseyin Arslan,et al.  A survey of spectrum sensing algorithms for cognitive radio applications , 2009, IEEE Communications Surveys & Tutorials.

[26]  Ieee Microwave Theory,et al.  Part 16: Air Interface for Fixed and Mobile Broadband Wireless Access Systems — Amendment for Physical and Medium Access Control Layers for Combined Fixed and Mobile Operation in Licensed Bands , 2003 .

[27]  Patrick Mitran,et al.  Achievable rates in cognitive radio channels , 2006, IEEE Transactions on Information Theory.

[28]  Gordon L. Stüber,et al.  Uplink Resource Allocation in Cognitive Radio Networks with Imperfect Spectrum Sensing , 2010, 2010 IEEE 72nd Vehicular Technology Conference - Fall.

[29]  Syed Ali Jafar,et al.  COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - The Throughput Potential of Cognitive Radio: A Theoretical Perspective , 2007, IEEE Communications Magazine.

[30]  Joseph Mitola,et al.  Cognitive Radio An Integrated Agent Architecture for Software Defined Radio , 2000 .

[31]  Vijay K. Bhargava,et al.  Optimal and Suboptimal Power Allocation Schemes for OFDM-based Cognitive Radio Systems , 2008, IEEE Transactions on Wireless Communications.

[32]  H.-H. Chen,et al.  Optimal distributed joint frequency, rate and power allocation in cognitive OFDMA systems , 2008, IET Commun..

[33]  Joseph Mitola An Integrated Agent Architecture for Software Defined Radio , 2000 .

[34]  Ying-Chang Liang,et al.  Optimal power allocation for OFDM-based cognitive radio with new primary transmission protection criteria , 2010, IEEE Transactions on Wireless Communications.

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

[36]  K. Fazel,et al.  Multi-Carrier and Spread Spectrum Systems: Fazel/Spread Spectrum , 2004 .

[37]  Hongbo Zhu,et al.  Channel capacity analysis of spectrum-sharing with imperfect channel sensing , 2009, 2009 Fourth International Conference on Communications and Networking in China.

[38]  Chunyan Miao,et al.  Resource Allocation in MU-OFDM Cognitive Radio Systems with Partial Channel State Information , 2010, EURASIP J. Wirel. Commun. Netw..