Optimal precoding for energy harvesting cognitive radio

Rui ZHU; Yunzhou LI; Jing WANG

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Journal of Tsinghua University(Science and Technology) ›› 2014, Vol. 54 ›› Issue (4) : 407-412.

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Optimal precoding for energy harvesting cognitive radio

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Abstract

Cognitive radio (CR) can effectively improve spectrum efficiencies while energy harvesting (EH) gives green communications. However, these methods have always been analyzed separately. The small amount of combined research has used the Gaussian input assumption. These drawbacks limit practical applications of combined systems. This study analyzed a combined system using the equip probability finite-alphabet input assumption which is more suitable for digital communication signals. A pre-coder algorithm was developed based on the stochastic dynamic program to improve the system utility. Numerical results show that the algorithm performance approaches the channel capacity upper bound for the combined system.

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cognitive radio / energy harvesting / stochastic dynamic program

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Rui ZHU,Yunzhou LI,Jing WANG. Optimal precoding for energy harvesting cognitive radio[J]. Journal of Tsinghua University(Science and Technology). 2014, 54(4): 407-412

References

[1]	Gastpr M. On capacity under receive and spatial spectrum-sharing constraints [J]. IEEE Trans Inf Theory, 2007, 53(2): 471-487.
[2]	Huang J, Berry R, Honig M L. Auction-based spectrum sharing[J]. ACM/Springer Mobile Networks and Applications Journal (MONET), 2006, 11(3): 405-418.
[3]	Yan Y, Huang J, Wang J. Dynamic bargaining for relay based cooperative spectrum sharing[J]. IEEE J Sel Areas Commun, 2013, 31(8):1480-1493.
[4]	Lu X, Erkip E, Wang Y. Power efficient multimedia communication over wireless channels[J]. IEEE J Sel Areas Commun., 2003, 21(5): 1738-1751.
[5]	Cui Q, Jantti R, Tao X. Energy-efficient relay selection and power allocation for two-way relay channel with analog network coding[J]. IEEE Communications Letters, 2012, 16(6):816-819
[6]	Ozel O, Ulukus S. Achieving AWGN capacity under stochastic energy harvesting[J]. IEEE Trans Inf Theory, 2012, 58(10): 6471-6483.
[7]	Ozel O, Tutuncuoglu K, Yang J. Transmission with energy harvesting nodes in fading wireless channels: Optimal policies[J]. IEEE J Sel Areas Commun, 2011, 29(8): 1732-1743.
[8]	Chin K, Zhang R. Optimal energy allocation for wireless communications with energy harvesting constraints[J]. IEEE Trans Signal Process, 2012, 60(9): 4808-4818.
[9]	Tutuncuoglu K, Yener A. Optimum transmission policies for battery limited energy harvesting nodes[J]. IEEE Trans Commun, 2012, 11(3): 1180-1189.
[10]	Guo D, Shamai S, Verdú S. Mutual information and minimum mean-square error in Gaussian channels[J]. IEEE Trans Inf Theory, 2005, 51(4): 1261-1282.
[11]	Cheng H, Zheng Y, Rosa M. Globally optimal linear precoders for finite alphabet signals over complex vector Gaussian channels[J]. IEEE Trans on signal processing, 2011, 59(7):3301-3314.
[12]	Zeng W, Xiao C, Lu J. Globally optimal precoder design with finite-alphabet input for cognitive radio networks[J]. IEEE Selected area in communications, 2012, 30(10): 1861-1874.
[13]	Zeng W, Xiao C, Wang M.et al.Linear precoding for finite- alphabet inputs over MIMO fading channels with statistical CSI[J]. IEEE Trans Signal Process, 2012, 60(6): 3134-3148.
[14]	Lozano A, Tulino A, Verdú S. Optimum power allocation for parallel Gaussian channels with arbitrary input distribu- tions[J]. IEEE Trans Inf Theory, 2006, 52(7): 3033-3051.