Back
 IJCNS  Vol.4 No.12 A , December 2011
LDPC-Coded OFDM Transmission Based on Adaptive Power Weights in Cognitive Radio Systems
Seyed Eman Mahmoodi, Bahman Abolhassani
Abstract: In this paper, we propose a new scheme to improve the performance of an LDPC-coded OFDM based cognitive radio (CR) link by applying adaptive power weights. To minimize estimation errors of detected signals in all the CR subcarriers, power weights are allocated to the CR subcarriers at the secondary transmitter. Some constraints for the power weights are considered, such as keeping the interference power introduced by the CR to primary users below a given interference threshold and also keeping sum of transmission powers in all CR subcarriers within a total transmission power. The LDPC decoder applies these power weights in the Log Likelihood Ratios (LLRs) used in message passing scheme at the secondary receiver to achieve more reliable communications. So, the received signal in each CR subcarrier will be decoded with the knowledge of transmission power weights, which come from the cognitive feedback channel without additional cost. Simulation results demonstrate that our proposed scheme achieves a lower bit error rate and a higher transmission rate compared with those of the same scheme without applying power weights.
Keywords: Cognitive Radio, OFDM, LDPC, Interference, Power Weighting
Cite this paper: nullS. Mahmoodi and B. Abolhassani, "LDPC-Coded OFDM Transmission Based on Adaptive Power Weights in Cognitive Radio Systems," International Journal of Communications, Network and System Sciences, Vol. 4 No. 12, 2011, pp. 761-769. doi: 10.4236/ijcns.2011.432094.
References

[1]   S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications,” IEEE Journal on Selected Areas in Communications, Vol. 23, No. 2, 2005, pp. 201-220. doi:10.1109/JSAC.2004.839380

[2]   T. Weiss and F. K. Jondral, “Spectrum Pooling: An Innovative Strategy for the Enhancement of Spectrum Efficiency,” IEEE Communications Magazine, Vol. 43, No.3, 2004, pp. S8-S14. doi:10.1109/MCOM.2004.1273768

[3]   G. Lechner, K. D. Nguyen, G. Fabregas and L. K. Rasmussen, “Optimal Power Control for LDPC Codes in Block-Fading Channels,” IEEE Transactions on Communications, Vol. 59, No. 7, 2011, pp. 1759-1765. doi:10.1109/TCOMM.2011.051311.090238

[4]   H. Futaki and T. Ohtsuki, “Performance of Low-Density Parity-Check (LDPC) Coded OFDM Systems,” IEEE International Conference on Communications (ICC), Vol. 3, 2002, pp. 1696-1700. doi:10.1109/ICC.2002.997138

[5]   M. Jiang, C. Zhao, E. Xu and L. Zhang, “Reliability-Based Iterative Decoding of LDPC Codes Using Likeli- hood Accumulation,” IEEE Communications Letters, Vol. 11, No. 8, 2007, pp. 677-679. doi:10.1109/LCOMM.2007.070450

[6]   J. Lei, R. Yates, P. Spasojevic and L. Greenstein, “Cooperative Sensing of Primary Users in Cognitive Radio Networks Based on Message Passing,” 43th Annual Conference on Information Sciences and Systems (CISS), Baltimore, 18-20 March 2009, pp. 568-573. doi:10.1109/CISS.2009.5054784

[7]   A. Baker, S. Soumik Ghosh, A. Kumar, and M. Bayoumi, “LDPC Decoder: A Cognitive Radio Perspective for Next Generation (XG) Communication,” IEEE Circuits and Systems Magazine, Vol. 7, No. 3, 2007, pp. 24-37. doi:10.1109/MCAS.2007.904180

[8]   B. Lu, Y. Guosen and W. Xiaodong, “Performance Analysis and Design Optimization of LDPC-coded MIMO OFDM Systems,” IEEE Transactions on Signal Processing, Vol. 52 , No. 2, 2004, pp. 348-361.

[9]   Y. Li and W. E. Ryan, “Mutual-Information-Based Adaptive Bit-Loading Algorithms for LDPC-Coded OFDM,” IEEE Transactions on Wireless Communications, Vol. 6, No. 5, 2007, pp. 1670-1680. doi:10.1109/TWC.2007.360369

[10]   A. Jovicic and P. Viswanath, “Cognitive Radio: An Information-Theoretic Perspective,” IEEE Transactions on Information Theory, Vol. 55, No. 9, 2009, pp. 3945-3958.

[11]   W. Lingfan, E. K. S. Au, P. W. C. Chan, R. D. Murch, R. S. Cheng, H. M. Wai and V. K. N. Lau, “Effect of Carrier Frequency Offset on Channel Estimation for SISO/MIMO OFDM Systems,” IEEE Transactions on Wireless Communications. Vol. 6, No. 5, 2007, pp. 1854-1863. doi:10.1109/TWC.2007.360387

[12]   S. E. Mahmoodi and B. Abolhassani, “Two New Power Allocation Schemes for an OFDM Cognitive Radio with No Knowledge on Primary Users’ Interference,” submitted to the International Journal of Communication Systems, 2011.

[13]   T. Weiss, J. Hillenbrand, A. Krohn and F. K. Jondral, “Mutual Interference in OFDM-based Spectrum Pooling Systems,” Proceeding of IEEE 59th Vehicular Technology Conference, Milan, 17-19 May 2004, pp. 1873-1877.

[14]   S. Boyd and L. Vandenberghe, “Convex Optimization,” Cambridge University Press, Cambridge, 2004.

[15]   G. Bansal, M. J. Hossain and V. K. Bhargava, “Optimal and Suboptimal Power Allocation Algorithms for OFDM-Based Cognitive Radio Systems,” IEEE Transaction on Wireless Communications, Vol. 7, No. 11, 2008, pp. 4710- 4718. doi:10.1109/T-WC.2008.07091

[16]   S. Xiangran and Sh. Dongxin, “Design and Optimization of LDPC Encoder Based on LU Decomposition with Simulated Annealing,” International Conference on Computer Science and Service System (CSSS), Nanjing, 27-29 June 2011, pp. 2181-2184. doi:10.1109/CSSS.2011.5974805

 
 
Top