Abstract
Interference alignment (IA) is an effective method that can eliminate interferences in wireless networks, and has been applied to spectrum sharing in cognitive radio (CR) networks recently. However, the availability of perfect network channel state information (CSI) is necessary for most existing IA schemes, which is not practical in general due to the realistic communication scenarios and deployment challenges. In this paper, we apply IA to cognitive relay networks under CSI mismatch where the variance of the CSI measurement error depends on signal-to-noise ratio (SNR). An adaptive Max-SINR IA algorithm has been introduced to improve the performance of the secondary network by using the knowledge of CSI error variance. Finally, we analyze the performance of the secondary network in terms of the end-to-end equivalent transmission rate and outage probability. Simulation results indicate that our proposed adaptive Max-SINR IA scheme can greatly improve the performance of the secondary network.
This work is supported by the National Natural Science Foundation of China (Nos. 61371122, 61471393, and 61501512), Jiangsu Provincial National Science Foundation (BK20150718) and China Postdoctoral Science Foundation under a Special Financial Grant (No. 2013T60912).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mitola, J.: Cognitive radio: an integrated agent architecture for software defined radio. Ph.D. dissertation, Royal Institute of Technology (KTH), Stockholm, Sweden (2000)
Akyildiz, I.F., Lee, W.-Y., Vuran, M.C., Mohanty, S.: Next generation dynamic spectrum access cognitive radio wireless networks: a survey. Comput. Netw. 50(13), 2127–2159 (2006)
Lee, K., Yener, A.: Outage performance of cognitive wireless relay networks. In: Proceedings of IEEE GLOBECOM, pp. 1–5 (2006)
Yan, Z., Wang, W., Zhang, X.: Exact outage performance of cognitive relay networks with maximum transmit power limits. IEEE Commun. Lett. 15(12), 1317–1319 (2011)
Zhang, X., Xing, J., Yan, Z., Gao, Y., Wang, W.: Outage performance study of cognitive relay networks with imperfect channel knowledge. IEEE Commun. Lett. 17(1), 27–30 (2013)
Jafar, S.A.: Interference alignment: a new look at signal dimensions in a communication network. Found. Trends Commun. Inf. Theory 7(1), 1–136 (2011)
Gomadam, K., Cadambe, V.R., Jafar, S.A.: A distributed numerical approach to interference alignment and applications to wireless interference networks. IEEE Trans. Inf. Theory 57(6), 3309–3322 (2011)
Makouei, B.N., Andrews, J.G., Heath, R.W.: MIMO interference alignment over correlated channels with imperfect CSI. IEEE Trans. Sig. Process. 59(6), 2783–2794 (2011)
Ayach, O.E., Heath, R.W.: Interference alignment with analog channel state feedback. IEEE Trans. Wirel. Commun. 11(2), 626–636 (2012)
Tresch, R., Guillaud, M.: Cellular interference alignment with imperfect channel knowledge. In: Proceedings of IEEE International Conference on Communications, pp. 1–5 (2009)
Razavi, S.M., Ratnarajah, T.: Performance analysis of interference alignment under CSI mismatch. IEEE Trans. Veh. Technol. 63(9), 4740–4748 (2014)
Blum, R.S.: MIMO capacity with interference. IEEE J. Sel. Areas Commun. 21(5), 793–801 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Yang, W., Zhang, T., Cai, Y., Wu, D. (2018). Interference Alignment in Cognitive Relay Networks Under CSI Mismatch. In: Chen, Q., Meng, W., Zhao, L. (eds) Communications and Networking. ChinaCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 209. Springer, Cham. https://doi.org/10.1007/978-3-319-66625-9_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-66625-9_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66624-2
Online ISBN: 978-3-319-66625-9
eBook Packages: Computer ScienceComputer Science (R0)