Achievable Rate of Multi-relay Cognitive Radio MIMO Channel with Space Alignment
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We study the impact of multiple relays on the primary user (PU) and secondary user (SU) rates of underlay MIMO cognitive radio. Both users exploit amplify-and-forward relays to communicate with the destination. A space alignment technique and a special linear precoding and decoding scheme are applied to allow the SU to use the resulting free eigenmodes. In addition, the SU can communicate over the used eigenmodes under the condition of respecting an interference constraint tolerated by the PU. At the destination, a successive interference cancellation (SIC) is performed to estimate the secondary signal. We present the explicit expressions of the optimal PU and SU powers that maximize their achievable rates. In the numerical results, we show that our scheme provides cognitive rate gain even in absence of tolerated interference. In addition, we show that increasing the number of relays enhances the PU and SU rates at low power regime and/or when the relays power is sufficiently high.
KeywordsUnderlay cognitive radio MIMO space alignment Amplify-and-forward multiple-relay
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- 1.Spectrum policy task force. Federal Communications Commission, Tech. Rep. ET Docket no. 02–135, November 2002Google Scholar
- 5.Sboui, L., Ghazzai, H., Rezki, Z., Alouini, M.-S.: Achievable rate of cognitive radio spectrum sharing MIMO channel with space alignment and interference temperature precoding. In: Proc. of the IEEE International Conference on Communications (ICC 2013), Budapest, Hungary, pp. 2656–2660, June 2013Google Scholar
- 6.Perlaza, S., Debbah, M., Lasaulce, S., Chaufray, J.-M.: Opportunistic interference alignment in MIMO interference channels. In: Proc. of the 19th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2008), Cannes, France, September 2008Google Scholar
- 7.Kang, X., Liang, Y.-C., Nallanathan, A.: Optimal power allocation for fading channels in cognitive radio networks under transmit and interference power constraints. In: Proc. of the IEEE International Conference on Communications (ICC 2008), Beijing, China, pp. 3568–3572, May 2008Google Scholar
- 10.Naeem, M., Lee, D., Pareek, U.: An efficient multiple relay selection scheme for cognitive radio systems. In: IEEE International Conference on Communications Workshops (ICC), Cape Town, South Africa, pp. 1–5 (2010)Google Scholar
- 11.Sboui, L., Ghazzai, H., Rezki, Z., Alouini, M.-S.: On the throughput of a Relay-Assisted cognitive radio MIMO channel with space alignment. In: 12th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt 2014), Hammamet, Tunisia, pp. 317–323, May 2014Google Scholar
- 14.Popovski, P., Yomo, H., Nishimori, K., Di Taranto, R., Prasad, R.: Opportunistic interference cancellation in cognitive radio systems. In: Proc. of the 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2007), Dublin, Ireland, pp. 472–475, April 2007Google Scholar
- 15.Qingyu, M., Osseiran, A., Gan, J.: MIMO amplify-and-forward relaying: spatial gain and filter matrix design. In: Proc. IEEE International Conference on Communications Workshops (ICC Workshops 2008), Beijing, China (2008)Google Scholar
- 17.Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press (2004)Google Scholar