Performance analysis of receive diversity under time-varying and spatially correlated channels using partial CSI
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In this paper, a single input multiple output system is considered with L receive antennas and the underlying channels are assumed to be time varying with temporal correlation coefficient a and spatially correlated with correlation coefficient \(\rho \). Further, the channel is assumed to be identically distributed using Rayleigh fading channels and characterized by first order autoregressive model. For the detection, we assume partial channel state information (CSI) available at the receiver. The partial CSI is in the form of a known preamble (one symbol) only before beginning of a frame of size N symbols. Further, the preamble is imperfectly known with a variance of error \(\sigma _e^2\). For the assumed system, closed form expressions of symbol error rate (SER) are derived for M-PSK and M-QAM constellations under the compound effect of spatially correlated channels, temporally correlated channels and partial CSI at the Receiver. The derived expressions are functions of average SNR per symbol, \(\rho \), a, \(\sigma _e^2\), N, L and modulation order M. Further, these expressions are reduced for some special cases and compared with prevailing results in literature. The analytical expressions are also validated by comparing them with the corresponding simulation results. The derived expressions are very useful to select N, L and M to overcome the deterioration in SER due to adverse effects of \(\rho \), a and \(\sigma _e^2\).
KeywordsAutoregressive process Partial CSIR Spatial correlation Time varying channel SIMO
The authors would like to thank Mr. Saket Buch, Space Applications Centre, ISRO for his critical review of this work.
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Conflicts of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
- 1.Abeysinghe, J.R., & Roberts, J.A. (1995). Bit error rate performance of antenna diversity systems with channel correlation. In Proceedings of GLOBECOM.Google Scholar
- 6.Anvar, S. M. M., Khanmohammadi, S., & Museviniya., Javad. (2015). Game theoretic power allocation for fading MIMO multiple access channels with imperfect CSIR. Telecommunication Systems, 61(4), 875–886.Google Scholar
- 11.Trivedi, Y. N., & Chaturvedi, A. K. (2007). Application of Receive Diversity to Rapidly Time Varying Channels with Partial Knowledge at the Receiver. Mumbai: NCC, IIT.Google Scholar
- 12.Trivedi, Y. N., & Chaturvedi, A. K. (2009). Detection in Time-Varying Wireless Channels Using Partial Channel State Information. Guwahati: NCC, IIT.Google Scholar
- 16.Perahia, E., & Pottie, G. J. (1994). On diversity combining for correlated slowly flat-fading Rayleigh channels. In Proceedings of ICC/SUPERCOMM.Google Scholar
- 17.Jakes, W. C., & Cox, D. C. (Eds.). (1994). Microwave Mobile Communications. New York: Wiley-IEEE Press.Google Scholar
- 18.Kulkarni, M., Choudhary, L., Kumbhani, B., & Kshetrimayum, R. S. (2014). Performance analysis comparison of transmit antenna selection with maximum ratio combining and orthogonal space time block codes in equicorrelated Rayleigh fading multiple input multiple output channels. IET Communications, 8(10), 1850–1858.CrossRefGoogle Scholar
- 19.Proakis, J . G. (2001). Digital Communications (4th ed.). New York: McGraw Hill.Google Scholar
- 20.WolframAlpha Online Integral Calculator. [Online]. www.wolframalpha.com/calculators/integral-calculator.Google Scholar
- 21.Gradshteyn, I . S., & Ryzhik, I . M. (2007). Table of Integrals, Series, and Products (7th ed.). Cambridge: Academic press.Google Scholar