Optimal non-coherent data detection for massive SIMO wireless systems: A polynomial complexity solution
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
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Abstract© 2015 IEEE. This paper considers the joint maximum likelihood (ML) channel estimation and data detection problem for massive SIMO (single input multiple output) wireless systems. We propose efficient algorithms achieving the exact ML non-coherent data detection, for both constant-modulus constellations and nonconstant-modulus constellations. Despite a large number of unknown channel coefficients in massive SIMO systems, we show that the expected computational complexity is linear in the number of receive antennas and polynomial in channel coherence time. To the best of our knowledge, our algorithms are the first efficient algorithms to achieve the exact joint ML channel estimation and data detection performance for massive SIMO systems with general constellations. Simulation results show our algorithms achieve considerable performance gains at a low computational complexity.
CitationAlshamary HAJ, Al-Naffouri T, Zaib A, Xu W (2015) Optimal non-coherent data detection for massive SIMO wireless systems: A polynomial complexity solution. 2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE). Available: http://dx.doi.org/10.1109/DSP-SPE.2015.7369548.
Conference/Event nameIEEE Signal Processing and Signal Processing Education Workshop, SP/SPE 2015