Abstract
This paper investigates pilot and data power allocation for a multi-cell spatially correlated massive multiple-input multiple-output (MIMO) system with imperfect channel state information (CSI). By exploiting the availability of statistical CSI, the uplink closed-form spectral efficiency (SE) expressions are derived for both full covariance knowledge case and no prior statistical information case. In order to enhance the accuracy of channel estimation, novel pilot power allocation schemes are firstly designed by minimizing the sum normalized mean square error (NMSE) of all users. Then, based on the optimal pilot power, data power allocation schemes are proposed to maximize the sum SE of system. For solving these non-convex problems, an iterative optimization algorithm is developed to obtain the local optimal solution by exploiting second-order channel statistics of users. Compared with the traditional method, numerical results show that the proposed pilot and data power allocation schemes can achieve higher SE for spatially correlated massive MIMO system.
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