Abstract
Channel estimation (CE) is a crucial phase in wireless communication systems, especially in cell-free (CF) massive multiple input multiple output (M-MIMO) since it is a dynamic wireless network. Therefore, this work is introduced to study CE for the CF M-MIMO system in the uplink phase, wherein the performance of different estimators are evaluated, discussed, and compared in various situations. We assume the scenario in which each access point has prior knowledge of the channel statistics. The phase-aware-minimum mean square error (PA-MMSE) estimator, the non-phase-aware-MMSE (NPA-MMSE) estimator, and the least-squares estimator are the three estimators which are exploited in this work. Besides, we consider the Rician fading channel in which the line-of-sight path is realized with a phase-shift that models the users’ mobility where the considered phase-shift follows a uniform distribution. On the other hand, the mean-squared error metric is employed in order to evaluate the performance of each estimator, where an analytical and simulated result is provided for the PA-MMSE estimator and the NPA-MMSE estimator in order to assert our numerical results.
Highlights
The employment of a large number of antennas at the base stations knows, in the literature of communication systems as the massive multiple input multiple output (MMIMO) technology [1], where this technology can offer good service to many users even if in the worst scenario, in which the users are simultaneously served [2, 3]
The traditional LS estimator, which is among the non-bayesian estimators that have no information concerning channel statistic (i.e., large-scale fading (LSF) βm,k, gm,k, and the phase-shift χm,k) [26], where this estimator aims to minimize the difference between the received signal and the desired signal as follows
As indicates from the figure, better performance is achieved by the phase-aware-minimum mean square error (PA-MMSE) estimator since the PA-MMSE estimator has complete knowledge of the phase-shift, the LSF coefficient, and the channel average gk
Summary
The employment of a large number of antennas at the base stations knows, in the literature of communication systems as the massive multiple input multiple output (MMIMO) technology [1], where this technology can offer good service to many users even if in the worst scenario, in which the users are simultaneously served [2, 3]. CF M-MIMO offers a significant gain for the fifth generation (5G) wireless communication systems, in which an enormous number of access points (APs) serve a relatively small number of users in the same time-frequency resources. CF M-MIMO is an innovative technology that enables such a system to operate with a more important potential for 5G wireless communication using only a straightforward signal processing technique. This technology can offer energy efficiency (EE), substantial throughput, and high precision. Thereby, due to the increased demand for connectivity, and the requirement to provide users with good service, the distributed M-MIMO design is expected to provide much improvement for wireless communication systems. CF M-MIMO has garnered significant attention from researchers
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