On Channel Estimation for Rician Fading with the Phase-Shift in Cell-Free Massive MIMO System

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 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-phaseaware-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.

[1]  T. Kailath,et al.  Estimation of Signal Parameters via Rotational Invariance Techniques - ESPRIT , 1986, MILCOM 1986 - IEEE Military Communications Conference: Communications-Computers: Teamed for the 90's.

[2]  Erik G. Larsson,et al.  Cell-Free Massive MIMO Versus Small Cells , 2016, IEEE Transactions on Wireless Communications.

[3]  Bhaskar D. Rao,et al.  Precoding and Power Optimization in Cell-Free Massive MIMO Systems , 2017, IEEE Transactions on Wireless Communications.

[4]  Erik G. Larsson,et al.  Cell-Free Massive MIMO: Uniformly great service for everyone , 2015, 2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[5]  Yi Wang,et al.  A current perspective on distributed antenna systems for the downlink of cellular systems , 2013, IEEE Communications Magazine.

[6]  Ralph Otto Schmidt,et al.  A signal subspace approach to multiple emitter location and spectral estimation , 1981 .

[7]  Thomas L. Marzetta,et al.  Cell-Free Massive MIMO systems , 2015, 2015 49th Asilomar Conference on Signals, Systems and Computers.

[8]  Jing Wang,et al.  Distributed wireless communication system: a new architecture for future public wireless access , 2003, IEEE Commun. Mag..

[9]  Emil Björnson,et al.  Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI , 2010, IEEE Transactions on Signal Processing.

[10]  Emil Björnson,et al.  Scalable Cell-Free Massive MIMO Systems , 2019, IEEE Transactions on Communications.

[11]  Thomas L. Marzetta,et al.  Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas , 2010, IEEE Transactions on Wireless Communications.

[12]  Erik G. Larsson,et al.  On the performance of cell-free massive MIMO with short-term power constraints , 2016, 2016 IEEE 21st International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD).

[13]  Muhammad Ali Imran,et al.  5G Backhaul Challenges and Emerging Research Directions: A Survey , 2016, IEEE Access.

[14]  Emil Björnson,et al.  Ubiquitous cell-free Massive MIMO communications , 2018, EURASIP Journal on Wireless Communications and Networking.

[15]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[16]  Jeffrey G. Andrews,et al.  Downlink performance and capacity of distributed antenna systems in a multicell environment , 2007, IEEE Transactions on Wireless Communications.

[17]  Kien T. Truong,et al.  The viability of distributed antennas for massive MIMO systems , 2013, 2013 Asilomar Conference on Signals, Systems and Computers.

[18]  Emil Björnson,et al.  Optimality Properties, Distributed Strategies, and Measurement-Based Evaluation of Coordinated Multicell OFDMA Transmission , 2011, IEEE Transactions on Signal Processing.

[19]  Emil Björnson,et al.  Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency , 2018, Found. Trends Signal Process..

[20]  Erik G. Larsson,et al.  Fundamentals of massive MIMO , 2016, SPAWC.

[21]  Hien Quoc Ngo,et al.  CELL-FREE MASSIVE MIMO SYSTEMS WITH MULTI-ANTENNA USERS , 2018, 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[22]  Thomas L. Marzetta,et al.  A Macro Cellular Wireless Network with Uniformly High User Throughputs , 2014, 2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall).

[23]  Daniel Castanheira,et al.  Distributed antenna system capacity scaling [Coordinated and Distributed MIMO] , 2010, IEEE Wireless Communications.

[24]  Bo Ai,et al.  Uplink Performance of Cell-Free Massive MIMO Over Spatially Correlated Rician Fading Channels , 2021, IEEE Communications Letters.

[25]  Emil Björnson,et al.  Performance Analysis and Power Control of Cell-Free Massive MIMO Systems With Hardware Impairments , 2018, IEEE Access.