Channel Estimation Based Intelligent Reflecting Surfaces for Massive MIMO System Considering Spatially Correlated Channels
Corresponding Author
Jamal Amadid
Higher Institute of Engineering and Business (ISGA), Marrakesh, Morocco
Correspondence: Jamal Amadid ([email protected])
Search for more papers by this authorAsma Khabba
Instrumentation, Signals and Physical Systems (I2SP) Group, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco
Search for more papers by this authorZakaria El Ouadi
Instrumentation, Signals and Physical Systems (I2SP) Group, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco
Search for more papers by this authorAbdelouhab Zeroual
Instrumentation, Signals and Physical Systems (I2SP) Group, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco
Search for more papers by this authorCorresponding Author
Jamal Amadid
Higher Institute of Engineering and Business (ISGA), Marrakesh, Morocco
Correspondence: Jamal Amadid ([email protected])
Search for more papers by this authorAsma Khabba
Instrumentation, Signals and Physical Systems (I2SP) Group, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco
Search for more papers by this authorZakaria El Ouadi
Instrumentation, Signals and Physical Systems (I2SP) Group, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco
Search for more papers by this authorAbdelouhab Zeroual
Instrumentation, Signals and Physical Systems (I2SP) Group, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco
Search for more papers by this authorABSTRACT
Recently, many fundamental technologies have emerged to boost and improve the performance of existing and future wireless communication systems, one of these technologies being the utilization of intelligent reflecting surfaces (IRS). This work investigates the channel estimation and spectral efficiency (SE) of a Massive multiple-input multiple-output (M-MIMO) system based on an IRS for spatially correlated channels. The system's performance is evaluated in terms of both channel estimation and SE, utilizing the minimum mean square error (MMSE) estimator. Accordingly, a three-stage M-MIMO channel estimation assisted by an IRS using the pilot sequences in a more practical propagation environment, that is, spatially correlated channels, wherein the IRS components empower the BS to estimate the uplink reflected channel state information (CSI) (i.e., estimation of reflected channels). In addition, the three stages channel estimate based on pilot sequences is computed and evaluated using the MMSE estimator and the normalized-mean square error (NMSE) metric, respectively. In this framework, this work proposes a local multiple scattering (LMS) model that describes the spatial correlation (SC) over the proposed uniform rectangular array (URA) by relying on the LMS model that describes the SC over a ULA configuration. In other words, using the Kronecker product (KP) of the correlation matrix constructed through a ULA, we built the correlation matrix that describes the SC over the proposed URA. In contrast to the linear array, the proposed array design is more constrained, leading to a higher degree of SC and better channel estimation quality. Numerical results are provided to assert and validate both our theoretical expression, as well as, the effectiveness of the proposed configuration.
Conflicts of Interest
The authors declare no conflicts of interest.
Open Research
Data Availability Statement
No data was used for the research described in the article.
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