Abstract
Reducing the computational complexity of the modern wireless communication systems such as massive MIMO configurations is of utmost interest. In this paper, we propose algorithms which can be used to accelerate matrix inversion and reduce the complexity of common spatial multiplexing schemes in massive MIMO systems. Here, we specifically investigate the performance of the proposed methods in systems that utilize STBC (Space-Time Block Code) in the uplink of dynamic massive MIMO systems for different scenarios. A multi-user system in which the base station is equipped with a large number of antennas and each user has two antennas is considered. In addition, users can enter or exit the system dynamically. For a given space-time block coding/decoding scheme, the computational complexity of the receiver will be significantly reduced by employing the proposed methods. The first approach is utilizing Neumann series to approximate the inverse matrix for linear decoders. The second tactic is reducing the computational complexity of the STBC decoders when a user is added to system or removed from it. In the proposed schemes, the matrix inversion for ZF and MMSE decoding is derived from inversing a partitioned matrix and Woodbury matrix identity. Furthermore, the suggested techniques can be utilized when the number of users is fixed but the CSI changes for a particular user. The mathematical equations for both approaches are derived and the complexity of the suggested methods is compared to the direct computation of the inverse matrix. Moreover, the performance of the proposed algorithms is evaluated in terms of the system BER (bit error rate). Evaluations confirm the effectiveness of the proposed approaches.
Highlights
Massive Multiple-input multiple-output (MIMO) has been explored as one of the underlying technologies for the new generations of wireless communication systems in recent years [1]
It has been demonstrated that as long as the number of Base station (BS) antennas is much larger than the number of users, Block error rate (BLER) is similar to the case when an exact inverse is calculated while the required computations is reduced by one order of magnitude
For the selected Space-time block code (STBC) scheme, based on the matrix inversion lemmas such as the inverse of a partitioned matrix and the Woodbury formula [15], we propose and evaluate low-complexity methods to speed up STBC ZF and Minimum mean square error (MMSE) decoders
Summary
Massive MIMO (multiple-input multiple-output) has been explored as one of the underlying technologies for the new generations of wireless communication systems in recent years [1]. In massive MIMO configuration for cellular communications the BS (base station) is equipped with a large number of antennas and simultaneously serves multiple users. In such formations high capacity, energy efficiency as well as high reliability can be achieved via relatively simple signal processing techniques [2]. Complexity reduction has been investigated for the cases in which a user is added to the cell or removed from it as well as the case when a user’s CSI (channel state information) is changed In these circumstances, if we calculate the exact inverse of the decoder matrix using conventional methods such as Cholesky decomposition, high computational load will be imposed on the system. We propose calculating the exact inverse matrix by utilizing available information and matrix inversion identities to update the current inverse matrix
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: EURASIP Journal on Wireless Communications and Networking
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
